An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem

Abstract

We consider a capacitated hub location-routing problem (HLRP) which combines the hub location problem and multihub vehicle routing decisions. The HLRP not only determines the locations of the capacitated $p$-hubs within a set of potential hubs but also deals with the routes of the vehicles to meet the demands of customers. This problem is formulated as a 0-1 mixed integer programming model with the objective of the minimum total cost including routing cost, fixed hub cost, and fixed vehicle cost. As the HLRP has impractically demanding for the large sized problems, we develop a solution method based on the endosymbiotic evolutionary algorithm (EEA) which solves hub location and vehicle routing problem simultaneously. The performance of the proposed algorithm is examined through a comparative study. The experimental results show that the proposed EEA can be a viable solution method for the supply chain network planning.