A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service

This paper addresses the two-echelon capacitated vehicle routing problem (2E-CVRP) with stochastic demands (2E-CVRPSD) in city logistics. A stochastic program with recourse is used to describe the problem. This program aims to minimize the sum of the travel cost and the expected cost of recourse act...

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Bibliographic Details
Published in:The Journal of the Operational Research Society Vol. 68; no. 11; pp. 1409 - 1421
Main Authors: Wang, Kangzhou, Lan, Shulin, Zhao, Yingxue
Format: Journal Article
Language:English
Published: London Taylor & Francis 01.11.2017
Taylor & Francis, Ltd
Palgrave Macmillan UK
Taylor & Francis Ltd
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ISSN:0160-5682, 1476-9360
Online Access:Get full text
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Summary:This paper addresses the two-echelon capacitated vehicle routing problem (2E-CVRP) with stochastic demands (2E-CVRPSD) in city logistics. A stochastic program with recourse is used to describe the problem. This program aims to minimize the sum of the travel cost and the expected cost of recourse actions resulting from potential route failures. In a two-echelon distribution system, split deliveries are allowed at the first level but not at the second level, thereby increasing the difficulty of calculating the expected failure cost. Three types of routes with or without split deliveries are identified. Different methods are devised or adapted from the literature to compute the failure cost. A genetic-algorithm-based (GA) approach is proposed to solve the 2E-CVRPSD. A simple encoding and decoding scheme, a modified route copy crossover operator, and a satellite-selection-based mutation operator are devised in this approach. The numerical results show that for all instances, the expected cost of the best 2E-CVRPSD solution found by the proposed approach is not greater than that of the best-known 2E-CVRP solution with an average relative gap of 2.57%. Therefore, the GA-based approach can find high-quality solutions for the 2E-CVRPSD.
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ISSN:0160-5682
1476-9360
DOI:10.1057/s41274-016-0170-7