{"id":6137,"date":"2026-05-10T06:18:10","date_gmt":"2026-05-09T22:18:10","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=6137"},"modified":"2026-07-02T02:07:28","modified_gmt":"2026-07-01T18:07:28","slug":"vrp-model-with-time-window-multiproduct-and-multidepot","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=vrp-model-with-time-window-multiproduct-and-multidepot","title":{"rendered":"VRP Model with time window, multiproduct and multidepot"},"content":{"rendered":"\n
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<\/i> 2020<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 23, Issue 2<\/a><\/p>\n<\/div>\n\n\n\n

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Jos\u00e9 Ruiz-Meza1,2<\/sup><\/i><\/a>, Isaid Montes1<\/sup>, Arnoldo P\u00e9rez1<\/sup>, and Mar\u00eda Ramos-M\u00e1rquez3<\/sup><\/p>\n\n\n\n

1<\/sup>Industrial Engineering Program, Corporaci\u00f3n Universitaria del Caribe, Sincelejo, Colombia <\/p>\n\n\n\n

2<\/sup>Faculty of Engineering, Universidad de La Sabana, Ch\u00eda, Colombia <\/p>\n\n\n\n

3<\/sup>Faculty of Engineering, Universidad Tecnol\u00f3gica de Bol\u00edvar, Cartagena, Colombia<\/p>\n<\/div>\n\n\n\n

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Received:\u00a0July 30, 2019
Accepted:\u00a0February 15, 2020
Publication Date:\u00a0May 10, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

Graphic representation of multiproduct and multidepot VRP<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:  BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202006_23(2).0008<\/a>  <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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With the increase in the transfer of products in supply chains, the organization of routes requires a complex allocation insofar as different environmental variables are considered, and VRP models are an efficient tool for the solution of routing systems of low, medium and high complexity. In this paper, we developed a vehicle routing model with hard time window, multidepot, multiproduct and heterogeneous fleet for the minimization of the distance travelled. We applied the model to a case study of a company that distributes water bottles and bales in which we made a new distribution of delivery schedules by order applied Pareto analysis. We obtained optimal computational results using exact methods in a very short computational time and minimizing the distance to 35.08 % of the current route.<\/p>\n\n\n\n

Keywords:\u00a0Pareto analysis; mathematical model; vehicle routing; optimization<\/em><\/p>\n\n\n\n

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