Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/36308
Title: Design and development of a hybrid artificial BEE colony algorithm for the environmental vehicle routing problem
Authors: Zhang, SZ
Lee, CKM 
Choy, KL 
Ho, W
Ip, WH 
Keywords: Green logistics
Capacitated vehicle routing problem
Artificial bee colony algorithm
Environmental influence
Environmental vehicle routing problem
CO2 emission
Issue Date: 2014
Publisher: Pergamon Press
Source: Transportation research. Part D, Transport and environment, 2014, v. 31, p. 85-99 How to cite?
Journal: Transportation research. Part D, Transport and environment 
Abstract: The vehicle routing problem (VRP) is a critical and vital problem in logistics for the design of an effective and efficient transportation network, within which the capacitated vehicle routing problem (CVRP) has been widely studied for several decades due to the practical relevance of logistics operation. However, CVRP with the objectives of minimizing the overall traveling distance or the traveling time cannot meet the latest requirements of green logistics, which concern more about the influence on the environment. This paper studies CVRP from an environmental perspective and introduces a new model called environmental vehicle routing problem (EVRP) with the aim of reducing the adverse effect on the environment caused by the routing of vehicles. In this research, the environmental influence is measured through the amount of the emission carbon dioxide, which is a widely acknowledged criteria and accounts for the major influence on environment. A hybrid artificial bee colony algorithm (ABC) is designed to solve the EVRP model, and the performance of the hybrid algorithm is evaluated through comparing with well-known CVRP instances. The computational results from numerical experiments suggest that the hybrid ABC algorithm outperforms the original ABC algorithm by 5% on average. The transformation from CVRP to EVRP can be recognized through the differentiation of their corresponding optimal solutions, which provides practical insights for operation management in green logistics.
URI: http://hdl.handle.net/10397/36308
ISSN: 1361-9209
DOI: 10.1016/j.trd.2014.05.015
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