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研究生： 哈璱那
Hasna - Khairunnisa
論文名稱： 隨機最佳化選址模型-以電動機車充電站為例
Location and Allocation Optimization for Battery Station System of Electric Scooters
指導教授： 王孔政
Kung-Jeng Wang
口試委員: 喻奉天
Vincent F. Yu
曹譽鐘
Yu-Chung Tsao
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： 2015
畢業學年度： 103
語文別： 英文
論文頁數： 55
中文關鍵詞： 三階供應鏈 、二階隨機規劃模型 、位置配置 、電池交換站 、電動摩托車 、基因演算法 、蟻群演算法
外文關鍵詞： three echelon supply chain, two-level stochastic programming model, facility location problem, battery swap station, electric scooter, genetic algorithm, ant algorithm
相關次數： 點閱：362  下載：9 
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    • 隨著人口密度的增加，空氣汙染及交通運輸議題已被視為發展市區永續計畫的重要因素。摩托車是造成空氣汙染的原因之一，此問題可藉由提供方便、乾淨的電動摩托車及其電池交換站以求解決。本研究針對電動摩托車電池交換的位置配置問題，在需求不確定的情況下，建立一三階供應鏈網路模型，分別代表電池供應商、¬電池交換站及市場。本研究¬發展出二階隨機規劃模型，求解限制條件下的站別設置，以及供應商、電池交換站及市場間的作業指派，並以基因演算法求解利潤最大化。本研究的基因演算法整合線性規劃及貪婪啟發法。此外，以部分因子設計進行敏感度分析，以評估演算法的效率。本研究亦進行相關參數在不同參數值及不同大小問題下的測試。最後，比較三種問題解決演算法手法:基因演算法結合線性規劃、基演算法結合貪婪啟發法及新開發蟻群演算法結合貪婪啟發法的綜合績效評估。

    As the world’s population grows, air pollution and transportation are important issues to be considered in developing a city sustainable plan. Scooters are one of causes of air pollution in the city because they produces unhealthy air quality for the citizens. In order to deal with the air pollution problem, the use of electric scooter can answer it by providing a convenient, clean, and cost effective mode of personal transportation. This paper presents an electric scooter battery swap station location and allocation problem by designing a three-echelon supply chain network under demand uncertainty, representing battery suppliers, battery stations, and marketplaces. We develop a two-stage stochastic programming model to locate a number of stations in a finite set of potential sites, then assigning task between supplier, stations, and marketplaces, then the genetic algorithm is proposed to solve it. The objective is to design the system of electric scooter station in an area, in order to find the best location in that area where the station should be located. The battery station system of electric scooters also includes the battery allocation between the system networks, which are the suppliers, station, and marketplace. Performance evaluation of the algorithm to solve the propose model was conducted by comparing three methods, genetic algorithm with linear programming, genetic algorithm with greedy heuristic, and revised ant algorithm with greedy heuristic. Sensitivity analysis is also conducted to evaluate the algorithm efficiency by using fractional factorial design. Finally the problem related parameter sensitivity is performed to test the result under different parameter value and different demand variance.

    摘要 i ABSTRACT ii ACKNOWLEDGEMENTS iii TABLE OF CONTENTS iv LISTS OF TABLES vi LISTS OF FIGURES vii CHAPTER 1 INTRODUCTION 1 1.1 Research Background 1 1.2 Research Objective 3 1.3 Research Limitation 3 1.4 Thesis Structure 4 CHAPTER 2 LITERATURE REVIEW 5 2.1 Facility Location and Allocation Problem 5 2.2 Electric Scooter Station System 6 2.3 Solution Algorithm 11 CHAPTER 3 MODEL DEVELOPMENT 13 3.1 Model Formulation 13 3.1.1 Problem Definition 13 3.1.2 Mathematical Model 18 3.2 Solution Algorithm 21 3.2.1 Ant Algorithm 22 3.2.2 Genetic Algorithm 23 3.2.3 Fitness Function, Scenario Generation, and Termination Condition 24 CHAPTER 4 EXPERIMENT AND RESULTS 26 4.1 Performance Evaluation 26 4.2 Numerical Example 28 4.3 Sensitivity Analysis 32 4.3.1 Revised Ant Algorithm Parameter Sensitivity 32 4.3.2 Problem Parameters Sensitivity 34 CHAPTER 5 CONCLUSIONS 37 5.1 Conclusions 37 5.2 Contributions 38 5.3 Future Research 38 REFERENCES 39 APPENDIX 42 A. Data Parameter Setting for Performance Evaluation Comparison 42 B. Data Parameter Setting for Numerical Experiment 45 C. Revised Ant Algorithm with Greedy Heuristic Procedures 46 D. Genetic Algorithm Procedures 48 E. Numerical Example Results 50 F. Fractional Factorial Design Experiments Result 55 G. Data Parameter Setting for Problem Parameter Sensitivity 55

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