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class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 19166</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: optimal model</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19166</span> Toward a Characteristic Optimal Power Flow Model for Temporal Constraints</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zongjie%20Wang">Zongjie Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhizhong%20Guo"> Zhizhong Guo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> While the regular optimal power flow model focuses on a single time scan, the optimization of power systems is typically intended for a time duration with respect to a desired objective function. In this paper, a temporal optimal power flow model for a time period is proposed. To reduce the computation burden needed for calculating temporal optimal power flow, a characteristic optimal power flow model is proposed, which employs different characteristic load patterns to represent the objective function and security constraints. A numerical method based on the interior point method is also proposed for solving the characteristic optimal power flow model. Both the temporal optimal power flow model and characteristic optimal power flow model can improve the systems’ desired objective function for the entire time period. Numerical studies are conducted on the IEEE 14 and 118-bus test systems to demonstrate the effectiveness of the proposed characteristic optimal power flow model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimal%20power%20flow" title="optimal power flow">optimal power flow</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20period" title=" time period"> time period</a>, <a href="https://publications.waset.org/abstracts/search?q=security" title=" security"> security</a>, <a href="https://publications.waset.org/abstracts/search?q=economy" title=" economy"> economy</a> </p> <a href="https://publications.waset.org/abstracts/61552/toward-a-characteristic-optimal-power-flow-model-for-temporal-constraints" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61552.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">461</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19165</span> Effect of Variable Fluxes on Optimal Flux Distribution in a Metabolic Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ehsan%20Motamedian">Ehsan Motamedian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Finding all optimal flux distributions of a metabolic model is an important challenge in systems biology. In this paper, a new algorithm is introduced to identify all alternate optimal solutions of a large scale metabolic network. The algorithm reduces the model to decrease computations for finding optimal solutions. The algorithm was implemented on the Escherichia coli metabolic model to find all optimal solutions for lactate and acetate production. There were more optimal flux distributions when acetate production was optimized. The model was reduced from 1076 to 80 variable fluxes for lactate while it was reduced to 91 variable fluxes for acetate. These 11 more variable fluxes resulted in about three times more optimal flux distributions. Variable fluxes were from 12 various metabolic pathways and most of them belonged to nucleotide salvage and extra cellular transport pathways. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flux%20variability" title="flux variability">flux variability</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20network" title=" metabolic network"> metabolic network</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed-integer%20linear%20programming" title=" mixed-integer linear programming"> mixed-integer linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20optimal%20solutions" title=" multiple optimal solutions"> multiple optimal solutions</a> </p> <a href="https://publications.waset.org/abstracts/15698/effect-of-variable-fluxes-on-optimal-flux-distribution-in-a-metabolic-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15698.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">441</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19164</span> An Elbow Biomechanical Model and Its Coefficients Adjustment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jie%20Bai">Jie Bai</a>, <a href="https://publications.waset.org/abstracts/search?q=Yongsheng%20Gao"> Yongsheng Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=Shengxin%20Wang"> Shengxin Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jie%20Zhao"> Jie Zhao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Through the establishment of the elbow biomechanical model, it can provide theoretical guide for rehabilitation therapy on the upper limb of the human body. A biomechanical model of the elbow joint can be built by the connection of muscle force model and elbow dynamics. But there are many undetermined coefficients in the model like the optimal joint angle and optimal muscle force which are usually specified as the experimental parameters of other workers. Because of the individual differences, there is a certain deviation of the final result. To this end, the RMS value of the deviation between the actual angle and calculated angle is considered. A set of coefficients which lead to the minimum RMS value will be chosen to be the optimal parameters. The direct search method and the conjugacy search method are used to get the optimal parameters, thus the model can be more accurate and mode adaptability. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=elbow%20biomechanical%20model" title="elbow biomechanical model">elbow biomechanical model</a>, <a href="https://publications.waset.org/abstracts/search?q=RMS" title=" RMS"> RMS</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20search" title=" direct search"> direct search</a>, <a href="https://publications.waset.org/abstracts/search?q=conjugacy%20search" title=" conjugacy search"> conjugacy search</a> </p> <a href="https://publications.waset.org/abstracts/7188/an-elbow-biomechanical-model-and-its-coefficients-adjustment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7188.