The backroom assignment problem for in-store order fulfillment

Abstract

Efficient in-store fulfillment is essential for today’s omnichannel services, as retailers are taking on tasks previously performed by customers themselves while shopping. This paper introduces a novel backroom assignment problem for omnichannel stores, aiming to optimize the allocation of articles to a forward pick area exclusively dedicated to online demand. We present both random and dedicated storage policy formulations for the backroom assignment problem (BAP), determining the allocation of articles, their quantities to the forward pick area, and the selection of storage units. To achieve a balance between computational efficiency and solution quality, we introduce two decomposition methods. We evaluate the impact of our proposed BAP formulations using real data from a drug store chain and quantify the effects of an increasing online demand ratio and different forward pick area sizes on the in-store logistical effort. Results from a three-store use case demonstrate that backroom assignments can substantially reduce in-store logistical effort compared to a scenario without backroom usage, especially as demand shifts increasingly towards the online channel. The results also show that our decomposition methods are effective in handling problem instances in most cases, equipping retailers to evaluate the influence of backroom assignments. We conclude with managerial implications and explore future research opportunities.