Vehicle Routing with Time Windows and Customer Selection for Perishable Goods

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In this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several products to be delivered to customers with respect to their demands and with consideration of different soft time windows for each customer, heterogeneous distribution fleet and customer selection option for the distributer. The proposed model is solved with TH method. The two genetic algorithm and simulated annealing algorithm are used to solve large-sized problems. 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In this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several products to be delivered to customers with respect to their demands and with consideration of different soft time windows for each customer, heterogeneous distribution fleet and customer selection option for the distributer. The proposed model is solved with TH method. The two genetic algorithm and simulated annealing algorithm are used to solve large-sized problems. Finally, their results are compared to each other when the optimization software becomes unable of solution representation." /> <meta name="citation_id" content="2570" /> <meta name="citation_publication_date" content="2015/08/01" /> <meta name="citation_date" content="2015-08-01" /> <meta name="citation_journal_title" content="International Journal of Supply and Operations Management" /> <meta name="citation_issn" content="23831359" /> <meta name="citation_volume" content="2" /> <meta name="citation_issue" content="2" /> <meta name="citation_firstpage" content="700" /> <meta name="citation_lastpage" content="719" /> <meta name="citation_publisher" content="Kharazmi University" /> <meta name="citation_doi" content="10.22034/2015.2.02" /> <meta name="DC.Identifier" content="10.22034/2015.2.02" /> <meta name="citation_abstract_html_url" content="http://www.ijsom.com/article_2570.html" /> <meta name="citation_pdf_url" content="http://www.ijsom.com/article_2570_a9c5b522f6da35dc41be1f07210905e4.pdf" /> <meta name="DC.Title" content="Vehicle Routing with Time Windows and Customer Selection for Perishable Goods" /> <meta name="DC.Source" content="International Journal of Supply and Operations Management" /> <meta name="DC.Date" content="01/08/2015" /> <meta name="DC.Date.issued" content="2015-08-01" /> <meta name="DC.Format" content="application/pdf" /> <meta name="DC.Contributor" content="Rabbani, Masoud" /> <meta name="DC.Contributor" content="Ramezankhani, Mohammad-Javad" /> <meta name="DC.Contributor" content="Farrokhi-Asl, Hamed" /> <meta name="DC.Contributor" content="Farshbaf-Geranmayeh, Amir" /> <meta name="og:title" content="Vehicle Routing with Time Windows and Customer Selection for Perishable Goods" /> <meta name="og:description" content="Delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years due to the global market becoming more competitive. In this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several products to be delivered to customers with respect to their demands and with consideration of different soft time windows for each customer, heterogeneous distribution fleet and customer selection option for the distributer. The proposed model is solved with TH method. The two genetic algorithm and simulated annealing algorithm are used to solve large-sized problems. 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href="./?_action=article&au=110492&_au=Masoud++Rabbani">Masoud Rabbani</a> <sup><a href="mailto:mrabani@ut.ac.ir" data-toggle="tooltip" data-placement="bottom" title="Email to Corresponding Author"><i class="fa fa-envelope-o" ></i></a></sup> <sup><a href="#aff1" >1</a></sup> </li> <li class="padding-3"> <a href="./?_action=article&au=111852&_au=Mohammad-Javad++Ramezankhani">Mohammad-Javad Ramezankhani</a> <sup><a href="#aff2" >2</a></sup> </li> <li class="padding-3"> <a href="./?_action=article&au=111743&_au=Hamed++Farrokhi-Asl">Hamed Farrokhi-Asl</a> <sup><a href="#aff2" >2</a></sup> </li> <li class="padding-3"> <a href="./?