Joint Inventory and Fulfilment Optimization for an Omnichannel Retailer: A Stochastic Optimization Approach

36 Pages Posted: 15 May 2022

See all articles by Abdelrahman Aboelrous

Abdelrahman Aboelrous

affiliation not provided to SSRN

Adriana F. Gabor

Khalifa University

Yingqian Zhang

affiliation not provided to SSRN

Abstract

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

Suggested Citation

Aboelrous, Abdelrahman and Gabor, Adriana F. and Zhang, Yingqian, Joint Inventory and Fulfilment Optimization for an Omnichannel Retailer: A Stochastic Optimization Approach. Available at SSRN: https://ssrn.com/abstract=4110440 or http://dx.doi.org/10.2139/ssrn.4110440

Abdelrahman Aboelrous

affiliation not provided to SSRN ( email )

No Address Available

Adriana F. Gabor (Contact Author)

Khalifa University ( email )

Abu Dhabi
United Arab Emirates

Yingqian Zhang

affiliation not provided to SSRN ( email )

No Address Available

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