Correlated Storage Assignment Strategy to reduce Travel Distance in Order Picking∗∗Zhang thanks the financial support of the china scholarship council (CSC).

Abstract

Abstract Diverse solutions of a correlated storage assignment strategy (CSAS) are developed in this paper to reduce the travel distance in the picker-to-parts order picking system in a single-block warehouse. The correlation among stock keeping units (SKUs) is considered for the storage location assignment. Because the correlation can be used in both the item clustering and the improvement of the results of other storage assignment strategies, a methodology, which includes a pre-process and two branching processes, is firstly proposed to develop algorithms of the CSAS. For the clustering-based CSAS, the sum-seed and the static-seed clustering algorithms are presented to find the itemsets, and four algorithms of sequencing itemsets and single SKUs are developed. For the improvement-based CSAS, the insertion algorithm searches the solution iteratively. In the experiment, the average travel distance per picking is used to measure the improvement of the CSAS. Compared with the full-turnover storage, the CSAS reduces maximal 2.08% of the average travel distance per picking.