[논문]폐쇄루프공급망모델에서 역물류 활동 강화: 혼합유전알고리즘 접근법

윤영수

doi:10.9723/jksiis.2021.26.1.055

폐쇄루프공급망모델에서 역물류 활동 강화: 혼합유전알고리즘 접근법
Reinforcing Reverse Logistics Activities in Closed-loop Supply Chain Model: Hybrid Genetic Algorithm Approach 원문보기

한국산업정보학회논문지 = Journal of the Korea Industrial Information Systems Research, v.26 no.1, 2021년, pp.55 - 65

초록
AI-Helper

본 연구에서는 폐쇄루프공급망 (Closed-loop supply chain: CLSC) 모델에서 역물류 (Reverse logistics: RL) 활동을 강화하기 위한 방법론을 개발한다. 이를 위해 RL 활동 중에서 주로 고려되는 설비 중의 하나인 회복센터(Recovery center: RC)의 활동을 강화한다. RC에서의 강화된 활동에 따라 고객으로부터 회수되는 사용 후 제품은 검사 및 회복과정을 거쳐 전방향물류 (Forward logistics: FL)에서 부품 혹은 제품으로 재사용된다. 강화된 RC 활동을 가진 CLSC 모델의 운영과정을 효율적으로 표현하기 위한 수리모델이 제시되며. 혼합유전알고리즘 (Hybrid genetic algorithm: HGA) 접근법을 이용해 제안된 수리모델이 이행된다. 수치실험에서는 두 개의 상이한 형태의 CLSC 모델이 제시되며, 본 연구에서 제안된 HGA 접근법과 기존의 연구에서 제안된 몇몇 접근법들의 수행도가 비교분석되었다. 비교분석결과 HGA가 기존의 접근법들 보다 더 우수한 수행도를 보여주었다. 또한 RC 활동의 검사 및 회복과정을 거친 부품 및 제품의 비율을 다양하게 조절함으로서 강화된 RC 활동을 가진 CLSC 모델의 유용성을 증명했다.

Abstract ▼ AI-Helper

In this paper, a methodology for reinforcing reverse logistics (RL) activities in a closed-loop supply chain (CLSC) model is proposed. For the methodology, the activities of the recovery center (RC) which can be considered as one of the facilities in the RL are reinforced. By the reinforced activities in the RC, the recovered parts and products after checking and recovering processes of the returned product from customer can be reused in the forward logistics (FL) of the CLSC model. A mathematical formulation is suggested for representing the CLSC model with reinforced RL activities, and implemented using a hybrid genetic algorithm (HGA) approach. In numerical experiment, two different scales of the CLSC model are presented and the performance of the HGA approach is compared with those of some conventional approaches. The experimental results show that the former outperforms the latter in most of performance measures. The robustness of the CLSC model is also proved by regulating various rates of the recovered parts and products in the RC.

주제어

표/그림 (12)

그림 Fig. 1 A Conceptual Network Flow of the Proposed CLSC Model
그림 Fig. 2 Various Activities at the RC
그림 Fig. 3 Flow Chart of the pro-HGA Approach
표 Table 1 CLSC Model with Two Different Scales
표 Table 2 Parameter Setting
표 Table 3 Performance Measures
표 Table 4 Experimental Results using Two Different Scales
표 Table 5 Various Rates of the Amounts sent from the RC to RT, PM and DP
그림 Fig. 4 Change of the Total Cost
그림 Fig. 5 Change of the Total Revenue
그림 Fig. 6 Changes of the total profit
표 Table 6 Changes of the Cost by using New Technology

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원문보기 상세보기
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