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http://dx.doi.org/10.9723/jksiis.2017.22.2.079

Adaptive Hybrid Genetic Algorithm Approach for Optimizing Closed-Loop Supply Chain Model  

Yun, YoungSu (조선대학교 경상대학 경영학부)
Chuluunsukh, Anudari (조선대학교 대학원 경영학과)
Chen, Xing (조선대학교 대학원 경영학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.22, no.2, 2017 , pp. 79-89 More about this Journal
Abstract
The Optimization of a Closed-Loop Supply Chain (CLSC) Model Using an Adaptive Hybrid Genetic Algorithm (AHGA) Approach is Considered in this Paper. With Forward and Reverse Logistics as an Integrated Logistics Concept, The CLSC Model is Consisted of Various Facilities Such as Part Supplier, Product Manufacturer, Collection Center, Recovery Center, etc. A Mathematical Model and the AHGA Approach are Used for Representing and Implementing the CLSC Model, Respectively. Several Conventional Approaches Including the AHGA Approach are Used for Comparing their Performances in Numerical Experiment.
Keywords
Adaptive Hybrid Genetic Algorithm; Closed-Loop Supply Chain Model; Forward Logistics; Reverse Logistics; Mathematical Model;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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