Spare part inventory optimization in a multi-echelon system based on genetic algorithm methods

摘要

Spare part inventory optimization in a multi-echelon system presents a difficult problem which involves a non-linear objective function and integer variables to be optimized. In this paper, an optimization model was developed, which maximizes the support probability and minimizes the support costs. In order to resolve the model, a dynamic niche gathering genetic algorithm (GA) optimization method was utilized. In this method, the clustering model and process of the algorithm were employed, which can improve the solving efficiency of the GA method. Finally, a numerical example was given, which showed the feasibility and validity of this method.