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<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd"> <ArticleSet> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>7</Volume> <Issue>4</Issue> <PubDate PubStatus="epublish"> <Year>2020</Year> <Month>11</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>A Mathematical Approach to Ordering Policy Selection for Cold Items in a Warehouse with Different Operational Constraints</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>299</FirstPage> <LastPage>309</LastPage> <ELocationID EIdType="pii">2823</ELocationID> <ELocationID EIdType="doi">10.22034/IJSOM.2020.4.1</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Milad</FirstName> <LastName>Zamani</LastName> <Affiliation>Department of Indusrtial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran</Affiliation> </Author> <Author> <FirstName>Seyed Hamid Reza</FirstName> <LastName>Pasandideh</LastName> <Affiliation>Department of Indusrtial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran</Affiliation> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2019</Year> <Month>12</Month> <Day>22</Day> </PubDate> </History> <Abstract>According to the importance of keeping temperature-dependent products, the present study investigated the inventory control of cold products. In this study, a warehouse with limited space and ambient temperature is assumed. Based on the assumptions of the problem, the best ordering system for cold products should be selected from the two fixed order size and periodic review systems by formulating a mixed integer nonlinear programming model. The objective of the model is to minimize the sum of costs, including adjusting the temperature of the products and the cost of producing fluoride gas produced by keeping them in the refrigerator and for both types of ordering systems, taking into account different constraints consisting of warehouse space, available budget, the storage temperature of the products in the warehouse and the maximum number of cold products that can follow any ordering system. Finally, by solving the model, the type of ordering system for each product, the ordering system characteristics and their storage temperature are obtained. After solving the model, sensitivity analysis is performed on different parameters including available space for holding the products at the warehouse, available budget, the minimum number of the products that can follow a specific ordering system and shortage cost and the results are discussed.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">Inventory control of cold products</Param> </Object> <Object Type="keyword"> <Param Name="value">Periodic review system</Param> </Object> <Object Type="keyword"> <Param Name="value">Fixed order size system</Param> </Object> <Object Type="keyword"> <Param Name="value">Sensitivity Analysis</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2823_ac04e8de136c283e49cde7da8aa9eff2.pdf</ArchiveCopySource> </Article> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>7</Volume> <Issue>4</Issue> <PubDate PubStatus="epublish"> <Year>2020</Year> <Month>11</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>Analysing Impatience in Multiserver Markovian Queues</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>310</FirstPage> <LastPage>321</LastPage> <ELocationID EIdType="pii">2824</ELocationID> <ELocationID EIdType="doi">10.22034/IJSOM.2020.4.2</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Girin</FirstName> <LastName>Saikia</LastName> <Affiliation>Department of Statistics, Gauhati University, Guwahati, Assam, India.</Affiliation> </Author> <Author> <FirstName>Amit</FirstName> <LastName>Choudhury</LastName> <Affiliation>Department of Statistics, Gauhati University, Guwahati, Assam, India.</Affiliation> </Author> <Author> <FirstName>Pallabi</FirstName> <LastName>Medhi</LastName> <Affiliation>Department of Statistics, Gauhati University, Guwahati, Assam, India.</Affiliation> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2020</Year> <Month>05</Month> <Day>08</Day> </PubDate> </History> <Abstract>Reneging and Balking are practical aspects of customer impatience. In traditional queuing literature, customer impatience was rarely considered. However, for the last few decades, queuing theorists have been trying to integrate aspect of balking and reneging into modeling of queues. This paper is an extension of the work in the same direction. We consider a multi-server Markovian queuing model under the assumption that customers are state aware and the reneging rates increase as the state of the system goes up. We also assume that the customer may balk with balking probabilities proportional to the state of the system. Under this setup performance measures are derived and presented.