研究生: |
邵亜喧 Moch - Yasin |
---|---|
論文名稱: |
A Simulated Annealing for Green Vehicle Routing Problem A Simulated Annealing for Green Vehicle Routing Problem |
指導教授: |
喻奉天
Vincent F. Yu |
口試委員: |
楊朝龍
Chao-Lung Yang 郭伯勳 Po-Hsun Kuo |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 工業管理系 Department of Industrial Management |
論文出版年: | 2013 |
畢業學年度: | 101 |
語文別: | 英文 |
論文頁數: | 74 |
中文關鍵詞: | alternative fuel vehicle 、simulated annealing |
外文關鍵詞: | alternative fuel vehicle, simulated annealing |
相關次數: | 點閱:259 下載:0 |
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Nowadays, the encouragement of the use of green vehicle is greater than it previously has ever been. In the United States, transportation sector is responsible for 28% of national greenhouse gas emissions in 2009. Therefore, there have been many studies devoted to the green supply chain management including the green vehicle routing problem (GVRP). GVRP plays a very important role in helping organizations with alternative fuel-powered vehicle fleets overcome obstacles resulted from limited vehicle driving range in conjunction with limited fuel infrastructure. The objective of GVRP is to minimize total distance traveled by the alternative fuel vehicle fleet. This study develops a mathematical model and a simulated annealing (SA) heuristic for the GVRP. Computational results indicate that the SA heuristic is capable of obtaining good GVRP solutions within a reasonable amount of time.
Nowadays, the encouragement of the use of green vehicle is greater than it previously has ever been. In the United States, transportation sector is responsible for 28% of national greenhouse gas emissions in 2009. Therefore, there have been many studies devoted to the green supply chain management including the green vehicle routing problem (GVRP). GVRP plays a very important role in helping organizations with alternative fuel-powered vehicle fleets overcome obstacles resulted from limited vehicle driving range in conjunction with limited fuel infrastructure. The objective of GVRP is to minimize total distance traveled by the alternative fuel vehicle fleet. This study develops a mathematical model and a simulated annealing (SA) heuristic for the GVRP. Computational results indicate that the SA heuristic is capable of obtaining good GVRP solutions within a reasonable amount of time.
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