Robust omnichannel retail operations with the implementation of ship-from-store

Abstract

In this paper, we consider an omnichannel retailer (o-tailer) selling multiple products through a capacitated retail network over a multi-period horizon, where each inventory facility is equipped with a certain ability to fulfill the orders regardless of the channel. We study omnichannel retail operations with the implementation of ship-from-store to minimize the o-tailer’s expected total cost. At the start of each period, the o-tailer determines how much to replenish each product for each distribution center (DC), and how to allocate its inventory from DCs to different stores. At the end of each period, the o-tailer decides from which DCs and/or stores to fulfill the realized online demands. We formulate the problem as a multi-period stochastic optimization model and adopt a robust two-phase approach (RTA) to solve it. Phase 1 determines the binary replenishment decisions using a target-oriented robust optimization approach, whereas Phase 2 uses a linear decision rule to adaptively determine the replenishment, allocation, and fulfillment quantities. Numerical experiments suggest that the RTA outperforms existing approaches and can efficiently produce good-quality and robust solutions for realistic problem instances. A further sensitivity analysis explores the impacts of various system parameters on the RTA’s performance and the benefits of omnichannel fulfilment.