Abstract
An extended Tabu algorithm with an aspiration factor is proposed. The algorithm is based on the success of techniques such as the memorization of the previously visited subspaces, the systematic diversification as well as the intensification process for neighborhood creations. The numerical results obtained by solving a mathematical test function and the benchmark problem 22 of the TEAM Workshop reported in this paper demonstrate the usefulness of the proposed method.
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