A novel hybrid alternate two phases differential evolution for binary CSPs

Abstract

A novel improve algorithm TPDE is proposed in this paper, which combines differential evolution(DE). Each individual contains two states, the attractive state and the repulsive state. In order to refrain from the shortcoming of premature convergence, a two point reversal crossover operator is defined and in the repulsive process each particle is repelled away from some inferior solution in the current tabu list to fly towards some promising areas which can introduce some new information to guide the swarm searching process. DE adjusts the mutation rate F and the crossover rate CR adaptively, taking account of the different distribution of population. TPDE maintains the diversity of population and improves the global convergence ability. It also improves the efficiency and success rate and avoids the premature convergence. Simulation and comparisons based on test-sets of CSPs demonstrate the effectiveness, efficiency and robustness of the proposed algorithm.