A new tabu search method for optimization with continuous parameters

A new tabu search algorithm for global optimization of multimodal functions with continuous variables is presented. The taboo list contains all points and a prohibited zone around each point that depends on the value of the objective function and decreases as the number of iteration increases. The numerical results obtained by solving problems 22 and 25 of the TEAM workshop demonstrate the speed effectiveness of the proposed method. It is compared favorably with other tabu search, genetic algorithm, and simulated annealing.