Designing a multi-objective nonlinear cross-docking location allocation model using genetic algorithm

Authors

1 Assistant Professor, Dep. of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

2 M.Sc., Dep. of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

3 M.Sc., Dep. of Production and Operations Management, Chalmers University of Technology, Sweden

Abstract

In this study, a cross-docking system is designed at strategic and tactical levels. For making the strategic decisions, a multi-objective nonlinear location allocation model for cross-docks is presented based on a distri-bution location allocation model by Andreas Klose and Andreas Drexl. The model is further developed to in-clude the whole supply chain members and the objective functions are weighted by implementing AHP. A ge-netic algorithm solution is designed for sample cross-dock location allocation problems. In the tactical stage, model was further simulated under two different distribution strategies to decide on the tactical parameters. As an example, the performance of the model is verified.

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