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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Genetic Algorithm Approach for Multi-Objective Optimization of Closed-Loop Supply Chain Network
verfasst von : Li-Chih Wang, Tzu-Li Chen, Yin-Yann Chen, Hsin-Yuan Miao, Sheng-Chieh Lin, Shuo-Tsung Chen
Erschienen in: Proceedings of the Institute of Industrial Engineers Asian Conference 2013
Verlag: Springer Singapore
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Abstract
This paper applies multi-objective genetic algorithm (MOGA) to solve a closed-loop supply chain network design problem with multi-objective sustainable concerns. First of all, a multi-objective mixed integer programming model capturing the tradeoffs between the total cost and the carbon dioxide (CO2) emission is developed to tackle the multi-stage closed-loop supply chain design problem from both economic and environmental perspectives. The multi-objective optimization problem raised by the model is then solved using MOGA. Finally, some experiments are made to measure the performance.