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. © 2002 Elsevier Science B.V. All rights reserved.
Jussien, N., & Lhomme, O. (2002). Local search with constraint propagation and conflict-based heuristics. Artificial Intelligence, 139(1), 21–45. https://doi.org/10.1016/S0004-3702(02)00221-7