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">553</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19163</span> Optimal Location of the I/O Point in the Parking System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jing%20Zhang">Jing Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jie%20Chen"> Jie Chen</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parking%20system" title="parking system">parking system</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20location" title=" optimal location"> optimal location</a>, <a href="https://publications.waset.org/abstracts/search?q=response%20time" title=" response time"> response time</a>, <a href="https://publications.waset.org/abstracts/search?q=S%2FR%20machine" title=" S/R machine"> S/R machine</a> </p> <a href="https://publications.waset.org/abstracts/73138/optimal-location-of-the-io-point-in-the-parking-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73138.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">419</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19162</span> Controlled Chemotherapy Strategy Applied to HIV Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shohel%20Ahmed">Shohel Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Md.%20Abdul%20Alim"> Md. Abdul Alim</a>, <a href="https://publications.waset.org/abstracts/search?q=Sumaiya%20Rahman"> Sumaiya Rahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Optimal control can be helpful to test and compare different vaccination strategies of a certain disease. The mathematical model of HIV we consider here is a set of ordinary differential equations (ODEs) describing the interactions of CD4+T cells of the immune system with the human immunodeficiency virus (HIV). As an early treatment setting, we investigate an optimal chemotherapy strategy where control represents the percentage of effect the chemotherapy has on the system. The aim is to obtain a new optimal chemotherapeutic strategy where an isoperimetric constraint on the chemotherapy supply plays a crucial role. We outline the steps in formulating an optimal control problem, derive optimality conditions and demonstrate numerical results of an optimal control for the model. Numerical results illustrate how such a constraint alters the optimal vaccination schedule and its effect on cell-virus interactions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chemotherapy%20of%20HIV" title="chemotherapy of HIV">chemotherapy of HIV</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control%20involving%20ODEs" title=" optimal control involving ODEs"> optimal control involving ODEs</a>, <a href="https://publications.waset.org/abstracts/search?q=optimality%20conditions" title=" optimality conditions"> optimality conditions</a>, <a href="https://publications.waset.org/abstracts/search?q=Pontryagin%E2%80%99s%20maximum%20principle" title=" Pontryagin’s maximum principle"> Pontryagin’s maximum principle</a> </p> <a href="https://publications.waset.org/abstracts/65162/controlled-chemotherapy-strategy-applied-to-hiv-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65162.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">340</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19161</span> Optimal Management of Internal Capital of Company</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Sadallah">S. Sadallah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=management" title="management">management</a>, <a href="https://publications.waset.org/abstracts/search?q=software" title=" software"> software</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal" title=" optimal"> optimal</a>, <a href="https://publications.waset.org/abstracts/search?q=greedy%20algorithm" title=" greedy algorithm"> greedy algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=graph-diagram" title=" graph-diagram"> graph-diagram</a> </p> <a href="https://publications.waset.org/abstracts/47406/optimal-management-of-internal-capital-of-company" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47406.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">290</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19160</span> Predictive Models of Ruin Probability in Retirement Withdrawal Strategies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuanjin%20Liu">Yuanjin Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ruin%20probability" title="ruin probability">ruin probability</a>, <a href="https://publications.waset.org/abstracts/search?q=retirement%20withdrawal%20strategies" title=" retirement withdrawal strategies"> retirement withdrawal strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20models" title=" predictive models"> predictive models</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20model" title=" optimal model"> optimal model</a> </p> <a href="https://publications.waset.org/abstracts/147438/predictive-models-of-ruin-probability-in-retirement-withdrawal-strategies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/147438.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">79</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19159</span> Licensing in a Hotelling Model with Quadratic Transportation Costs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fehmi%20Bouguezzi">Fehmi Bouguezzi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper studies optimal licensing regimes in a linear Hotelling model where firms are located at the end points of the city and where the transportation cost is not linear but quadratic. We study for that a more general cost function and we try to compare the findings with the results of the linear cost. We find the same optimal licensing regimes. A per unit royalty is optimal when innovation is not drastic and no licensing is better when innovation is drastic. We also find that no licensing is always better than fixed fee licensing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hotelling%20model" title="Hotelling model">Hotelling model</a>, <a href="https://publications.waset.org/abstracts/search?q=technology%20transfer" title=" technology transfer"> technology transfer</a>, <a href="https://publications.waset.org/abstracts/search?q=patent%20licensing" title=" patent licensing"> patent licensing</a>, <a href="https://publications.waset.org/abstracts/search?q=quadratic%20transportation%20cost" title=" quadratic transportation cost"> quadratic transportation cost</a> </p> <a href="https://publications.waset.org/abstracts/15248/licensing-in-a-hotelling-model-with-quadratic-transportation-costs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15248.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">353</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19158</span> An Optimal Control Model for the Dynamics of Visceral Leishmaniasis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ibrahim%20M.%20Elmojtaba">Ibrahim M. Elmojtaba</a>, <a href="https://publications.waset.org/abstracts/search?q=Rayan%20M.