経営情報と意思決定科学ジャーナル

1532-5806

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Influence of Artificial Intelligence on Lateral-Transshipment: Case Study, Mono-Echelon and Two-Retailer Inventory System

Elleuch Fadoi, Sarra Sghaier & Semi Boudabbous

We consider a single-tier inventory system composed of two retailers in which inventory choices at each depot are coordinated in a centralized manner. Lateral transshipments are permitted as recourse actions within the same tier of the inventory system to reduce the level of Service. However, this transshipment process usually results in unwanted delivery delays. In this research work, we propose a multiobjective model of the transshipment problem composed of two-Retailers which addresses the optimization of three contradictory objectives: (1) minimize the expected overall cost, (2) maximize the service rate. Artificial Intelligence (AI) is the present and future of technology. But how can it be implemented to improve production processes and the supply chain? Artificial Intelligence opens up an infinite number of scenarios to explore and develop, such as the possibility of seizing new commercial opportunities for greater growth, profitability and sustainability. In our research work, we emphasize the cooperation between these two new notions : Artificial intelligence and Lateral Transshipment. For this, a series of simulation experiments are performed to find the best transshipment policy, in terms, of minimizing the Average Global Desservice Rate.