A Multi-objective Optimization for Green Supply Chain Network Design with Multi-period Stochastic Demand

• Main Authors: Pei-Han Lee, 李沛涵
• Other Authors: Dah-chuan Gong
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/96900880489340158423

碩士 === 中原大學 === 工業與系統工程研究所 === 100 === Global warming related issues have caught much attention recently. These include the impact of climate change around the world, which is getting worst and causing many dangerous problems for human and living things. In order to control greenhouse gas emissions and then to slow down the global warming, Kyoto Protocol has been implemented for the purposes. It clearly specifies its member countries’ responsibility to reduce six greenhouse gases’ emissions. Among them, the amount of carbon emission contributes the most. In past, the traditional design of supply chain network only pursues economic goal, high profitability and low cost. In the present, as carbon emissions is increasing, importance of environmental protection cannot be ignored. Therefore, in this thesis we focus on a supply chain network design model. Under the considerations of multi-period stochastic demand, limited factory capacity, inventory, supply amount, and various environmental investments, we propose a multi-objective optimization model to minimize the total cost and carbon emission. In the solving process, we first apply the chance constrained programming method to convert the uncertainty mode to the certainty mode, and then solve the multi-objective problem via the normalized normal constraint method. Finally, through numerical examples and parameter analyses, we discuss the obtained managerial insights. Expect this model can serve as an effective tool for firm to design its green supply chain network and to achieve a balance between its economic sustainability and environmental sustainability.