%20Altayeb"> Rayan M. Altayeb</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Visceral leishmaniasis (VL) is a vector-borne disease caused by the protozoa parasite of the genus leishmania. The transmission of the parasite to humans and animals occurs via the bite of adult female sandflies previously infected by biting and sucking blood of an infectious humans or animals. In this paper we use a previously proposed model, and then applied two optimal controls, namely treatment and vaccination to that model to investigate optimal strategies for controlling the spread of the disease using treatment and vaccination as the system control variables. The possible impact of using combinations of the two controls, either one at a time or two at a time on the spread of the disease is also examined. Our results provide a framework for vaccination and treatment strategies to reduce susceptible and infection individuals of VL in five years. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=visceral%20leishmaniasis" title="visceral leishmaniasis">visceral leishmaniasis</a>, <a href="https://publications.waset.org/abstracts/search?q=treatment" title=" treatment"> treatment</a>, <a href="https://publications.waset.org/abstracts/search?q=vaccination" title=" vaccination"> vaccination</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20control" title=" optimal control"> optimal control</a>, <a href="https://publications.waset.org/abstracts/search?q=numerical%20simulation" title=" numerical simulation"> numerical simulation</a> </p> <a href="https://publications.waset.org/abstracts/39487/an-optimal-control-model-for-the-dynamics-of-visceral-leishmaniasis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39487.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">407</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19157</span> Analysis on Prediction Models of TBM Performance and Selection of Optimal Input Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hang%20Lo%20Lee">Hang Lo Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Ki%20Il%20Song"> Ki Il Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Hee%20Hwan%20Ryu"> Hee Hwan Ryu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=TBM%20performance%20prediction%20model" title="TBM performance prediction model">TBM performance prediction model</a>, <a href="https://publications.waset.org/abstracts/search?q=classification%20system" title=" classification system"> classification system</a>, <a href="https://publications.waset.org/abstracts/search?q=simple%20regression%20analysis" title=" simple regression analysis"> simple regression analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=residual%20analysis" title=" residual analysis"> residual analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20input%20parameters" title=" optimal input parameters"> optimal input parameters</a> </p> <a href="https://publications.waset.org/abstracts/52738/analysis-on-prediction-models-of-tbm-performance-and-selection-of-optimal-input-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52738.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">314</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19156</span> Optimal Driving Strategies for a Hybrid Street Type Motorcycle: Modelling and Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jhon%20Vargas">Jhon Vargas</a>, <a href="https://publications.waset.org/abstracts/search?q=Gilberto%20Osorio-Gomez"> Gilberto Osorio-Gomez</a>, <a href="https://publications.waset.org/abstracts/search?q=Tatiana%20Manrique"> Tatiana Manrique</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents an optimal driving strategy proposal for a 125 c.c. street-type hybrid electric motorcycle with a parallel configuration. The results presented in this article are complementary regarding the control proposal of a hybrid motorcycle. In order to carry out such developments, a representative dynamic model of the motorcycle is used, in which also are described different optimization functionalities for predetermined driving modes. The purpose is to implement an off-line optimal driving strategy which distributes energy to both engines by minimizing an objective torque requirement function. An optimal dynamic contribution is found from the optimization routine, and the optimal percentage contribution for vehicle cruise speed is implemented in the proposed online PID controller. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20model" title="dynamic model">dynamic model</a>, <a href="https://publications.waset.org/abstracts/search?q=driving%20strategies" title=" driving strategies"> driving strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20hybrid%20motorcycle" title=" parallel hybrid motorcycle"> parallel hybrid motorcycle</a>, <a href="https://publications.waset.org/abstracts/search?q=PID%20controller" title=" PID controller"> PID controller</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/133692/optimal-driving-strategies-for-a-hybrid-street-type-motorcycle-modelling-and-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133692.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">200</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19155</span> Two-Warehouse Inventory Model for Deteriorating Items with Inventory-Level-Dependent Demand under Two Dispatching Policies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lei%20Zhao">Lei Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhe%20Yuan"> Zhe Yuan</a>, <a href="https://publications.waset.org/abstracts/search?q=Wenyue%20Kuang"> Wenyue Kuang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=FIFO%20model" title="FIFO model">FIFO model</a>, <a href="https://publications.waset.org/abstracts/search?q=inventory-level-dependent" title=" inventory-level-dependent"> inventory-level-dependent</a>, <a href="https://publications.waset.org/abstracts/search?q=LIFO%20model" title=" LIFO model"> LIFO model</a>, <a href="https://publications.waset.org/abstracts/search?q=two-warehouse%20inventory" title=" two-warehouse inventory"> two-warehouse inventory</a> </p> <a href="https://publications.waset.org/abstracts/50101/two-warehouse-inventory-model-for-deteriorating-items-with-inventory-level-dependent-demand-under-two-dispatching-policies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50101.