A Combined Dynamic Programming and Simulation Approach to the Sizing of the Low-Level Order-Picking Area

Abstract

In order to increase the efficiency of the order-picking process, warehouses are forced to find ways to adopt to constantly intensifying changes in the assortment and quantities of stored products. Accordingly, we present a methodology that deals with such a problem at a tactical level by defining the optimal size and an allocation of products within the order-picking area of the most typical order-picking setting. The methodology combined two methods, dynamic programming and simulation modelling, with the aim of taking advantages of their positive features. In that sense, the optimal allocation of products for different sizes of the order-picking zone were obtained by the dynamic programming approach. Afterwards, the influence of a demand’s seasonality and variations were treated by the simulation model, so that the more realistic performances of the system were captured for the optimal allocation of products. The methodology was tested on the retailer data with significant week seasonality. The obtained results confirmed the practical applicability of the methodology in real systems, while the sensitivity analysis of results showed that special attention and effort should be given to the determination of costs related to the engagement of order-pikers, storage equipment and unit replenishment during a planning period.

Online and Offline Model for Housekeeping Order Assignment Based on Dynamic Programming Algorithm

“…The results show that the allocation results obtained by the model are highly optimized. Djurdjević et al [44] combined DP and simulation modeling methods and proposed a method to define the optimal size and product allocation in the order selection area of the most typical order selection settings. The results show that this method can effectively solve the optimal configuration of products in picking areas of different scales.…”

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