Peer-induced fairness capacitated vehicle routing scheduling using a hybrid optimization ACO–VNS algorithm
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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.
KeywordsEmergency relief distribution Vehicle routing problem Fairness Variable neighbourhood search Ant colony optimization
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).
Compliance with ethical standards
Conflict of interest
Author Yifan Wu declares that he has no conflict of interest. Author Fan Pan declares that he has no conflict of interest. Author Shuxia Li declares that she has no conflict of interest. Author Zhen Chen declares that he has no conflict of interest. Author Ming Dong declares that he has no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
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