Chaotic migration-based pseudo parallel genetic algorithm and its application
一种基于混沌迁移的伪并行遗传算法及其应用

To address the premature convergence in the searching process of genetic algorithm a chaotic migration-based pseudo parallel genetic algorithm (CMPPGA) is proposed,which applied the idea of isolated evolution and information exchanging in distributed parallel genetic algorithm by serial program structure to solve the optimization problem of low real-time demand.In this algorithm,the asynchronic migration of individuals during parallel evolution is guided by a chaotic migration sequence.Because the sequence is ergodic and stochastic,information exchanging among sub-populations is ensured to be efficient and sufficient.Simulation study of CMPPGA and its application to inventory optimization have proved its capability of strong global search and superiority to SGA and high immunity against premature convergence.