Local search with constraint propagation and conflict-based heuristics

  • Authors:

  • Narendra Jussien;Olivier Lhomme

  • Affiliations:

  • École des Mines de Nantes, BP 20722, Nantes Cedex 3, France;ILOG, 1681 route des Dolines, Valbonne, France

  • Venue:
  • Artificial Intelligence
  • Year:
  • 2002

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Abstract

Search algorithms for solving CSP (Constraint Satisfaction Problems) usually fall into one of two main families: local search algorithms and systematic algorithms. Both families have their advantages. Designing hybrid approaches seems promising since those advantages may be combined into a single approach. In this paper, we present a new hybrid technique. It performs a local search over partial assignments instead of complete assignments, and uses filtering techniques and conflict-based techniques to efficiently guide the search. This new technique benefits from both classical approaches: a priori pruning of the search space from filtering-based search and possible repair of early mistakes from local search. We focus on a specific version of this technique: tabu decision-repair. Experiments done on open-shop scheduling problems show that our approach competes well with the best highly specialized algorithms.