Peer-induced fairness capacitated vehicle routing scheduling using a hybrid optimization ACO–VNS algorithm

Abstract

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.