【摘要】 针对类电磁机制算法求解高维问题耗时的缺点,提出了一种蜜蜂进化型类电磁机制算法。在该算法中,种群的最优粒子作为蜂王与被选的每个粒子(雄蜂)以概率进行交叉操作,增强了对种群最优粒子所包含信息的开采能力。为了避免算法过早收敛,结合邻域搜索技术来改进种群中的粒子,提高了算法的勘探能力。理论分析表明新算法以概率1收敛到问题的最优解。实验结果表明,蜜蜂进化型类电磁机制算法是一种提高类电磁机制算法性能的有效改进算法。更多还原

【Abstract】 To overcome the shortcoming of high computational cost of standard electromagnetism-like mechanism algorithm for high dimensional problems,a Bee Evolutionary Electromagnetism-like Mechanism(BEEM)is presented.In BEEM,optimum individual as a queen-bee is in population crossover with each selected individua(ldrone).As a result,it reinforces the exploitation of standard electromagnetism-like mechanism algorithm.In order to avoid premature convergence,the neighbor search is adopted to improve individual in the population,and to enhance the exploration of electromagnetism-like mechanism algorithm.Its convergence to the global optimum with probability one is proven.Experiments results show BEEM is an efficient and effective algorithm.更多还原