A tabu search Hooke and Jeeves algorithm for unconstrained optimization

This paper addresses the problem of finding the global minimum of a nonconvex function. A new hybrid algorithm for this problem based on tabu search is developed. It is hybrid in the sense that search directions are generated using tabu search strategy and then they are used in an optimization algorithm. The algorithm is tested on some standard test functions and its performance is compared with existing algorithms. Computational results show that the proposed algorithm is very efficient and robust.