一类仓库作业优化问题的混合遗传算法研究  

Research on One Class of Optimization Problem of the Automated Warehouse Using a New Kind of Hybrid Genetic Algorithm

作　　者：田国会[1] 张攀[1] 李晓磊[1] 尹建芹[1] 路飞[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061

出　　处：《系统仿真学报》2004年第6期1198-1201,共4页Journal of System Simulation

基　　金：国家自然科学基金(60104009);山东省自然科学基金(Z2000 G01)。

摘　　要：针对自动化立体仓库固定货架系统中拣选作业优化问题的特点, 分析并设计了一种新型高效混合遗传算法。提出了多起点2-最近点搜索算法进行初始种群的构造,采用了一种新的自适应启发式变异方法,显著改善了原有遗传算法的搜索能力。仿真结果表明该算法从执行时间和优化效果两方面均能够很好地满足作业要求。According to the requirements of the order-picking task of the fixed shelve in the automated warehouse, a kind of new rapid and efficient hybrid genetic algorithm is analysed and designed. The multi-start 2-nearest neighbor searcher is presented for the construction of the initial population and a new adaptive heuristic mutation is adopted. The ability of local searching of conventional genetic algorithm is prominently improved. The simulation indicates that this method can acquire good results, satisfying the demands of the work in both efficiency and optimization.

关 键 词：自动化立体仓库 组合优化问题 多起点2-最近点搜索算法 混合遗传算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]