Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm

Bo Peng, Lifan Wu, Yuxin Yi and Xiding Chen
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Bo Peng: School of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, China
Lifan Wu: School of Business Administration, Southwestern University of Finance and Economics, Chengdu 610074, China
Yuxin Yi: College of Management, Sichuan Agricultural University, Chengdu 610074, China
Xiding Chen: Department of Finance, Wenzhou Business College, Wenzhou 325035, China

Sustainability, 2020, vol. 12, issue 5, 1-19

Abstract: The growing concerns about human pollution has motivated practitioners and researchers to focus on the environmental and social impacts of logistics and supply chains. In this paper, we consider the environmental impact of carbon dioxide emission on a vehicle routing problem with multiple depots. We present a hybrid evolutionary algorithm (HEA) to tackle it by combining a variable neighborhood search and an evolutionary algorithm. The proposed hybrid evolutionary algorithm includes several distinct features such as multiple neighborhood operators, a route-based crossover operator, and a distance- and quality-based population updating strategy. The results from our numerical experiments confirm the effectiveness and superiority of the proposed HEA in comparison with the best-performing methods in the literature and the public exact optimization solver CPLEX. Furthermore, an important aspect of the HEA is studied to assess its effect on the performance of the HEA.

Keywords: variable neighborhood search; hybrid evolutionary algorithm; depot-based crossover operator; distance- and quality-based population updating strategy; multi-depot green vehicle routing problem (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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