基于非支配遗传算法的自动化仓库动态货位优化∗

摘要

To solve the slotting optimization of AS/RS, in which random spaces were occupied, an optimi-zation method based on the dynamic storage strategy and non-dominated sorting genetic algorithm II ( NS-GA-II) was proposed. In this method, low energy consumption and high efficiency were taken into consid-eration for the section assignment and the locations and goods were numbered. Then, the optimization model was established for location assignment by defining the optimal objectives as the travel time of Storage/Re-trieval machines and the stability of the whole warehouse. Finally, the optimal Pareto solution of dynamic location assignment was obtained using the NSGA-II. A numerical example demonstrated the feasibility of the proposed method, which not only reduced the energy and time consumption of storage and retrieval cy-cle, but also improved the stability of the whole warehouse.%针对存有随机数量货物的机床零部件自动化立体仓库( AS/RS )中存在的货位规划难题，提出了一种基于动态的仓储模式与Pareto遗传算法的AS/RS货位优化方法。该方法以能耗最低和效率最高为基本原则规划库区和优化分配货架，完成货位编号和货品编号；以堆垛机行驶时间和货架稳定性为优化目标，建立货位多目标优化的数学模型；采用第二代非支配排序遗传算法得到动态货位优化的Pareto最优解。仿真实例计算结果表明，该方法使货物的出入库能量消耗、出入库效率以及货架的稳定性等指标得到较大改善。