【作者】 甘屹； 杜继涛；

【机构】 上海理工大学机械工程学院；

【摘要】 借鉴蚁群的并行活动,本文提出通过蚁群信息素分布多样性,蚁群更新信息素策略,体现寻优活动多样性。并在调度过程中,通过各寻优群体分别进行相互独立的蚁群寻优,在局部最优基础上获得全局最优解,实现并行蚁群优化。仿真结果说明,利用蚁群并行寻优的性能比基本蚁群算法更有效。更多还原

【Abstract】 Based on the ants’ parallel actions,the diversity of optimization wer embodied by the distributing multiformity of ant colony pheromone and the pheromone updating strategy.During the scheduling process, sub-colony search the optimum results independently.Then the global optimization can be accessed based on the local optimized results.The simulation shows that the performance of the parallel ACO is more efficiency than basic ACO.更多还原