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">286</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19154</span> Study on Optimal Control Strategy of PM2.5 in Wuhan, China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qiuling%20Xie">Qiuling Xie</a>, <a href="https://publications.waset.org/abstracts/search?q=Shanliang%20Zhu"> Shanliang Zhu</a>, <a href="https://publications.waset.org/abstracts/search?q=Zongdi%20Sun"> Zongdi Sun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=grey%20relational%20degree" title="grey relational degree">grey relational degree</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple%20linear%20regression" title=" multiple linear regression"> multiple linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=nonlinear%20programming" title=" nonlinear programming"> nonlinear programming</a> </p> <a href="https://publications.waset.org/abstracts/54538/study-on-optimal-control-strategy-of-pm25-in-wuhan-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54538.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">307</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19153</span> Portfolio Selection with Constraints on Trading Frequency</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Min%20Dai">Min Dai</a>, <a href="https://publications.waset.org/abstracts/search?q=Hong%20Liu"> Hong Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Shuaijie%20Qian"> Shuaijie Qian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We study a portfolio selection problem of an investor who faces constraints on rebalancing frequency, which is common in pension fund investment. We formulate it as a multiple optimal stopping problem and utilize the dynamic programming principle. By numerically solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation, we find a series of free boundaries characterizing optimal strategy, and the constraints significantly impact the optimal strategy. Even in the absence of transaction costs, there is a no-trading region, depending on the number of the remaining trading chances. We also find that the equivalent wealth loss caused by the constraints is large. In conclusion, our model clarifies the impact of the constraints on transaction frequency on the optimal strategy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=portfolio%20selection" title="portfolio selection">portfolio selection</a>, <a href="https://publications.waset.org/abstracts/search?q=rebalancing%20frequency" title=" rebalancing frequency"> rebalancing frequency</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20strategy" title=" optimal strategy"> optimal strategy</a>, <a href="https://publications.waset.org/abstracts/search?q=free%20boundary" title=" free boundary"> free boundary</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20stopping" title=" optimal stopping"> optimal stopping</a> </p> <a href="https://publications.waset.org/abstracts/171745/portfolio-selection-with-constraints-on-trading-frequency" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/171745.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">95</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19152</span> Assessment of Korea's Natural Gas Portfolio Considering Panama Canal Expansion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Juhan%20Kim">Juhan Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Jinsoo%20Kim"> Jinsoo Kim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> South Korea cannot import natural gas in any form other than LNG because of the division of South and North Korea. Further, the high proportion of natural gas in the national energy mix makes this resource crucial for energy security in Korea. Expansion of Panama Canal will allow for reducing the cost of shipping between the Far East and U.S East. Panama Canal expansion can have significant impacts on South Korea. Due to this situation, we review the natural gas optimal portfolio by considering the uniqueness of the Korean Natural gas market and expansion of Panama Canal. In order to assess Korea’s natural gas optimal portfolio, we developed natural gas portfolio model. The model comprises two steps. First, to obtain the optimal long-term spot contract ratio, the study examines the price level and the correlation between spot and long-term contracts by using the Markowitz, portfolio model. The optimal long-term spot contract ratio follows the efficient frontier of the cost/risk level related to this price level and degree of correlation. Second, by applying the obtained long-term contract purchase ratio as the constraint in the linear programming portfolio model, we determined the natural gas optimal import portfolio that minimizes total intangible and tangible costs. Using this model, we derived the optimal natural gas portfolio considering the expansion of Panama Canal. Based on these results, we assess the portfolio for natural gas import to Korea from the perspective of energy security and present some relevant policy proposals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=natural%20gas" title="natural gas">natural gas</a>, <a href="https://publications.waset.org/abstracts/search?q=Panama%20Canal" title=" Panama Canal"> Panama Canal</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20analysis" title=" portfolio analysis"> portfolio analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=South%20Korea" title=" South Korea"> South Korea</a> </p> <a href="https://publications.waset.org/abstracts/67569/assessment-of-koreas-natural-gas-portfolio-considering-panama-canal-expansion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67569.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">296</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19151</span> Comparative Study of Deep Reinforcement Learning Algorithm Against Evolutionary Algorithms for Finding the Optimal Values in a Simulated Environment Space</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Akshay%20Paranjape">Akshay Paranjape</a>, <a href="https://publications.waset.org/abstracts/search?q=Nils%20Plettenberg"> Nils Plettenberg</a>, <a href="https://publications.waset.org/abstracts/search?q=Robert%20Schmitt"> Robert Schmitt</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reinforcement%20learning" title="reinforcement learning">reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithms" title=" evolutionary algorithms"> evolutionary algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=production%20process%20optimization" title=" production process optimization"> production process optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=real-time%20optimization" title=" real-time optimization"> real-time optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid-MPO" title=" hybrid-MPO"> hybrid-MPO</a> </p> <a href="https://publications.waset.org/abstracts/159906/comparative-study-of-deep-reinforcement-learning-algorithm-against-evolutionary-algorithms-for-finding-the-optimal-values-in-a-simulated-environment-space" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/159906.