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">Balking</Param> </Object> <Object Type="keyword"> <Param Name="value">Impatience</Param> </Object> <Object Type="keyword"> <Param Name="value">Qqueuing</Param> </Object> <Object Type="keyword"> <Param Name="value">Reneging</Param> </Object> <Object Type="keyword"> <Param Name="value">Performance measures</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2824_678ed763b6bc2f974237d9164e8c8f25.pdf</ArchiveCopySource> </Article> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>7</Volume> <Issue>4</Issue> <PubDate PubStatus="epublish"> <Year>2020</Year> <Month>11</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>Explaining the Competencies of Project Managers According To PMCDF Model</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>322</FirstPage> <LastPage>343</LastPage> <ELocationID EIdType="pii">2825</ELocationID> <ELocationID EIdType="doi">10.22034/IJSOM.2020.4.3</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Fereshteh</FirstName> <LastName>Mansourimoayyed</LastName> <Affiliation>Department of Business Management, Faculty of Management & Economics, Tarbiat Modares University, Tehran, Iran</Affiliation> <Identifier Source="ORCID">0000-0001-9810-7815</Identifier> </Author> <Author> <FirstName>Amirmohammad</FirstName> <LastName>Colabi</LastName> <Affiliation>Department of Business Management, Faculty of Management & Economics, Tarbiat Modares University, Tehran, Iran</Affiliation> </Author> <Author> <FirstName>Majid</FirstName> <LastName>Semiari</LastName> <Affiliation>Department of Executive Management, Tehran Branch, Islamic Azad University of Research and Science, Tehran, Iran</Affiliation> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2020</Year> <Month>01</Month> <Day>10</Day> </PubDate> </History> <Abstract>Today, editing a pattern to evaluate the project management competency based on professional values and principles in order to select, evaluate, and elevate the project manpower will be very effective in the professional excellence and growth in the specialized field regarding project-oriented organizations. For a project manager to perform successfully in a particular area of management, he or she must have the qualifications required in that area. In this regard, this study has tried to explain the model and assess the competencies of the project managers of Mapna Locomotive Engineering and Manufacturing Company based on Project Manager Competency Development Framework (PMCDF) with the aim of developing their competencies. This study conducted in four phases. First, designing and explaining the model of competencies of project managers; second, evaluating the competencies of 17 projects managers of the company based on the model explained; third, identifying the existing gaps; and fourth, presenting improvement programs, training and developing strategies. The results of the study indicate that the statistical population of the research is lower than the ideal level in all areas of competency including knowledge, skill, behavior, organization, and industry and at various project levels 1, 2 and 3 except the industrial competency.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">Project managers competency development framework (PMCDF)</Param> </Object> <Object Type="keyword"> <Param Name="value">Project management body of knowledge (PMBOK)</Param> </Object> <Object Type="keyword"> <Param Name="value">Project managers competency</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2825_5fef8054da32d51efaa02ad04b9e4395.pdf</ArchiveCopySource> </Article> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>7</Volume> <Issue>4</Issue> <PubDate PubStatus="epublish"> <Year>2020</Year> <Month>11</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>A New Hestenes-Stiefel and Fletcher-Reeves Conjugate Gradient Method with Descent Properties for Optimization Models</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>344</FirstPage> <LastPage>349</LastPage> <ELocationID EIdType="pii">2826</ELocationID> <ELocationID EIdType="doi">10.22034/IJSOM.2020.4.4</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Saleh Nazzal</FirstName> <LastName>Alsuliman</LastName> <Affiliation>Faculty of Informatics and Computing, Sultan Zainal Abidin University, Kuala Terengganu, Malaysia</Affiliation> </Author> <Author> <FirstName>Sulaiman</FirstName> <LastName>Ibrahim Mohammed</LastName> <Affiliation>Faculty of Informatics and Computing, Sultan Zainal Abidin University, Kuala Terengganu, Malaysia</Affiliation> </Author> <Author> <FirstName>Mustafa</FirstName> <LastName>Mamat</LastName> <Affiliation>Faculty of Informatics and Computing, Sultan Zainal Abidin University, Kuala Terengganu, Malaysia</Affiliation> </Author> <Author> <FirstName>Deiby</FirstName> <LastName>Salaki</LastName> <Affiliation>Department of Mathematics, Faculty of Mathematics and Natural Science, Sam Ratulangi University, Indonesia</Affiliation> </Author> <Author> <FirstName>Nelson</FirstName> <LastName>Nainggolan</LastName> <Affiliation>bDepartment of Mathematics, Faculty of Mathematics and Natural Science, Sam Ratulangi University, Indonesia</Affiliation> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2020</Year> <Month>02</Month> <Day>12</Day> </PubDate> </History> <Abstract>The conjugate gradient (CG) scheme is regarded as among the efficient methods for large-scale optimization problems. Several versions of CG methods have been presented recently owing to their rapid convergence, simplicity, and their less memory requirements. In this article, we construct a new CG algorithm via the combination of the classical methods of Fletcher-Reeves (FR), and Hestenes-Stiefel (HS). The new CG method possesses the descent properties and converge globally provided the exact minimization condition is satisfied. The tests of the new CG method using MATLAB are analysed in terms of iteration number and CPU time. Numerical results have been reported which shows that the proposed CG method performs better compare to other CG methods.