Optimization of total inventory cost and order fill rate in a supply chain using PSO

Abstract

This paper proposes a method to optimize both the total cost and order fill rates in a supply chain using the particle swarm optimization (PSO) method. This method automatically adjusts the initial inventory levels of all tiers involved in a supply chain by considering information quality level (IQL), which is determined by the degree of availability of lead time history data. Analyses of variance are used to examine if there are any effects of IQL on the total cost and order fill rates. The results show that the proposed method finds better solutions which provide a lower inventory level while maintaining higher order fill rates than when PSO is not applied.