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">119</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19150</span> An Overbooking Model for Car Rental Service with Different Types of Cars</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Naragain%20Phumchusri">Naragain Phumchusri</a>, <a href="https://publications.waset.org/abstracts/search?q=Kittitach%20Pongpairoj"> Kittitach Pongpairoj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Overbooking is a very useful revenue management technique that could help reduce costs caused by either undersales or oversales. In this paper, we propose an overbooking model for two types of cars that can minimize the total cost for car rental service. With two types of cars, there is an upgrade possibility for lower type to upper type. This makes the model more complex than one type of cars scenario. We have found that convexity can be proved in this case. Sensitivity analysis of the parameters is conducted to observe the effects of relevant parameters on the optimal solution. Model simplification is proposed using multiple linear regression analysis, which can help estimate the optimal overbooking level using appropriate independent variables. The results show that the overbooking level from multiple linear regression model is relatively close to the optimal solution (with the adjusted R-squared value of at least 72.8%). To evaluate the performance of the proposed model, the total cost was compared with the case where the decision maker uses a naïve method for the overbooking level. It was found that the total cost from optimal solution is only 0.5 to 1 percent (on average) lower than the cost from regression model, while it is approximately 67% lower than the cost obtained by the naïve method. It indicates that our proposed simplification method using regression analysis can effectively perform in estimating the overbooking level. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=overbooking" title="overbooking">overbooking</a>, <a href="https://publications.waset.org/abstracts/search?q=car%20rental%20industry" title=" car rental industry"> car rental industry</a>, <a href="https://publications.waset.org/abstracts/search?q=revenue%20management" title=" revenue management"> revenue management</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20model" title=" stochastic model"> stochastic model</a> </p> <a href="https://publications.waset.org/abstracts/77611/an-overbooking-model-for-car-rental-service-with-different-types-of-cars" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/77611.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">176</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19149</span> Analytical Solutions for Corotational Maxwell Model Fluid Arising in Wire Coating inside a Canonical Die </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Sohail%20Khan">Muhammad Sohail Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=Rehan%20Ali%20Shah"> Rehan Ali Shah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present paper applies the optimal homotopy perturbation method (OHPM) and the optimal homotopy asymptotic method (OHAM) introduced recently to obtain analytic approximations of the non-linear equations modeling the flow of polymer in case of wire coating of a corotational Maxwell fluid. Expression for the velocity field is obtained in non-dimensional form. Comparison of the results obtained by the two methods at different values of non-dimensional parameter l<sub>10</sub>, reveal that the OHPM is more effective and easy to use. The OHPM solution can be improved even working in the same order of approximation depends on the choices of the auxiliary functions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=corotational%20Maxwell%20model" title="corotational Maxwell model">corotational Maxwell model</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20homotopy%20asymptotic%20method" title=" optimal homotopy asymptotic method"> optimal homotopy asymptotic method</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20homotopy%20perturbation%20method" title=" optimal homotopy perturbation method"> optimal homotopy perturbation method</a>, <a href="https://publications.waset.org/abstracts/search?q=wire%20coating%20die" title=" wire coating die"> wire coating die</a> </p> <a href="https://publications.waset.org/abstracts/54265/analytical-solutions-for-corotational-maxwell-model-fluid-arising-in-wire-coating-inside-a-canonical-die" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54265.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">340</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19148</span> Model of Optimal Centroids Approach for Multivariate Data Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pham%20Van%20Nha">Pham Van Nha</a>, <a href="https://publications.waset.org/abstracts/search?q=Le%20Cam%20Binh"> Le Cam Binh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analysis%20of%20optimization" title="analysis of optimization">analysis of optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence%20based%20optimization" title=" artificial intelligence based optimization"> artificial intelligence based optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20for%20learning%20and%20data%20analysis" title=" optimization for learning and data analysis"> optimization for learning and data analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=global%20optimization" title=" global optimization"> global optimization</a> </p> <a href="https://publications.waset.org/abstracts/126058/model-of-optimal-centroids-approach-for-multivariate-data-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/126058.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">214</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19147</span> Product Development in Company</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Giorgi%20Methodishvili">Giorgi Methodishvili</a>, <a href="https://publications.waset.org/abstracts/search?q=Iuliia%20Methodishvili"> Iuliia Methodishvili</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper product development algorithm is used to determine the optimal management of financial resources in company. Aspects of financial management considered include put initial investment, examine all possible ways to solve the problem and the optimal rotation length of profit. The software of given problems is based using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=management" title="management">management</a>, <a href="https://publications.waset.org/abstracts/search?q=software" title=" software"> software</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal" title=" optimal"> optimal</a>, <a href="https://publications.waset.org/abstracts/search?q=greedy%20algorithm" title=" greedy algorithm"> greedy algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=graph-diagram" title=" graph-diagram"> graph-diagram</a> </p> <a href="https://publications.waset.org/abstracts/182730/product-development-in-company" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/182730.