_action=article&au=111853&_au=Amir++Farshbaf-Geranmayeh">Amir Farshbaf-Geranmayeh</a> <sup><a href="#aff2" >2</a></sup> </li> </ul> <p class="margin-bottom-3 ltr" id="aff1"> <sup>1</sup> Tehran University, Tehran, Iran </p> <p class="margin-bottom-3 ltr" id="aff2"> <sup>2</sup> College of Engineering, University of Tehran, Tehran, Iran </p> <div class="margin-bottom-3 ltr" id="ar_doi" title="DOI"><i class="ai ai-doi size-25 text-orange"></i> <span dir="ltr"><a href="https://dx.doi.org/10.22034/2015.2.02">10.22034/2015.2.02</a></span></div> <p style="margin:12px -2px 0 -2px"><strong>Abstract</strong></p> <div class="padding_abstract justify ltr">Delivering perishable products to customers as soon as possible and with the minimum cost has been always a challenge for producers and has been emphasized over recent years due to the global market becoming more competitive. In this paper a multi-objective mix integer non-linear programming model is proposed to maximize both profits of a distributer and the total freshness of the several products to be delivered to customers with respect to their demands and with consideration of different soft time windows for each customer, heterogeneous distribution fleet and customer selection option for the distributer. The proposed model is solved with TH method. The two genetic algorithm and simulated annealing algorithm are used to solve large-sized problems. Finally, their results are compared to each other when the optimization software becomes unable of solution representation.</div> <p class="padding-0" style="margin:12px -2px 0 -2px"><strong>Keywords</strong></p> <ul class="block list-inline list-inline-seprator margin-bottom-6 ltr"> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=105012&_kw=Vehicle+Routing+Problem+with+Time+Windows+%28VRPTW%29" >Vehicle Routing Problem with Time Windows (VRPTW)</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=105013&_kw=Perishable+Goods" >Perishable Goods</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=105014&_kw=Multi-objective+Programming" >Multi-objective Programming</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=102135&_kw=Genetic+Algorithm" >Genetic Algorithm</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=102134&_kw=Simulated+Annealing" >Simulated Annealing</a> </li> </ul> <p class="padding-0" style="margin:12px -2px 0 -2px"><strong>Main Subjects</strong></p> <ul class="block list-inline list-inline-seprator margin-bottom-6"> <li class="padding-3"> <a href="./?_action=article&sb=153&_sb=logistics%2C+transportation%2C+distribution%2C+and+materials+Handling" >logistics, transportation, distribution, and materials Handling</a> </li> </ul> </div> <hr> <div class="page_break"></div> <div class="panel"> <div class="panel-heading card-header"> <h4 class="panel-title "> <a data-toggle="collapse" data-parent="#accordions" href="#collapsesRef"><i class="fa fa-plus"></i> References</a> </h4> </div> <div id="collapsesRef" class="panel-collapse collapse"> <div class="panel-body justify"> <div class="padding-3 margin-top-3 ltr justify">Amorim, P., & Almada-Lobo, B. (2014). The impact of food perishability issues in the vehicle routing problem. Computers & Industrial Engineering, Vol. 67, pp. 223-233. </div> <div class="padding-3 margin-top-3 ltr justify">Amorim, P., Parragh, S. N., Sperandio, F., & Almada-Lobo, B. (2012). A rich vehicle routing problem dealing with perishable food: a case study. Top, pp. 1-20. </div> <div class="padding-3 margin-top-3 ltr justify">Chen, H.-K., Hsueh, C.-F., & Chang, M.-S. (2009). Production scheduling and vehicle routing with time windows for perishable food products. Computers & Operations Research, Vol. 36(7), pp. 2311-2319. </div> <div class="padding-3 margin-top-3 ltr justify">Cordeau, J.