AN ASSIGNMENT ALGORITHM FOR DYNAMIC PICKING SYSTEMS

In a dynamic environment, such as high-technology industry, a forward picking area requires an intelligent approach to ongoing rewarehousing (reassignment of stock items to locations). The items go through life cycles and product mix changes. Some items are common across multiple families in the product mix. Several of the items also tend to be pic ked in conjunction with other items, so their locations in the picking face should be made considering correlated assignments. This problem is not limited to high-technology industries, but also occurs in any s etting where there are seasonalities or promotional programs, such as in retail distribution. This paper describes an approach, conceptual f ramework, and heuristic Dynamic Stock Location Assignment Algorithm (S LAA) for dynamic reconfiguration of the order picking system. Previous relevant research is reviewed. This paper also provides a sensitivity analysis of the algorithm and shows that it performs consistently bet ter than the cube per order index rule at minimizing order processing time in dynamic environments with changing popularity and correlation of demand.