Local search with constraint propagation and conflict-based heuristics

Local search with constraint propagation and conflict-based heuristics

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Article ID: iaor20032965
Country: United States
Volume: 139
Issue: 1
Start Page Number: 21
End Page Number: 45
Publication Date: Jul 2002
Journal: Artificial Intelligence
Authors: ,
Keywords: artificial intelligence
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 sheduling problems show that our approach competes well with the best highly specialized algorithms.

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