Premium
A branch‐and‐price‐based large neighborhood search algorithm for the vehicle routing problem with time windows
Author(s) -
PrescottGag Eric,
Desaulniers Guy,
Rousseau LouisMartin
Publication year - 2009
Publication title -
networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.977
H-Index - 64
eISSN - 1097-0037
pISSN - 0028-3045
DOI - 10.1002/net.20332
Subject(s) - vehicle routing problem , benchmark (surveying) , mathematical optimization , heuristic , set (abstract data type) , computer science , diversification (marketing strategy) , routing (electronic design automation) , algorithm , mathematics , computer network , geodesy , marketing , business , programming language , geography
Given a fleet of vehicles assigned to a single depot, the vehicle routing problem with time windows (VRPTW) consists of determining a set of feasible vehicle routes to deliver goods to a set of customers while minimizing, first, the number of vehicles used and, second, total distance traveled. A large number of heuristic approaches for the VRPTW have been proposed in the literature. In this article, we present a large neighborhood search algorithm that takes advantage of the power of branch‐and‐price which is the leading methodology for the exact solution of the VRPTW. To ensure diversification during the search, this approach uses different procedures for defining the neighborhood explored at each iteration. Computational results on the Solomo's and the Gehring and Homberge's benchmark instances are reported. Compared to the best known methods, the proposed algorithm produces better solutions, especially on the largest instances where the number of vehicles used is significantly reduced. © 2009 Wiley Periodicals, Inc. NETWORKS, 2009