Applying genetic algorithm in a joint decision problem of inventory optimization and order allocation in an omnichannel retailer

Abstract

Since e-commerce has become a popular trend for businesses to reach more customers, many retailers are gradually evolving into omnichannel retailers which can merge offline and online and offer a variety of shopping models to reach customers in more ways. Vietnam's retailers are likewise affected by this wave and have undergone significant changes since the COVID-19 pandemic's entrance. However, for some businesses, managing and operating an omnichannel system is still new. This paper focuses on an omnichannel retailer in Vietnam to study, which is in a struggle with managing the inventory while dealing with many stores operating in both offline and online channels. By targeting the problem into Inventory Optimization in proposing an integrated inventory for both channels and considering transshipment among stores, and Order Allocation in an aspect of minimizing cost for each replenishment, this paper builds a joint decision model and applies Genetic Algorithm to solve. Results gathered by CLPEX demonstrate that the suggested model may perform better in terms of operating expenses for the system, however, there is a problem when solving the problem using GA, so an optimal - solution cannot be produced by applying this approach. However, the result by CLPEX can prove that by implementing the proposed system which uses an integrated inventory policy, it can be more economic than the current system.