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">CG parameter</Param> </Object> <Object Type="keyword"> <Param Name="value">Line search procedure</Param> </Object> <Object Type="keyword"> <Param Name="value">Unconstrained optimization</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2826_aa6eddec6d20b14519a00c8da271c91e.pdf</ArchiveCopySource> </Article> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>7</Volume> <Issue>4</Issue> <PubDate PubStatus="epublish"> <Year>2020</Year> <Month>11</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>Designing a Food Supply Chain Network under Uncertainty and Solving by Multi-objective Metaheuristics</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>350</FirstPage> <LastPage>372</LastPage> <ELocationID EIdType="pii">2827</ELocationID> <ELocationID EIdType="doi">10.22034/IJSOM.2020.4.5</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Hossein Ali</FirstName> <LastName>Hassanpour</LastName> <Affiliation>Industrial Engineering Department, Faculty of Engineering,Imam Hossein Comprehensive University, Tehran, Iran</Affiliation> </Author> <Author> <FirstName>Mohammad Reza</FirstName> <LastName>Taheri</LastName> <Affiliation>Department of Industrial Engineering, Imam Hossein Comprehensive University, Tehran, Iran</Affiliation> </Author> <Author> <FirstName>Reza</FirstName> <LastName>Rezanezhad</LastName> <Affiliation>Department of Industrial Engineering, Imam Hossein Comprehensive University, Tehran, Iran</Affiliation> <Identifier Source="ORCID">0000-0002-1386-8277</Identifier> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2020</Year> <Month>02</Month> <Day>26</Day> </PubDate> </History> <Abstract>Short life cycle products, especially food products, require a certain type of supply chain management due to their particular specifications such as perishability. On the other hand, the food distribution also requires special considerations and imparts more complexity compared with the distribution of other goods because in food distribution the quality of the food delivered to the customer should be considered as well as transportation costs. Therefore, in this paper, a new mathematical model is developed for integrating decisions regarding food supply and distribution under conditions of uncertainty (vehicles’ travel time) with aims to minimize purchase and transportation costs and maximize customer satisfaction. Customer satisfaction relies upon the quality of the food delivered to the customers. The multi-objective model proposed in this paper is NP-hard. Hence, a developed version of NSGA-II called Multi-Objective Time Travel to History (MOTTH) algorithm, inspired from the idea of traveling through history, is proposed to solve the problem. In order to validate the performance of the proposed algorithm, the results of MOTTH algorithm are compared with the results obtained from an exact augmented epsilon-constraint method. Furthermore, a comparison is provided between the NSGA-II and MOTTH algorithms, the results of which indicate the superiority of the MOTTH metaheuristic algorithm.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">Foodstuffs</Param> </Object> <Object Type="keyword"> <Param Name="value">Perishable Goods</Param> </Object> <Object Type="keyword"> <Param Name="value">Supply chain</Param> </Object> <Object Type="keyword"> <Param Name="value">metaheuristic</Param> </Object> <Object Type="keyword"> <Param Name="value">Augmented epsilon-constraint</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2827_55f5d3a11ab3ea61620fdfa083031a59.pdf</ArchiveCopySource> </Article> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>7</Volume> <Issue>4</Issue> <PubDate PubStatus="epublish"> <Year>2020</Year> <Month>11</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>Fuzzy TOPSIS and Grey Relation Analysis Integration for Supplier Selection in Fiber Industry</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>373</FirstPage> <LastPage>383</LastPage> <ELocationID EIdType="pii">2828</ELocationID> <ELocationID EIdType="doi">10.22034/IJSOM.2020.4.6</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Amol Nayakappa</FirstName> <LastName>Patil</LastName> <Affiliation>Department of Mechanical Engineering, Agnel Institute of Technology and Design, Assagao, Bardez-Goa, India</Affiliation> </Author> <Author> <FirstName>Shivakumar</FirstName> <LastName>K M</LastName> <Affiliation>Department of Mechanical Engineering, Sahyadri College of Egineering and Management, Manglore, Affiliated to Visvesvarya Technological University, Belagavi, India</Affiliation> </Author> <Author> <FirstName>Manjunath</FirstName> <LastName>Patel G C</LastName> <Affiliation>Department of Mechanical Engineering, PES Institute of Technology and Management, Shivamogga, Affiliated to Visvesvarya Technological University, Belagavi, India</Affiliation> <Identifier Source="ORCID">orcid.org/0000-0001-9340-7464</Identifier> </Author> <Author> <FirstName>Somashekar</FirstName> <LastName>P Jatti</LastName> <Affiliation>Department of Mechanical Engineering, BVVS Polytechnic, Bagalkot, Kar nataka, India</Affiliation> </Author> <Author> <FirstName>Saish N.