A path relinking algorithm for a multi-depot periodic vehicle routing problem

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• 作者：Alireza Rahimi-Vahed (1)
  Teodor Gabriel Crainic (2)
  Michel Gendreau (3)
  Walter Rei (2)
  
• 关键词：Multi ; depot periodic vehicle routing problem ; Path relinking ; Integrative co ; operative search
• 刊名：Journal of Heuristics
• 出版年：2013
• 出版时间：June 2013
• 年：2013
• 卷：19
• 期：3
• 页码：497-524
• 全文大小：295KB
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• 作者单位：Alireza Rahimi-Vahed (1)
  Teodor Gabriel Crainic (2)
  Michel Gendreau (3)
  Walter Rei (2)
  
  1. D茅partement Informatique et recherche op茅rationnelle and Interuniversity Research Centre on Enterprise Networks, Logistics, and Transportation (CIRRELT), Universit茅 de Montr茅al, C.P. 8888, succ. Centre-ville, Montreal, QC, H3C 3P8, Canada
  2. D茅partement Management et technologie, ESG and Interuniversity Research Centre on Enterprise Networks, Logistics, and Transportation (CIRRELT), Universit茅 du Qu茅bec 脿 Montr茅al, C.P. 8888, succ. Centre-ville, Montreal, QC, H3C 3P8, Canada
  3. D茅partement de math茅matiques et g茅nie Industriel and Interuniversity Research Centre on Enterprise Networks, Logistics, and Transportation (CIRRELT), 脡cole Polytechnique, C.P. 6079, succ. Centre-ville, Montreal, QC, H3C 3A7, Canada
  
• ISSN：1572-9397

文摘

In this paper, we consider a multi-depot periodic vehicle routing problem which is characterized by the presence of a homogeneous fleet of vehicles, multiple depots, multiple periods, and two types of constraints that are often found in reality, i.e., vehicle capacity and route duration constraints. The objective is to minimize total travel costs. To tackle the problem, we propose an efficient path relinking algorithm whose exploration and exploitation strategies enable the algorithm to address the problem in two different settings: (1) As a stand-alone algorithm, and (2) As a part of a co-operative search algorithm called integrative co-operative search. The performance of the proposed path relinking algorithm is evaluated, in each of the above ways, based on standard benchmark instances. The computational results show that the developed PRA performs well, in both solution quality and computational efficiency.