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http://dx.doi.org/10.9723/jksiis.2016.21.4.031

Hybrid Genetic Algorithm Approach using Closed-Loop Supply Chain Model  

Yun, YoungSu (조선대학교 경상대학 경영학부)
Anudari, Chuluunsukh (조선대학교 대학원 경영학과)
Chen, Xing (조선대학교 대학원 경영학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.21, no.4, 2016 , pp. 31-41 More about this Journal
Abstract
This paper is to evaluate the performance of a proposed hybrid genetic algorithm (pro-HGA) approach using closed-loop supply chain (CLSC) model. The proposed CLSC model is a integrated supply chain network model both with forward logistics and reverse logistics. In the proposed CLSC model, the reuse, resale and waste disposal using the returned products are taken into consideration. For implementing the proposed CLSC model, two conventional approaches and the pro-HGA are used in numerical experiment and their performances are compared with each other using various measures of performance. The experimental results show that the pro-HGA approach is more efficient in locating optimal solution than the other competing approaches.
Keywords
Closed-Loop Supply Chain Model; Forward Logistics; Reverse Logistics; Hybrid Genetic Algorithm;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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