An endosymbiotic evolutionary algorithm for the hub location-routing problem
type: Item
instance of: scholarly article
title: An endosymbiotic evolutionary algorithm for the hub location-routing problem
zbMATH Open document ID: 1394.90397
DOI: 10.1155/2015/525980
author: Ji Ung Sun
published in: Mathematical Problems in Engineering
publication date: 2018-08-27T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 90B80
Mathematics Subject Classification ID: 90C59
zbMATH DE Number: 6926570
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/525980
OpenAlex ID: W1605172996
Wikidata QID: Q59118859
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description: scientific article; zbMATH DE number 6926570