Conference Paper

Optimisation of the Beer Distribution Game with Complex Customer Demand Patterns

Dept. of Inf. Technol., Nat. Univ. of Ireland, Galway
DOI: 10.1109/CEC.2009.4983273 Conference: Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2009, Trondheim, Norway, 18-21 May, 2009
Source: DBLP

ABSTRACT This paper examines a simulation of the Beer Distribution Game and a number of optimisation approaches to this game. This well known game was developed at MIT in the 1960s and has been widely used to educate graduate students and business managers on the dynamics of supply chains. This game offers a complex simulation environment involving multidimensional constrained parameters. In this research we have examined a traditional genetic algorithm approach to optimising this game, while also for the first time examining a particle swarm optimisation approach. Optimisation is used to determine the best ordering policies across an entire supply chain. This paper will present experimental results for four complex customer demand patterns. We will examine the efficacy of our optimisation approaches and analyse the implications of the results on the Beer Distribution Game. Our experimental results clearly demonstrate the advantages of both genetic algorithm and particle swarm approaches to this complex problem. We will outline a direct comparison of these results, and present a series of conclusions relating to the Beer Distribution Game.

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Available from: Enda Howley, Jul 03, 2015
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    ABSTRACT: 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.
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