한국산업정보학회논문지 (Journal of Korea Society of Industrial Information Systems)

한국산업정보학회 (Korea Society of Industrial Information Systems)
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그린 공급망 네트워크 모델: 유전알고리즘 접근법

Green Supply Chain Network Model: Genetic Algorithm Approach

  • 투고 : 2019.06.03
  • 심사 : 2019.06.08
  • 발행 : 2019.06.30
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초록

본 연구에서는 그린공급망(green supply chain: gSC) 네트워크 모델이 제안된다. 제안된 gSC 네트워크 모델은 환경적 요인 및 경제적 요인을 고려한다. 환경적 요인으로는 부품 및 제품 수송 과정에서 발생하는 CO2 발생량의 총비용 최소화를 고려하며, 경제적 요인으로는 부품 및 제품 생산처리에 필요한 처리비용, 수송과정에서 발생하는 수송비용, 각 단계에서 고려되는 설비들의 개설을 위한 개설비용의 최소화를 고려한다. 수리모형에서는 환경적 요인 및 경제적 요인을 위해 고려되는 다양한 비용들의 총합의 최소화를 목적함수로 사용하며, 각 단계 간 수송량의 제약 등 다양한 제약조건을 함께 고려한다. 제안된 수리모형의 이행을 위해 유전알고리즘(Genetic algorithm: GA) 접근법을 사용한다. 수치실험에서는 네 가지 규모의 gSC 네트워크 모델을 제시하고, 이를 다양한 수행도 척도들을 사용하여 GA 접근법을 통해 해결하였다. 실험결과는 제안된 gSC 네트워크 모델과 GA 접근법의 우수성을 입증하였다.

In this paper, we design a green supply chain (gSC) network model. For constructing the gSC network model, environmental and economic factors are taken into consideration in it. Environmental factor is to minimize the $CO_2$ emission amount emitted when transporting products or materials between each stage. For economic factor, the total cost which is composed of total transportation cost, total handling cost and total fixed cost is minimized. To minimize the environmental and economic factors simultaneously, a mathematical formulation is proposed and it is implemented in a genetic algorithm (GA) approach. In numerical experiment, some scales of the gSC network model is presented and its performance is analyzed using the GA approach. Finally, the efficiencies of the gSC network model and the GA approach are proved.

키워드

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Fig. 1 Conceptual material flow structure for the gSC network model

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Fig. 2 Flow of transportation amount in the gSC_1

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Fig. 3 Flow of transportation amount in the gSC_2

Table 1 Four scales for the gSC network model implementationScale Supplier Manufacturer DC Retailer Customer

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Table 3 Computation results using the proposed GA approach

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Table 2 Measure of performance

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참고문헌

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피인용 문헌

  1. A Study of Cold Chain Logistics in China: Hybrid Genetic Algorithm Approach vol.25, pp.6, 2020, https://doi.org/10.9723/jksiis.2020.25.6.159