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Complete local search with memory

Author

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  • Sierksma, G.
  • Ghosh, D.

    (Groningen University)

Abstract

Neighborhood search heuristics like local search and its variants are some of the most popular approaches to solve discrete optimization problems of moderate to large size. Apart from tabu search, most of these heuristics are memoryless. In this paper we introduce a new neighborhood search heuristic that makes effctive use of memory structures in a way that is different from tabu search. We report computational experiments with this heuristic on the traveling salesperson problem and the subset sum problem.

Suggested Citation

  • Sierksma, G. & Ghosh, D., 2000. "Complete local search with memory," Research Report 00A47, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    • Handle: RePEc:gro:rugsom:00a47
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    File URL: http://irs.ub.rug.nl/ppn/240965930
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    References listed on IDEAS

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    1. David S. Johnson & Cecilia R. Aragon & Lyle A. McGeoch & Catherine Schevon, 1991. "Optimization by Simulated Annealing: An Experimental Evaluation; Part II, Graph Coloring and Number Partitioning," Operations Research, INFORMS, vol. 39(3), pages 378-406, June.
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    Cited by:

    1. Marta Sofia R. Monteiro & Dalila B. M. M. Fontes & Fernando A. C. C. Fontes, 2009. "Restructuring Facility Networks under Economy of Scales," FEP Working Papers 324, Universidade do Porto, Faculdade de Economia do Porto.

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