TABU search methodology in global optimization

This paper investigates the application of TABU search methodology in global optimization. A general multilevel TABU search algorithm is proposed. The algorithm is applied to the problem of finding constrained global minima of a piecewise smooth function of the form ф(x) = max{ 1(x), …, m(x)} subject to box constraints. The tests are performed on a special class of problems of this type arising from the synthesis of radar polyphase codes. It is shown that problems of this type are NP-hard.