Qihuan Zhang , Ziteng Wang , Min Huang , Yang Yu , Shu-Cherng Fang
{"title":"Heterogeneous multi-depot collaborative vehicle routing problem","authors":"Qihuan Zhang , Ziteng Wang , Min Huang , Yang Yu , Shu-Cherng Fang","doi":"10.1016/j.trb.2022.03.004","DOIUrl":null,"url":null,"abstract":"<div><p>Collaborative vehicle routing of multiple logistics providers is an important component of horizontal logistic collaboration that generates economic and societal benefits. Existing research on collaborative vehicle routing is limited to the homogeneous setting where the logistics providers transport the same product. To better address the need of a general modeling framework and fast computational methods for the growth of collaboration among logistics providers carrying various products, we investigate a heterogeneous multi-depot collaborative vehicle routing problem (HMCVRP) in this paper. The key operational and computational challenge of realizing the collaborative route planning is to properly select transfer points for product transshipment between vehicles of different depots. We propose a Benders-based branch-and-cut algorithm with the technique of combinatorial Benders’ cuts to solve a mixed-integer programming formulation of HMCVRP. Numerical experiments indicate that the proposed algorithm significantly outperforms the CPLEX solver using the commonly adopted big-M transformation-based method. Additional computational study further reveals the importance of the locations of depots and having a well-designed cost savings allocation mechanism in practice.</p></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"160 ","pages":"Pages 1-20"},"PeriodicalIF":5.8000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part B-Methodological","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0191261522000467","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 13
Abstract
Collaborative vehicle routing of multiple logistics providers is an important component of horizontal logistic collaboration that generates economic and societal benefits. Existing research on collaborative vehicle routing is limited to the homogeneous setting where the logistics providers transport the same product. To better address the need of a general modeling framework and fast computational methods for the growth of collaboration among logistics providers carrying various products, we investigate a heterogeneous multi-depot collaborative vehicle routing problem (HMCVRP) in this paper. The key operational and computational challenge of realizing the collaborative route planning is to properly select transfer points for product transshipment between vehicles of different depots. We propose a Benders-based branch-and-cut algorithm with the technique of combinatorial Benders’ cuts to solve a mixed-integer programming formulation of HMCVRP. Numerical experiments indicate that the proposed algorithm significantly outperforms the CPLEX solver using the commonly adopted big-M transformation-based method. Additional computational study further reveals the importance of the locations of depots and having a well-designed cost savings allocation mechanism in practice.
期刊介绍:
Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.