2016•Journal of the Korea Industrial Information Systems ResearchOpen access

Hybrid Genetic Algorithm Approach using Closed-Loop Supply Chain Model

YoungSu Yun, Chuluunsukh Anudari, Xing Chen

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Abstract

본 연구는 폐쇄루프 공급망 모델(Closed-Loop Supply Chain Model)을 이용하여 새로운 형태의 혼합형유전알고리즘(Proposed Hybrid Genetic Algorithm: pro-HGA)접근법의 수행도를 평가하기 위한 논문이다. 제안한 폐쇄루프 공급망 모델은 물류네트워크에서 순방향물류(Forward Logistics)와 역물류(Reverse Logistics)를 함께 고려한 통합형 물류모델이며. 이 모델에서는 회수된 제품의 재사용(Reuse), 재판매(Resale) 및 폐기(Waste Disposal)를 함께 고려하고 있다. 제안된 모델의 이행을 위해 기존연구에서 제안한 유전알고리즘(Genetic Algorithm: GA), 혼합형유전알고리즘(Hybrid Genetic Algorithm: HGA)과 본 연구에서 제안한 pro-HGA를 함께 적용하여 각 접근법들의 우수성을 비교분석하였다. 분석결과 본 연구에서 제안한 pro-HGA가 기존의 GA, HGA보다 더 우수한 결과를 얻었다. 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.

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What this paper is about

본 연구는 폐쇄루프 공급망 모델(Closed-Loop Supply Chain Model)을 이용하여 새로운 형태의 혼합형유전알고리즘(Proposed Hybrid Genetic Algorithm: pro-HGA)접근법의 수행도를 평가하기 위한 논문이다. 제안한 폐쇄루프 공급망 모델은 물류네트워크에서 순방향물류(Forward Logistics)와 역물류(Reverse Logistics)를 함께 고려한 통합형 물류모델이며. 이 모델에서는 회수된 제품의 재사용(Reuse), 재판매(Resale) 및 폐기(Waste Disposal)를 함께 고려하고 있다. 제안된 모델의 이행을 위해 기존연구에서 제안한 유전알고리즘(Genetic Algorithm: GA), 혼합형유전알고리즘(Hybrid Genetic Algorithm: HGA)과 본 연구에서 제안한 pro-HGA를 함께 적용하여 각 접근법들의 우수성을 비교분석하였다. 분석결과 본 연구에서 제안한 pro-HGA가 기존의 GA, HGA보다 더 우수한 결과를 얻었다. 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.

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Available abstract

본 연구는 폐쇄루프 공급망 모델(Closed-Loop Supply Chain Model)을 이용하여 새로운 형태의 혼합형유전알고리즘(Proposed Hybrid Genetic Algorithm: pro-HGA)접근법의 수행도를 평가하기 위한 논문이다. 제안한 폐쇄루프 공급망 모델은 물류네트워크에서 순방향물류(Forward Logistics)와 역물류(Reverse Logistics)를 함께 고려한 통합형 물류모델이며. 이 모델에서는 회수된 제품의 재사용(Reuse), 재판매(Resale) 및 폐기(Waste Disposal)를 함께 고려하고 있다. 제안된 모델의 이행을 위해 기존연구에서 제안한 유전알고리즘(Genetic Algorithm: GA), 혼합형유전알고리즘(Hybrid Genetic Algorithm: HGA)과 본 연구에서 제안한 pro-HGA를 함께 적용하여 각 접근법들의 우수성을 비교분석하였다. 분석결과 본 연구에서 제안한 pro-HGA가 기존의 GA, HGA보다 더 우수한 결과를 얻었다. 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.

Key concepts: Reuse, Genetic algorithm, Supply chain, Reverse logistics, Closed loop, Computer science, Mathematical optimization, Loop (graph theory)

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