Study on an adaptive tabu search genetic algorithm

In order to solve the contradiction between reducing search space and keeping the diversity of evolution population in a genetic algorithm, an adaptive tabu search genetic algorithm is proposed. This algorithm adaptively changes the receiving probability of the tabu schema according to the diversity of evolution population, which not only reduces the search space and accelerates convergence speed but also efficiently avoids premature convergence. The simulation results show that the algorithm presented in the paper is effective.