</FirstName> <LastName>Rivankar</LastName> <Affiliation>Department of Mechanical Engineering, Agnel Institute of Technology and Design, Assagao, Bardez-Goa, India</Affiliation> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2020</Year> <Month>09</Month> <Day>02</Day> </PubDate> </History> <Abstract>In the present work, selection of right corrugated box supplier for fibre industry is studied. Decision makers independently evaluate the supplier’s strength for both qualitative (quality, reliability, flexibility, stability, capability, and availability) and quantitative (order volume, price, delivery, credit period and location) criteria’s with conflict in nature. Inappropriate choice of supplier by traditional approach could result in financial losses. Hybrid approach (Fuzzy TOPSIS and Grey relational analysis GRA) is proposed to select the right corrugated box supplier from the pool of suppliers for Fiber industry located in Goa, India. Fuzzy TOPSIS method is applied to evaluate the qualitative criteria, whereas, GRA for quantitative criteria’s for selecting the best supplier. Considering the ranks obtained from both the qualitative and quantitative criteria’s evaluated by Fuzzy TOPSIS and GRA, the best supplier is selected. In addition, sensitivity analysis is performed to know the changes in rank of suppliers with variation in preferential weights assigned to qualitative and quantitative criterion.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">Supplier Selection</Param> </Object> <Object Type="keyword"> <Param Name="value">Multi criteria decision making</Param> </Object> <Object Type="keyword"> <Param Name="value">Fuzzy TOPSIS</Param> </Object> <Object Type="keyword"> <Param Name="value">Grey Relation Analysis</Param> </Object> <Object Type="keyword"> <Param Name="value">Sensitivity Analysis</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2828_39474c27a626dfd0e23e9fcaf72ec161.pdf</ArchiveCopySource> </Article> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>7</Volume> <Issue>4</Issue> <PubDate PubStatus="epublish"> <Year>2020</Year> <Month>11</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>A Single-Manufacturer Multi-Retailer Integrated Inventory Model with Price Dependent Demand and Stochastic Lead Time</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>384</FirstPage> <LastPage>409</LastPage> <ELocationID EIdType="pii">2829</ELocationID> <ELocationID EIdType="doi">10.22034/IJSOM.2020.4.7</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Bibhas C.</FirstName> <LastName>Giri</LastName> <Affiliation>Department of Mathematics Jadavpur University Kolkata, India</Affiliation> </Author> <Author> <FirstName>Anamika</FirstName> <LastName>Dash</LastName> <Affiliation>Department of Mathematics Jadavpur University Kolkata, India</Affiliation> </Author> <Author> <FirstName>Ashis</FirstName> <LastName>Sarkar</LastName> <Affiliation>Department of Mathematics Jadavpur University Kolkata, India</Affiliation> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2020</Year> <Month>03</Month> <Day>04</Day> </PubDate> </History> <Abstract>This paper deals with a two-level supply chain composed of a single manufacturer and multiple retailers. Ordered quantities of the retailers are dispatched in some equal batches from the manufacturer. Customer demand linearly depends on the selling price of the item. Lead time is random and it follows a normal distribution. The proposed model is developed for both the centralized and the decentralized scenarios. In the decentralized scenario, a Stackelberg gaming approach is used to derive the optimal decisions. The developed models are illustrated by a numerical example. It is found that integration of the supply chain players gives an impressive increment in the profit of the whole supply chain. Sensitivity analysis is also performed to explore the impacts of key-model parameters on the expected average profit of the supply chain.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">Two-level supply chain</Param> </Object> <Object Type="keyword"> <Param Name="value">single manufacturer</Param> </Object> <Object Type="keyword"> <Param Name="value">multiple retailers</Param> </Object> <Object Type="keyword"> <Param Name="value">Price Dependent Demand</Param> </Object> <Object Type="keyword"> <Param Name="value">stochastic lead time</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2829_f570601e45579e6101aa0c15a1dc685a.pdf</ArchiveCopySource> </Article> </ArticleSet>