Abstract
The purpose of this chapter is to present the use of Genetic Algorithm (GA) for solving multi-echelon inventory problems. The literature of GA dealing with inventory control problems is briefly reviewed with particular focus on multi-echelon systems. A novel GA based solution algorithm is introduced for effective management of a stochastic inventory system across a distribution network under centralized control. To demonstrate the performance of proposed GA structure, several test cases with different operational parameters are studied and experimented. The percentage differences between the total cost obtained by GA and the lower bounds and simulation results are used as performance indicators. Findings of the experiments show that the proposed GA approach can be very useful for obtaining feasible and satisfying solutions for the centralized inventory distribution problem.
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Çelebi, D. (2011). Evolutionary Inventory Control for Multi-Echelon Systems. In: Köppen, M., Schaefer, G., Abraham, A. (eds) Intelligent Computational Optimization in Engineering. Studies in Computational Intelligence, vol 366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21705-0_12
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