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">62</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19146</span> Dynamic Correlations and Portfolio Optimization between Islamic and Conventional Equity Indexes: A Vine Copula-Based Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Imen%20Dhaou">Imen Dhaou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study examines conditional Value at Risk by applying the GJR-EVT-Copula model, and finds the optimal portfolio for eight Dow Jones Islamic-conventional pairs. Our methodology consists of modeling the data by a bivariate GJR-GARCH model in which we extract the filtered residuals and then apply the Peak over threshold model (POT) to fit the residual tails in order to model marginal distributions. After that, we use pair-copula to find the optimal portfolio risk dependence structure. Finally, with Monte Carlo simulations, we estimate the Value at Risk (VaR) and the conditional Value at Risk (CVaR). The empirical results show the VaR and CVaR values for an equally weighted portfolio of Dow Jones Islamic-conventional pairs. In sum, we found that the optimal investment focuses on Islamic-conventional US Market index pairs because of high investment proportion; however, all other index pairs have low investment proportion. These results deliver some real repercussions for portfolio managers and policymakers concerning to optimal asset allocations, portfolio risk management and the diversification advantages of these markets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CVaR" title="CVaR">CVaR</a>, <a href="https://publications.waset.org/abstracts/search?q=Dow%20Jones%20Islamic%20index" title=" Dow Jones Islamic index"> Dow Jones Islamic index</a>, <a href="https://publications.waset.org/abstracts/search?q=GJR-GARCH-EVT-pair%20copula" title=" GJR-GARCH-EVT-pair copula"> GJR-GARCH-EVT-pair copula</a>, <a href="https://publications.waset.org/abstracts/search?q=portfolio%20optimization" title=" portfolio optimization"> portfolio optimization</a> </p> <a href="https://publications.waset.org/abstracts/81937/dynamic-correlations-and-portfolio-optimization-between-islamic-and-conventional-equity-indexes-a-vine-copula-based-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81937.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">262</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19145</span> Optimal Evaluation of Weather Risk Insurance for Wheat</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Slim%20Amami">Slim Amami</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=agriculture" title="agriculture">agriculture</a>, <a href="https://publications.waset.org/abstracts/search?q=database" title=" database"> database</a>, <a href="https://publications.waset.org/abstracts/search?q=meteorological%20factors" title=" meteorological factors"> meteorological factors</a>, <a href="https://publications.waset.org/abstracts/search?q=production%20model" title=" production model"> production model</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20price" title=" optimal price "> optimal price </a> </p> <a href="https://publications.waset.org/abstracts/10722/optimal-evaluation-of-weather-risk-insurance-for-wheat" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/10722.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">225</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19144</span> Revisiting the Fiscal Theory of Sovereign Risk from the DSGE View</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eiji%20Okano">Eiji Okano</a>, <a href="https://publications.waset.org/abstracts/search?q=Kazuyuki%20Inagaki"> Kazuyuki Inagaki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We revisit Uribe's `Fiscal Theory of Sovereign Risk' advocating that there is a trade-off between stabilizing inflation and suppressing default. We develop a class of dynamic stochastic general equilibrium (DSGE) model with nominal rigidities and compare two de facto inflation stabilization policies, optimal monetary policy and optimal monetary and fiscal policy with the minimizing interest rate spread policy which completely suppress the default. Under the optimal monetary and fiscal policy, not only the nominal interest rate but also the tax rate work to minimize welfare costs through stabilizing inflation. Under the optimal monetary both inflation and output gap are completely stabilized although those are fluctuating under the optimal monetary policy. In addition, volatility in the default rate under the optimal monetary policy is considerably lower than one under the optimal monetary policy. Thus, there is not the SI-SD trade-off. In addition, while the minimizing interest rate spread policy makes inflation rate severely volatile, the optimal monetary and fiscal policy stabilize both the inflation and the default. A trade-off between stabilizing inflation and suppressing default is not so severe what pointed out by Uribe. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sovereign%20risk" title="sovereign risk">sovereign risk</a>, <a href="https://publications.waset.org/abstracts/search?q=optimal%20monetary%20policy" title=" optimal monetary policy"> optimal monetary policy</a>, <a href="https://publications.waset.org/abstracts/search?q=fiscal%20theory%20of%20the%20price%20level" title=" fiscal theory of the price level"> fiscal theory of the price level</a>, <a href="https://publications.waset.org/abstracts/search?q=DSGE" title=" DSGE"> DSGE</a> </p> <a href="https://publications.waset.org/abstracts/50808/revisiting-the-fiscal-theory-of-sovereign-risk-from-the-dsge-view" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50808.