Metaheuristic Approaches To Optimize Supply Chain Design Problems

Abstract

Every manufacturing process in this industry booming world requires cost effective and precise design of supply chain. Eventually, the population demand as well as the sustainability issues have impacted on overall supply chain network system. As like as other optimization fields like energy, system, the supply chain network optimization has become an indispensable part of every industry. In this research authors will try to concentrate on an efficient optimization method in a supply chain planning (SCP). At first, authors would demonstrate a supply chain model consisting of suppliers, assemblers, distribution centers and retailers. This model would be expressed as MIXED INTEGER NON- LINEAR PROGRAMMING MODEL firstly and two widely used metaheuristic technique e.g. Particle Swarm Optimization (PSO) and Teaching Learning based Optimization (TLBO) have been implemented to optimize that model. Core objective of this optimization model concludes cost minimization with respect to the service level in every echelon of supply chain. In the comparison between PSO and TLBO, TLBO shows better optimality in this minimization problem.