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研究生:黃冠捷
研究生(外文):Guan-JieHuang
論文名稱:禁忌搜尋法於自駕卡車搭配無人機模式之最佳配送
論文名稱(外文):A Tabu Search Solution Algorithm for Autonomous Truck-Drone Delivery
指導教授:胡大瀛胡大瀛引用關係
指導教授(外文):Ta-Yin Hu
學位類別:碩士
校院名稱:國立成功大學
系所名稱:交通管理科學系
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:95
中文關鍵詞:禁忌搜尋演算法自駕車無人機搭配無人機之旅行銷售員問題
外文關鍵詞:Tabu SearchAutonomous VehicleUnmanned Aerial VehicleTraveling Salesman ProblemFlying Sidekick Traveling Salesman Problem
相關次數:
  • 被引用被引用:2
  • 點閱點閱:253
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
Abstract i
摘要 iii
Contents iv
List of Table vi
List of Figure vii
CHAPTER 1 INTRODUCTION 1
1.1 Research Motivation and Background 1
1.2 Research Objectives 3
1.3 Research Flow Chart 3
CHAPTER 2 LITERATURE REVIEW 6
2.1 Autonomous Vehicles 6
2.2 Unmanned Aerial Vehicle (UAV) 8
2.2.1 Current States of Unmanned Aerial vehicles 8
2.2.2 Developments of Unmanned Aerial vehicles 9
2.3 Traveling Salesman Problem 10
2.3.1 Traveling Salesman Problem (TSP) 10
2.3.2 The Flying Sidekick Traveling Salesman Problem (FSTSP) 11
2.4 Vehicle Routing Problem 14
2.4.1 The Introduction of Vehicle Routing Problem 14
2.4.2 The extended problem of VRP 15
2.5 Tabu Search Method 25
2.6 Summary 28
CHAPTER 3 RESEARCH METHODOLOGY 29
3.1 Conceptual Framework 29
3.2 Problem Statement and Research Assumptions 30
3.3 Research Framework 34
3.4 Mathematical Formulation 36
3.5 Solution Algorithm 49
CHAPTER 4 NUMERICAL ANALYSIS 52
4.1 The Structure of Mathematical Model 52
4.2 The Structure of Heuristic Approach 53
4.2.1 Tabu Search Solution Algorithm 53
4.2.2 Heuristic Flowchart 57
4.3 Test Network Development 59
4.3.1 Test Network I 59
4.3.2 Test Network II 62
4.4 Results of Test Networks 64
4.4.1 Results of Test Network I Solving by GUROBI 64
4.4.2 Results of Test Network I Solving by Tabu Search Algorithm 68
4.4.3 Results of Test Network II Solving by GUROBI 70
4.4.4 Results of Test Network II Solving by Tabu Search Algorithm 72
4.5 Summary 74
CHAPTER 5 EMPIRICAL STUDY 76
5.1 Experimental Design and Setup 76
5.1.1 Experimental Design 76
5.1.2 Experimental Setup 79
5.2 Empirical Experiments 80
5.2.1 Empirical Instance with 20 Nodes 80
5.2.2 Empirical Instance with 30 Nodes 82
5.2.3 Empirical Instance with 40 Nodes 83
5.3 Results of Experimental Network 84
5.4 Summary 90
CHAPTER 6 CONCLUSIONS AND SUGGESTIONS 91
6.1 Conclusions 91
6.2 Suggestions 92
REFERENCE 93
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