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">326</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19143</span> Optimal Trajectories for Highly Automated Driving</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christian%20Rathgeber">Christian Rathgeber</a>, <a href="https://publications.waset.org/abstracts/search?q=Franz%20Winkler"> Franz Winkler</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiaoyu%20Kang"> Xiaoyu Kang</a>, <a href="https://publications.waset.org/abstracts/search?q=Steffen%20M%C3%BCller"> Steffen Müller</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this contribution two approaches for calculating optimal trajectories for highly automated vehicles are presented and compared. The first one is based on a non-linear vehicle model, used for evaluation. The second one is based on a simplified model and can be implemented on a current ECU. In usual driving situations both approaches show very similar results. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=trajectory%20planning" title="trajectory planning">trajectory planning</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20method" title=" direct method"> direct method</a>, <a href="https://publications.waset.org/abstracts/search?q=indirect%20method" title=" indirect method"> indirect method</a>, <a href="https://publications.waset.org/abstracts/search?q=highly%20automated%20driving" title=" highly automated driving"> highly automated driving</a> </p> <a href="https://publications.waset.org/abstracts/22622/optimal-trajectories-for-highly-automated-driving" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/22622.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">540</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19142</span> Optimal Bayesian Control of the Proportion of Defectives in a Manufacturing Process</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Viliam%20Makis">Viliam Makis</a>, <a href="https://publications.waset.org/abstracts/search?q=Farnoosh%20Naderkhani"> Farnoosh Naderkhani</a>, <a href="https://publications.waset.org/abstracts/search?q=Leila%20Jafari"> Leila Jafari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a model and an algorithm for the calculation of the optimal control limit, average cost, sample size, and the sampling interval for an optimal Bayesian chart to control the proportion of defective items produced using a semi-Markov decision process approach. Traditional p-chart has been widely used for controlling the proportion of defectives in various kinds of production processes for many years. It is well known that traditional non-Bayesian charts are not optimal, but very few optimal Bayesian control charts have been developed in the literature, mostly considering finite horizon. The objective of this paper is to develop a fast computational algorithm to obtain the optimal parameters of a Bayesian p-chart. The decision problem is formulated in the partially observable framework and the developed algorithm is illustrated by a numerical example. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20control%20chart" title="Bayesian control chart">Bayesian control chart</a>, <a href="https://publications.waset.org/abstracts/search?q=semi-Markov%20decision%20process" title=" semi-Markov decision process"> semi-Markov decision process</a>, <a href="https://publications.waset.org/abstracts/search?q=quality%20control" title=" quality control"> quality control</a>, <a href="https://publications.waset.org/abstracts/search?q=partially%20observable%20process" title=" partially observable process"> partially observable process</a> </p> <a href="https://publications.waset.org/abstracts/49751/optimal-bayesian-control-of-the-proportion-of-defectives-in-a-manufacturing-process" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49751.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">326</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19141</span> Future Optimization of the Xin’anjiang Hydropower</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Zaman">Muhammad Zaman</a>, <a href="https://publications.waset.org/abstracts/search?q=Guohua%20Fang">Guohua Fang</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Saifullah">Muhammad Saifullah</a>, <a href="https://publications.waset.org/abstracts/search?q="></a> </p> <p class="card-text"><strong>Abstract:</strong></p> The presented study emphasize at an optimal model to compare past and future optimal hydropower generation. In order to get maximum benefits from the Xin’anjiang hydropower station a model is developed. A Particle Swarm Optimization (PSO) has purposed and past and future water flow is used to get the maximum benefits from future water resources in this study. The results revealed that the future hydropower generation is more than the past generation. This paper gives us idea that what could we get in the past using optimal method of electricity generation and what can we get in the future using this technique. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PSO" title="PSO">PSO</a>, <a href="https://publications.waset.org/abstracts/search?q=future%20water%20resources" title=" future water resources"> future water resources</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Xin%E2%80%99anjiang" title=" Xin’anjiang"> Xin’anjiang</a>, <a href="https://publications.waset.org/abstracts/search?q=" title=""></a> </p> <a href="https://publications.waset.org/abstracts/42727/future-optimization-of-the-xinanjiang-hydropower" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42727.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">447</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19140</span> A Stokes Optimal Control Model of Determining Cellular Interaction Forces during Gastrulation </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yuanhao%20Gao">Yuanhao Gao</a>, <a href="https://publications.waset.org/abstracts/search?q=Ping%20%20Lin"> Ping Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Kees%20Weijer"> Kees Weijer</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An optimal control system model is proposed for the cell flow in the process of chick embryo gastrulation in this paper. The target is to determine the cellular interaction forces which are hard to measure. This paper will take an approach to investigate the forces with the idea of the inverse problem. By choosing the forces as the control variable and regarding the cell flow as Stokes fluid, an objective functional will be established to match the numerical result of cell velocity with the experimental data. So that the forces could be determined by minimizing the objective functional. The Lagrange multiplier method is utilized to derive the state and adjoint equations consisting the optimal control system, which specifies the first-order necessary conditions. Finite element method is used to discretize and approximate equations. A conjugate gradient algorithm is given for solving the minimum solution of the system and determine the forces. