A Hybrid Improvement Heuristic for the One-Dimensional Bin Packing Problem

  • Authors:

  • Adriana C. F. Alvim;Celso C. Ribeiro;Fred Glover;Dario J. Aloise

  • Affiliations:

  • Department of Computer Science, Catholic University of Rio de Janeiro, Rua Marquês de São Vicente 225, Rio de Janeiro, 22453-900, Brazil. alvim@inf.puc-rio.br;Department of Computer Science, Catholic University of Rio de Janeiro, Rua Marquês de São Vicente 225, Rio de Janeiro, 22453-900, Brazil. celso@inf.puc-rio.br;Leeds School of Business, University of Colorado at Boulder, Boulder, CO 80309-0419, US. Fred.Glover@colorado.edu;Department of Computer Science and Applied Mathematics, Universidade Federal do Rio Grande do Norte, Natal, RN 59078-970, Brazil. dario@digi.com.br

  • Venue:
  • Journal of Heuristics
  • Year:
  • 2004

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Abstract

We propose in this work a hybrid improvement procedure for the bin packing problem. This heuristic has several features: the use of lower bounding strategies; the generation of initial solutions by reference to the dual min-max problem; the use of load redistribution based on dominance, differencing, and unbalancing; and the inclusion of an improvement process utilizing tabu search. Encouraging results have been obtained for a very wide range of benchmark instances, illustrating the robustness of the algorithm. The hybrid improvement procedure compares favourably with all other heuristics in the literature. It improved the best known solutions for many of the benchmark instances and found the largest number of optimal solutions with respect to the other available approximate algorithms.