Joint Inventory and Fulfilment Optimization for an Omnichannel Retailer: A Stochastic Optimization Approach
36 Pages Posted: 15 May 2022
We study an inventory optimization problem for a retailer that faces stochastic online and in-store demand in a selling season of fixed length. The retailer has to decide the initial inventory levels and an order fulfilment policy such that the expected total costs are minimized. We approximate the problem by a two stage stochastic optimization on a reduced number of scenarios. For deciding the representative scenarios, we propose a new similarity measure and a novel technique that combines the framework of Good-Turing sampling and Linear Programming. On randomly generated instances, the proposed algorithm obtains an average cost reduction of 7.56% compared to a state of the art algorithm in literature. The proposed algorithm works considerably better for short time horizons and relatively large proportion of in-store customers.
Keywords: Omnichannel retailer, Inventory, Scenario Reduction, Stochastic optimization
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