【摘要】 蚁群算法是一种新型的启发式算法,研究表明该算法具有较强发现较好解的能力,但同时存在一些缺点如易出现停滞现象、收敛速度慢等.在蚁群算法的基础上结合自动化立体仓库固定货架拣选作业的特点,构建了货物拣选路径问题的数学模型,设计了新型的改进蚁群算法用于合理优化货物拣选路径以减少作业时间,并在算法中采取了三个改进措施,改善基本蚁群算法的搜索能力.候选节点集合策略和自适应调整算法参数能有效提高算法的搜索速度,选择算子使问题的解始终保持最优.实验表明该算法具有较好的全局寻优能力,收敛速度大幅度提高,能够很好地满足中大规模的拣选作业要求.更多还原

【Abstract】 Ant colony algorithm is a novel heuristic optimization algorithm.Study show that the algorithm has great ability of searching better solution,but at the same time there are some shortcomings such as tending to go into stagnation behavior and needing computing time.Based on ant colony algorithm,we analyzed the working characteristics of the order picking task of fixed storage racks in automated warehouse. Our objective is to acquire a preferable picking sequence and to minimize the storage/retrieval time.A mathematic model was constructed,and a kind of new improved ant colony algorithm was designed.To improve the search ability of the algorithm,three improvements were adopted.Awaiting nodes set and dynamic change on algorithm parameters effectively developed the search speed.Selection operator enabled the solution to be the optimization.An algorithm program was developed and computational simulations were carried.Simulation results demonstrate the improved algorithm has better overall search ability and quickly astringency,satisfying the demands of medium or large scale work.更多还原