文献类型：期刊文献

英文题名：Peer-induced fairness capacitated vehicle routing scheduling using a hybrid optimization ACO-VNS algorithm

作者：Wu, Yifan[1];Pan, Fan[2];Li, Shuxia[1];Chen, Zhen[1];Dong, Ming[3]

机构：[1]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Sino US Global Logist Inst, Shanghai 200030, Peoples R China;[3]Shanghai Jiao Tong Univ, Antai Coll Econ & Management, Shanghai 200052, Peoples R China

年份：2020

卷号：24

期号：3

起止页码：2201

外文期刊名：SOFT COMPUTING

收录：;EI(收录号：20192106951572);WOS:【SSCI(收录号:WOS:000518595800039)，SCI-EXPANDED(收录号:WOS:000518595800039)】；

基金：This study was funded in part by the National Natural Science Foundation of China (Grant Numbers 71471062, 71431004 and 71632008), the National Social Science Foundation of China (Grant Number 16ZDA083), the Ministry of Education Humanities and Social Science Research Planning Fund Project (Grant Number 18YJAZH046), the Natural Science Foundation of Shanghai (Grant Number 18ZR1409400).

语种：英文

外文关键词：Emergency relief distribution; Vehicle routing problem; Fairness; Variable neighbourhood search; Ant colony optimization

摘要：In this paper, we address the problem of delivering a given amount of goods in emergency relief distribution. This problem is considered to be a specific case of capacitated vehicle routing. As a novel issue, peer-induced fairness concern is aimed at securing more customers' needs by introducing the peer-induced fairness coefficient, which is the value of the population size divided by direct travel time. Thus, a peer-induced fairness capacitated vehicle routing scheduling model is proposed to handle the trade-off between timeliness and fairness in emergency material delivery. To solve the specific NP-hard capacitated vehicle routing problem, the properties of this problem are analysed, and an improved hybrid ACO-VNS algorithm based on ant colony optimization and variable neighbourhood search algorithm with five neighbourhood structures is accordingly presented. A comparison of the proposed algorithm with CPLEX and common optimization algorithms demonstrates that this method achieves better performance in a shorter time and is an efficient way to solve the vehicle routing scheduling problem in emergency relief distribution.