A Comparative Study of Three Echelon Inventory Optimization using Genetic Algorithm and Particle Swarm Optimization

Abstract

Supply chain is an integral part of the operations management and became a significant concept for overall profitability of industrial scenario. It consists of several levels in which material flows through various stages to reach the end customer. A three level supply chain consists of a manufacturer, distributor and retailer, who are the cost bearers. It is necessary to have a coordinated approach between the tiers so that the chain is timed accurately for least inventory and minimum cost consequently maximum profits. In this paper, we consider a coordinated three echelon supply chain with a single manufacturer supplying a single type of product to single distributor and then to a single retailer. A mathematical model is developed for the coordinated supply chain under consideration and it is solved using Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) for optimal values of decision variables and objective function. A numerical example is posed and the results obtained herein are compared for these techniques.