Abstract
TS (tabu search) is one of the meta-heuristic algorithms that can solve the combinatorial optimization problems, which is NP-hard such as TSPs (traveling salesman problems), satisfied. With the requirement of solving large-scale problems, we proposed a new parallel tabu search (PTS) approach, which was cooperated with genetic crossover operation for TSPs. In addition, a novel adaptive search strategy of intensification and diversification was proposed to improve the solution quality and efficiency in TS. Taking TSPs as sample, some simulation experiments were implemented. It was shown that our proposed PTS approach was feasible and effective.
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