Differential evolution algorithms with local search for the multi-products capacitated vehicle routing problem with time windows: A case study of the ice industry
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Creator 1. Rattanapong Kamphukaew
2. Kanchana Sethanan
3. Thitipong Jamrus
4. Hung-kai Wang
Title Differential evolution algorithms with local search for the multi-products capacitated vehicle routing problem with time windows: A case study of the ice industry
Publisher Faculty of Engineering, Khon Kaen University
Publication Year 2561
Journal Title Engineering and Applied Science Research
Journal Vol. 45
Journal No. 4
Page no. 273-281
Keyword Ice transportation, Capacitated vehicle routing problem, Time windows, Differential evolution algorithm, Local search
URL Website https://www.tci-thaijo.org/index.php/easr/index
Website title Engineering and Applied Science Research
ISSN 2539-6161
Abstract This research aims to offer a solution to the capacitated vehicle routing problem for multiple products, time windows and a heterogeneous fleet for ice transport. The problem structure is that the capacitated vehicle routing problem is one-to-many with multiple products, where each customer has a variety of product types and demands. Also, limited delivery time is considered for each customer. We used a mixed integer linear programming model to give an optimal solution, and propose a differential evolution method with a local search that we have developed. The objective is to sequence the delivery procedures for ice transport to minimize total costs, comprised of traveling costs, driver wages and a penalty costs. We obtained various solutions by a comparison of our proposed solution and the optimal solution of the ice transport case study and differential evolution with local search (DELS) to validate the proposed metaheuristic. The relative improvement between the current practice of the ice transport in the case study and the differential evolution with a local search was 3.70-25.75%. The differential evolution with a local search outperformed current practices by an average by 2.29%.
Engineering and Applied Science Research

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