摘要
在已经存储一定数量货物的自动化仓库中,以基于随机存储策略的库区和货位分配以及堆垛机行驶时间为优化控制目标.优化模型中的约束包括堆垛机容量和行驶速度以及在多任务作业周期中先存后取、由近及远存储、由远及近出库等.用遗传算法求出动态货位分配和拣选路径优化的Pareto最优解.实验结果验证了提出的方法的有效性.
Optimal control objectives based on a stochastic storage strategy for an automated storage/ retrieval system （AS/RS）, in which some spaces are occupied, were defined as the assignment optimizations for the whole warehouse and locations in it, and that for travel time of storage/retrieval machines （SRMs）. Constraints in the optimization model include the capacity and the travel speed, and the rules such as storage first and retrieval last, storage from near to far, and retrieval from far to near for the SRMs in a multi-command cycle. The optimal Pareto solution of the dynamic location assignment and picking up path optimization was obtained using a genetic algorithm. An experiment was presented to show the feasibility of the proposed method.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2008年第3期415-421,共7页
Journal of Southwest Jiaotong University
基金
甘肃省科技基金资助项目(2GS066-A52-001-04)
关键词
遗传算法
自动化立体仓库
多目标优化
约束
动态货位分配
genetic algorithm
automated storage/retrieve system
multiobjective optimization
constraint
dynamic location assignment
