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[학술저널]

  • 학술저널

Tracey Tshivhase(Tokyo Metropolitan University) Yasutaka Kainuma(Tokyo Metropolitan University)

DOI : 10.7232/iems.2020.19.4.847

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초록

Environmental impact of greenhouse gases in the supply chain has been a topic of major interest recent years. A bi-objective optimization problem is used to minimize the total cost and the nitrogen oxides in a typical light manufacturing industry. Nitrogen oxides are a well-known component of smog which reduces visibility in the atmosphere. This paper models a supply chain problem for cost minimization while also considering the nitrogen emissions from the facilities and transportation. Initially, the total costs part of the bi-objective problem is solved as a mixed integer linear problem using the genetic algorithm. The model minimizes the total costs of the supply chain including transportation costs. The proposed MILP is tested with random data of 11 different sets. The facilities and transportation options are limited by their capacities. A genetic algorithm in MATLAB was initially used for solving the first objective function. For better results, the model was finally solved with particle swarm optimization.

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ABSTRACT
1. INTRODUCTION
2. MODEL DEVELOPMENT
3. COMPUTATIONAL APPROACH
4. RESULTS AND DISCUSSIONS
5. CONCLUSION
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