Application of particle swarm intelligence algorithms in supply chain network architecture optimization

In today’s globalization, the success of an industry is dependent on cost effective supply chain management under various markets, logistics and production uncertainties. Uncertainties in the supply chain usually decrease profit, i.e. increase total supply chain cost. Demand uncertainty and constraints posed by the every echelon are important factors to be considered in the supply chain design operations. Optimization is no longer a luxury but has become the order of the day. This paper specifically deals with the modeling and optimization of a three echelon supply chain network using the particle swarm optimization/intelligence algorithms.

► We developed mathematical model for three echelon supply chain network model.
► We used four PSO Variants for the performance analysis of supply chain network.
► We applied particle swarm intelligence algorithms in supply chain network architecture optimization.
► We have compared computational efforts and solutions obtained by the PSO variants.
► PSO algorithm works like DSS for supply chain managers.