In this paper, we present a general approach to solve optimization problems formulated as constraint network. Indeed, we perform a tabu search algorithm by maintaining a consistent neighborhood in a space search denned on partial configurations. Considering local consistency, the current network is coherent at each search iteration. We have applied our approach to three real problems with very large data, and shown the adaptation details.
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