Applying Adapted PSO Approach to Minimize Costs in the Beer Distribution Game Using Three Dynamic Demand Patterns

In this paper an artificial intelligence´s mono-objective algorithm known as Particle Swarm Optimization (PSO) was applied. This PSO was adapted to optimize the minimum costs in the Beer Distribution Game Problem. The PSO makes an adjustment of the policy´s order of the participants in the supply chain (retailer, wholesaler, distributor and manufacturer) minimizing the costs involved into the inventory holding and resulting costs from the backlogs in orders. The supply chain was tested under three dynamic consumer demand patterns: One Step, Uniform and Cyclic. The test results were compared based on the Non-Parametric Wilcoxon´s Signed-Rank Test, showing which is better to use equal or individual order policy for each participant in the chain.