CAJ | 학술논문

针对单储位储存方式可能导致仓库存取通道拥挤和作业效率低的情形，提出了一种基于多候选储位的存取路径优化方法。首先分配了货物的存取储位，然后建立了多候选储位的车辆路径问题（ MLVRP）模型，并基于储位优先解码原则设计了遗传算法，最后通过算例证明该方法的有效性和算法的高效性。多候选储位的方法可以为取货任务至少节约18．4％（两个候选储位）和21．8％（三个候选储位）的路程，算法迭代10000次只需要434s。
침대단저위저존방식가능도치창고존취통도옹제화작업효솔저적정형，제출료일충기우다후선저위적존취로경우화방법。수선분배료화물적존취저위，연후건립료다후선저위적차량로경문제（ MLVRP）모형，병기우저위우선해마원칙설계료유전산법，최후통과산예증명해방법적유효성화산법적고효성。다후선저위적방법가이위취화임무지소절약18．4％（량개후선저위）화21．8％（삼개후선저위）적로정，산법질대10000차지수요434s。
With respect to the fact that every type of goods has only one storage location in warehouse will lead to crowded aisles and poor operational efficiency , this paper proposes an optimization approach for store and retriev-al routing problem when multi-candidate storages locations are assigned to each type of goods .First,the storage locations are allocated to goods .Then, a model is built for the vehicle routing problem with multi-candidate stor-age locations for each type of goods .A genetic algorithm based on priority-based decoding scheme is developed to solve the model .Finally , a case is given to illustrate the effectiveness of the proposed method and the efficiency of the algorithm.The solution that two-candidate and three candidate storage locations are allocated to each type of goods could at least save 18.4% and 21.8% distance for retrievals respectively .The algorithm iterated for 10000 times costs 434 seconds .