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimal%20control%20model" title="optimal control model">optimal control model</a>, <a href="https://publications.waset.org/abstracts/search?q=Stokes%20equation" title=" Stokes equation"> Stokes equation</a>, <a href="https://publications.waset.org/abstracts/search?q=conjugate%20gradient%20method" title=" conjugate gradient method"> conjugate gradient method</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20element%20method" title=" finite element method"> finite element method</a>, <a href="https://publications.waset.org/abstracts/search?q=chick%20embryo%20gastrulation" title=" chick embryo gastrulation"> chick embryo gastrulation</a> </p> <a href="https://publications.waset.org/abstracts/52434/a-stokes-optimal-control-model-of-determining-cellular-interaction-forces-during-gastrulation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52434.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">264</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19139</span> Optimal Hedging of a Portfolio of European Options in an Extended Binomial Model under Proportional Transaction Costs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Norm%20Josephy">Norm Josephy</a>, <a href="https://publications.waset.org/abstracts/search?q=Lucy%20Kimball"> Lucy Kimball</a>, <a href="https://publications.waset.org/abstracts/search?q=Victoria%20Steblovskaya"> Victoria Steblovskaya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=extended%20binomial%20model" title="extended binomial model">extended binomial model</a>, <a href="https://publications.waset.org/abstracts/search?q=non-self-financing%20hedging" title=" non-self-financing hedging"> non-self-financing hedging</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=proportional%20transaction%20costs" title=" proportional transaction costs"> proportional transaction costs</a> </p> <a href="https://publications.waset.org/abstracts/83333/optimal-hedging-of-a-portfolio-of-european-options-in-an-extended-binomial-model-under-proportional-transaction-costs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83333.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">257</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19138</span> Hidden Markov Model for the Simulation Study of Neural States and Intentionality</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20B.%20Mishra">R. B. Mishra</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hiden%20markov%20model" title="hiden markov model">hiden markov model</a>, <a href="https://publications.waset.org/abstracts/search?q=believe%20desire%20intention" title=" believe desire intention"> believe desire intention</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20activation" title=" neural activation"> neural activation</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a> </p> <a href="https://publications.waset.org/abstracts/31030/hidden-markov-model-for-the-simulation-study-of-neural-states-and-intentionality" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31030.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">382</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19137</span> The Optimal Order Policy for the Newsvendor Model under Worker Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sunantha%20Teyarachakul">Sunantha Teyarachakul</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We consider the worker-learning Newsvendor Model, under the case of lost-sales for unmet demand, with the research objective of proposing the cost-minimization order policy and lot size, scheduled to arrive at the beginning of the selling-period. In general, the New Vendor Model is used to find the optimal order quantity for the perishable items such as fashionable products or those with seasonal demand or short-life cycles. Technically, it is used when the product demand is stochastic and available for the single selling-season, and when there is only a one time opportunity for the vendor to purchase, with possibly of long ordering lead-times. Our work differs from the classical Newsvendor Model in that we incorporate the human factor (specifically worker learning) and its influence over the costs of processing units into the model. We describe this by using the well-known Wright’s Learning Curve. Most of the assumptions of the classical New Vendor Model are still maintained in our work, such as the constant per-unit cost of leftover and shortage, the zero initial inventory, as well as the continuous time. Our problem is challenging in the way that the best order quantity in the classical model, which is balancing the over-stocking and under-stocking costs, is no longer optimal. Specifically, when adding the cost-saving from worker learning to such expected total cost, the convexity of the cost function will likely not be maintained. This has called for a new way in determining the optimal order policy. In response to such challenges, we found a number of characteristics related to the expected cost function and its derivatives, which we then used in formulating the optimal ordering policy. Examples of such characteristics are; the optimal order quantity exists and is unique if the demand follows a Uniform Distribution; if the demand follows the Beta Distribution with some specific properties of its parameters, the second derivative of the expected cost function has at most two roots; and there exists the specific level of lot size that satisfies the first order condition. Our research results could be helpful for analysis of supply chain coordination and of the periodic review system for similar problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=inventory%20management" title="inventory management">inventory management</a>, <a href="https://publications.waset.org/abstracts/search?q=Newsvendor%20model" title=" Newsvendor model"> Newsvendor model</a>, <a href="https://publications.waset.org/abstracts/search?q=order%20policy" title=" order policy"> order policy</a>, <a href="https://publications.waset.org/abstracts/search?q=worker%20learning" title=" worker learning"> worker learning</a> </p> <a href="https://publications.waset.org/abstracts/24622/the-optimal-order-policy-for-the-newsvendor-model-under-worker-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/24622.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span 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