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研究生: Candra Bachtiyar
Candra - Bachtiyar
論文名稱: 以模擬退火法求解具容量限制之綠色車輛途程問題
A Simulated Annealing Heuristic for the Capacitated Green Vehicle Routing Problem
指導教授: 喻奉天
Vincent F. Yu
口試委員: 郭伯勳
Po-Hsun Kuo
楊朝龍
Chao-Lung Yang
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: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 77
中文關鍵詞: 绿色车辆路径问题替代燃料容量限制的VRP模拟退火
外文關鍵詞: Green vehicle routing problem, alternative fuel, capacitated VRP, simulated annealing.
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获能的绿色车辆路径问题(CGVRP)是绿色车辆路径问题(GVRP)的延伸。它特点是注重环境和经济成本,通过实施有效的途径,以满足对环境的关注,同时满足客户的需求。 CGVRP的数学模型是制定和模拟退火(SA)的启发,提出了其解决方案。 CGVRP配制成混合整数线性规划(MILP)。 CGVRP的目标是尽量减少其使用的替代燃料汽车(AFV)总的旅行距离。数值试验和敏感性分析是基于埃尔多安和米勒钩(2012)与随机需求进行。数值实验的结果表明,SA算法能够获得在一个合理的时间量好CGVRP解决方案。少量车辆通行能力增加导致总行程距离,直到35%。敏感性分析表明,车辆的通行能力影响到总的旅行距离。数量最多的车辆容量的减少行进距离和总行程距离取决于客户的数目以及车辆行驶范围。


Capacitated green vehicle routing problem (CGVRP) is an extension of green vehicle routing problem (GVRP). It characterized by focusing on the environmental and economic costs by implementing effective routes to meet the environmental concerns while fulfilling customer demand. Mathematical model of CGVRP is formulated and a simulated annealing (SA) heuristic is proposed for its solution. CGVRP formulated as a mixed integer linear program (MILP). The objective of CGVRP is minimizing total travel distance which using an alternative fuel vehicle (AFV). Numerical experiment and sensitivity analysis are conducted based on Erdoğan and Miller-Hooks (2012) with random of demand. Result of numerical experiment shows that SA algorithm is capable of obtaining good CGVRP solutions within a reasonable amount of time. A small amount vehicle capacity cause increasing total travel distance until 35%. The sensitivity analysis shows that the vehicle capacity effect to the total travel distance. The largest number of vehicle capacity reduces travel distance and the total travel distance is dependent on the number of customer and the vehicle driving range.

ACKNOWLEDGMENT iv ABSTRACT v TABLE OF CONTENTS vi LIST OF FIGURES viii LIST OF TABLES ix CHAPTER 1 INTRODUCTION 1 1.1 Background 1 1.2 Objective 5 1.3 Research Contribution 6 1.4 State of the Art 6 1.5 Research Scope 10 1.6 Organization of Thesis 10 CHAPTER 2 LITERATURE REVIEW 11 2.1 Green Supply Chain Management 11 2.2 Vehicle Routing Problem (VRP) 12 2.3 Green Vehicle Routing Problem 15 2.4 Alternative Fuel and Alternative Fuel Vehicle 16 2.5 Simulated Annealing 19 CHAPTER 3 MODEL DEVELOPMENT 21 3.1 Problem Statement 21 3.2 Assumptions 21 3.3 Mathematical Formulation 22 CHAPTER 4 METHODOLOGY 28 4.1 Solution Representation 28 4.2 Simulated Annealing (SA) Algorithm 29 4.3 Initial Solution 30 4.4 Neighborhood 32 4.5 SA Parameter 34 CHAPTER 5 NUMERICAL EXPERIMENT 35 5.1 CGVRP Model Verification 35 5.2 Parameter Setting 36 5.3 Performance of SA in Benchmark Instance of Related Problem 41 5.4 Numerical Experiment on CGVRP 49 5.4.1 Small Instance CGVRP 50 5.4.2 Large Instance CGVRP 57 5.4.3 Sensitivity Analysis 58 CHAPTER 6 CONCLUSION AND RECOMMENDATION 63 6.1 Conclusion 63 6.2 Recommendation 63 REFERENCES 65

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