Evolutionary algorithms for the Vehicle Routing Problem with Time Windows

Olli Bräysy, Wout Dullaert, Michel Gendreau

Research output: Contribution to JournalReview articleAcademicpeer-review

Abstract

This paper surveys the research on evolutionary algorithms for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW can be described as the problem of designing least cost routes from a single depot to a set of geographically scattered points. The routes must be designed in such a way that each point is visited only once by exactly one vehicle within a given time interval. All routes start and end at the depot, and the total demands of all points on one particular route must not exceed the capacity of the vehicle. The main types of evolutionary algorithms for the VRPTW are genetic algorithms and evolution strategies. In addition to describing the basic features of each method, experimental results for the benchmark test problems of Solomon (1987) and Gehring and Homberger (1999) are presented and analyzed.

Original languageEnglish
Pages (from-to)587-611
Number of pages25
JournalJournal of Heuristics
Volume10
Issue number6
DOIs
Publication statusPublished - Dec 2004

Fingerprint

Vehicle Routing Problem with Time Windows
Vehicle routing
Evolutionary algorithms
Evolutionary Algorithms
Evolution Strategies
Test Problems
Exceed
Genetic algorithms
Genetic Algorithm
Benchmark
Interval
Costs
Experimental Results
Time windows
Vehicle routing problem

Keywords

  • Evolutionary algorithms
  • Genetic algorithms
  • Transportation
  • Vehicle routing

Cite this

Bräysy, Olli ; Dullaert, Wout ; Gendreau, Michel. / Evolutionary algorithms for the Vehicle Routing Problem with Time Windows. In: Journal of Heuristics. 2004 ; Vol. 10, No. 6. pp. 587-611.
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Evolutionary algorithms for the Vehicle Routing Problem with Time Windows. / Bräysy, Olli; Dullaert, Wout; Gendreau, Michel.

In: Journal of Heuristics, Vol. 10, No. 6, 12.2004, p. 587-611.

Research output: Contribution to JournalReview articleAcademicpeer-review

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