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A Reactive Greedy Randomized Variable Neighborhood Tabu Search for the Vehicle Routing Problem with Time Windows

  • Panagiotis P. Repoussis
  • Dimitris C. Paraskevopoulos
  • Christos D. Tarantilis
  • George Ioannou
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4030)

Abstract

This paper presents a hybrid metaheuristic to address the vehicle routing problem with time windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from a depot to geographically dispersed customers. The routes must be designed such that each customer is visited only once by exactly one vehicle without violating capacity and time window constraints. The proposed solution method is a multi-start local search approach which combines reactively the systematic diversification mechanisms of Greedy Randomized Adaptive Search Procedures with a novel Variable Neighborhood Tabu Search hybrid metaheuristic for intensification search. Experimental results on well known benchmark instances show that the suggested method is both efficient and robust in terms of the quality of the solutions produced.

Keywords

Local Search Tabu Search Greedy Randomize Adaptive Search Procedure Vehicle Route Problem Tabu List 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Panagiotis P. Repoussis
    • 1
  • Dimitris C. Paraskevopoulos
    • 1
  • Christos D. Tarantilis
    • 1
  • George Ioannou
    • 1
  1. 1.Athens University of Economics & BusinessAthensGreece

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