Genetic Algorithm Approach for Multi-Objective Optimization of Closed-Loop Supply Chain Network

Li-Chih Wang,Shuo-Tsung Chen,Hsin-Yuan Miao,Sheng-Chieh Lin,Yin-Yann Chen,Tzu-Li Chen

doi:10.1007/978-981-4451-98-7_18

Genetic Algorithm Approach for Multi-Objective Optimization of Closed-Loop Supply Chain Network

Li-Chih Wang, Shuo-Tsung Chen + Show 4 more

https://doi.org/10.1007/978-981-4451-98-7_18

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Publication Date: Jan 1, 2013

Citations: 1

Affiliation: Tunghai University, National University of Formosa, National Formosa University, Fu Jen Catholic University

#Closed-loop Supply Chain Network Design #Multi-objective Mixed Integer Programming Model + Show 8 more

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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.

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