Simulation of Allocation Policies for a Serial Inventory System under Advance Demand Information using Supply Chain Management Software

In this paper, we simulate allocation policies for a two-stage inventory system that receives perfect advance demand information (ADI) from customers belonging to different demand classes using AnyLogic as supply chain management software. Demands for each customer class are generated by independent Poisson processes while the processing times are deterministic. All customers in the same class have the same demand lead time (the difference between the due date and the requested date) and back-ordering costs.

Each stage in the inventory system follows order-base-stock-policies where the replenishment order is issued upon arrival of a customer order. The problem requires a fast and reliable method that determines the system performance under different policies and ADI. Thus, the researchers employ discrete event simulation using the supply chain management software to obtain output parameters such as inventory costs, fill rates, waiting time, and order allocation times. A numerical analysis is conducted to identify a reasonable policy to use in this type of system.

This research conducted using supply chain management software can benefit many companies in the automotive, high-tech, and apparel industries. Consider the case of the Faurecia Group, one of the world’s leading automotive suppliers, as an example of a supplier that manages its production based on the advance demand information provided by its customers such as PSA, Renault, BMW, and Toyota.

Effect of customer class priority and demand lead time on average costsEffect of customer class priority and demand lead time on average costs

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