A genetic algorithm for a bi-objective capacitated arc routing problem

  • Authors:
  • P. Lacomme;C. Prins;M. Sevaux

  • Affiliations:
  • Université Blaise Pascal, LIMOS, Aubière Cedex, France;Université de Technologie de Troyes, LOSI, Troyes Cedex, France;Université de Valenciennes, LAMIH/SP, Le Mont Houy, Valenciennes Cedex, France

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2006

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Abstract

The capacitated arc routing problem (CARP) is a very hard vehicle routing problem for which the objective-in its classical form-is the minimization of the total cost of the routes. In addition, one can seek to minimize also the cost of the longest trip.In this paper, a multi-objective genetic algorithm is presented for this more realistic CARP. Inspired by the second version of the Non-dominated sorted genetic algorithm framework, the procedure is improved by using good constructive heuristics to seed the initial population and by including a local search procedure. The new framework and its different flavour is appraised on three sets of classical CARP instances comprising 81 files.Yet designed for a bi-objective problem, the best versions are competitive with state-of-the-art metaheuristics for the single objective CARP, both in terms of solution quality and computational efficiency: indeed, they retrieve a majority of proven optima and improve two best-known solutions.