-F., Desaulniers, G., Desrosiers, J., Solomon, M. M., & Soumis, F. (2001). VRP with time windows. The vehicle routing problem, Vol. 9, pp. 157-193. </div> <div class="padding-3 margin-top-3 ltr justify">Doerner, K. F., Gronalt, M., Hartl, R. F., Kiechle, G., & Reimann, M. (2008). Exact and heuristic algorithms for the vehicle routing problem with multiple interdependent time windows. Computers & Operations Research, Vol. 35(9), pp. 3034-3048. </div> <div class="padding-3 margin-top-3 ltr justify">Eglese, R. (1990). Simulated annealing: a tool for operational research. European Journal of Operational Research, Vol. 46(3), pp. 271-281. </div> <div class="padding-3 margin-top-3 ltr justify">Glover, F., & Kochenberger, G. A. (2003). Handbook of metaheuristics: Springer. </div> <div class="padding-3 margin-top-3 ltr justify">Golden, B. L., Raghavan, S., & Wasil, E. A. (2008). The Vehicle Routing Problem: Latest Advances and New Challenges: latest advances and new challenges (Vol. 43): Springer. </div> <div class="padding-3 margin-top-3 ltr justify">Hsu, C.-I., Hung, S.-F., & Li, H.-C. (2007). Vehicle routing problem with time-windows for perishable food delivery. Journal of Food Engineering, Vol. 80(2), pp. 465-475. </div> <div class="padding-3 margin-top-3 ltr justify">Naso, D., Surico, M., Turchiano, B., & Kaymak, U. (2007). Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete. European Journal of Operational Research, Vol. 177(3), pp. 2069-2099. </div> <div class="padding-3 margin-top-3 ltr justify">Osvald, A., & Stirn, L. Z. (2008). A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food. Journal of Food Engineering, Vol. 85(2), pp. 285-295. </div> <div class="padding-3 margin-top-3 ltr justify">Rahimi, M., Baboli, A., & Rekik, Y. (2014). A bi-objective inventory routing problem by considering customer satisfaction level in context of perishable product. Paper presented at the Computational Intelligence in Production and Logistics Systems (CIPLS), 2014 IEEE Symposium on. </div> <div class="padding-3 margin-top-3 ltr justify">Tarantilis, C., & Kiranoudis, C. (2002). Distribution of fresh meat. Journal of Food Engineering, Vol. 51(1), pp. 85-91. </div> <div class="padding-3 margin-top-3 ltr justify">Torabi , S., & Hassini, E. (2009). Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: an interactive fuzzy goal programming approach. International Journal of Production Research, Vol. 47(19), pp. 5475-5499. </div> <div class="padding-3 margin-top-3 ltr justify">Torabi, S. A., & Hassini, E. (2008). An interactive possibilistic programming approach for multiple objective supply chain master planning. Fuzzy Sets and Systems, Vol. 159(2), pp. 193-214. </div> <div class="padding-3 margin-top-3 ltr justify">Toth, P., & Vigo, D. (2001). 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(2015). Vehicle Routing with Time Windows and Customer Selection for Perishable Goods. <em>International Journal of Supply and Operations Management</em>, 2(2), 700-719. doi: 10.22034/2015.2.02</p> </div> </div> </div> </div> <div id="cite-mla" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content">  <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">MLA</h4> </div>  <div class="modal-body"> <p>Masoud Rabbani; Mohammad-Javad Ramezankhani; Hamed Farrokhi-Asl; Amir Farshbaf-Geranmayeh. "Vehicle Routing with Time Windows and Customer Selection for Perishable Goods". <em>International Journal of Supply and Operations Management</em>, 2, 2, 2015, 700-719. doi: 10.22034/2015.2.02</p> </div> </div> </div> </div> <div id="cite-harvard" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content">  <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">HARVARD</h4> </div>  <div class="modal-body"> <p>Rabbani, M., Ramezankhani, M., Farrokhi-Asl, H., Farshbaf-Geranmayeh, A. (2015). 'Vehicle Routing with Time Windows and Customer Selection for Perishable Goods', <em>International Journal of Supply and Operations Management</em>, 2(2), pp. 700-719. doi: 10.22034/2015.2.02</p> </div> </div> </div> </div> <div id="cite-vancouver" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content">  <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">VANCOUVER</h4> </div>  <div class="modal-body"> <p>Rabbani, M., Ramezankhani, M., Farrokhi-Asl, H., Farshbaf-Geranmayeh, A. 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Vehicle Routing with Time Windows and Customer Selection for Perishable Goods