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Title Page
Contents
Abstract 9
Chapter 1. Introduction 11
1.1. Background 11
1.1.1. Intelligent Transportation Systems 11
1.1.2. Online Supermarkets 14
1.2. Study Needs and Objective 15
1.3. Study Flowchart 19
Chapter 2. Literature Review 21
2.1. Overview 21
2.2. Meta-heuristic algorithm 22
2.3. Vehicle Routing Problem 24
Chapter 3. Data Collection and Analysis 26
3.1. Study Scope 26
3.2. Data Collection 27
3.2.1. Map Data 27
3.2.2. Transportation Data 28
3.2.3. Delivery Data 30
3.3. Data Processing 31
3.3.1. Map Data 31
3.3.2. Transportation Data 32
Chapter 4. Characteristic Analysis of Existing Delivery System 35
4.1. Overview 35
4.2. Evaluation of Existing Route 36
4.2.1. Existing delivery Route 37
4.2.2. Comparison with Dijkstra's algorithm Delivery Route 38
4.3. Summary 41
Chapter 5. Optimal route & scheduling based on meta-heuristic algorithm 42
5.1. Overview 42
5.2. Comparison Analysis between Meta-Heuristic algorithm 43
5.2.1. Genetic Algorithm Implementation 44
5.2.2. Tabu Search Implementation 44
5.2.3. Comparison Analysis Results 45
5.3. A Calculation of Optimal Vehicle Number & Route 46
5.3.1. Route Calculations each Vehicle number by using Tabu search 46
5.3.2. Calculation of Optimal Vehicle Number 48
5.4. Effectiveness comparison analysis 52
5.4.1. Operation Costs Analysis Result 54
5.4.2. Service Time Analysis Result 58
5.4.3. tCO₂ Emission Quantity Analysis Result 60
5.5. Summary 63
Chapter 6. Calculation of Routing Re-search with Real-time Transportation Data 65
6.1. Overview 65
6.2. Methodology for Real-time Dynamic Route 65
6.3. Efficiency Evaluation 68
6.4. Summary 70
Chapter 7. Conclusion and Further Study 71
7.1. Conclusion 71
7.2. Further study 72
REFERENCE 74
Table 1.1. Services & roles of ITS 11
Table 1.2. Function of complemented logical architecture 16
Table 2.1. Classification and types of VRP 25
Table 3.1. Composition of collected traffic data 29
Table 3.2. Composition of incident data 30
Table 3.3. Composition of time table speed data 33
Table 4.1. Sample of delivery data 37
Table 4.2. Improvement rate by each indicator 40
Table 5.1. Costs Calculation by each vehicle number 48
Table 5.2. Comparison vehicle number by each period 51
Table 5.3. Classification by each comparison analysis indicator & target 53
Table 5.4. Classification by improved vehicle number 53
Table 5.5. Improvement Rate of Operation Costs (Ex vs TS) 55
Table 5.6. Improvement Rate of Operation Costs (Ex vs TS) (excluded labor) 56
Table 5.7. Improvement Rate of Operation Costs (DI vs TS) 57
Table 5.8. Improvement Rate of Operation Costs (DI vs TS) (excluded labor) 58
Table 5.9. Improvement Rate of Service Time (Ex vs TS) 59
Table 5.10. Improvement Rate of Service Time (Di vs TS) 60
Table 5.11. Improvement Rate of tCO₂ emission quantity (Ex vs TS) 61
Table 5.12. Improvement Rate of tCO₂ emission quantity (Di vs TS) 62
Table 5.13. Average improvement by each comparison analysis indicator 64
Table 6.1. corresponsive vehicle ID and Incident contents 66
Table 6.2. Selected period and vehicle ID for route re-search 67
Table 6.3. Comparison delivery distance by each case 69
Table 6.4. Comparison delivery time by each case 69
Table 6.5. Comparison service time by each case 69
Fig 1.1. Information flow of ITS service field 12
Fig 1.2. Development of online supermarkets sales 14
Fig 1.3. Information flow of complemented logical architecture 17
Fig 1.4. Information flow of complemented physical architecture 18
Fig 1.5. Research flowchart 19
Fig 3.1. Collecting and merging map data 28
Fig 3.2. Data collection system based on probe vehicles 29
Fig 3.3. Expression of collected delivery data on the map 31
Fig 3.4. Map data processing procedure 32
Fig 3.5. Traffic data processing procedure 32
Fig 3.6. Normal distribution curve Traffic data 33
Fig 4.1. Information flow of optimal route search algorithm 35
Fig 4.2. Route extraction example 38
Fig 4.3. Comparison graphs by each indicator 40
Fig 5.1. Example concept of Vehicle Routing Problem 42
Fig 5.2. Comparison between meta-heuristic algorithm 45
Fig 5.3. Route planning by each vehicle number 47
Fig 5.4. Linear optimization description 49
Fig 5.5. Scatter diagram and regression line 50
Fig 5.6. Examples of changed vehicle number & route 52
Fig 5.7. Distributed Graph about Operation Cost (Ex vs TS) 54
Fig 5.8. Distributed Graph about Operation Cost (Ex vs TS) (excluded labor) 55
Fig 5.9. Distributed Graph about Operation Cost (DI vs TS) 56
Fig 5.10. Distributed Graph about Operation Cost (Di vs TS) (excluded labor) 57
Fig 5.11. Distributed Graph about Service Time (Ex vs TS) 59
Fig 5.12. Distributed Graph about Service Time (Di vs TS) 60
Fig 5.13. Distributed Graph about tCO₂ emission quantity (Ex vs TS) 61
Fig 5.14. Distributed Graph about tCO₂ emission quantity (Di vs TS) 62
Fig 6.1. Description of Incident data in Feb. 66
Fig 6.2. Description of planned route and blocked link 67
Fig 6.3. Description of Changed route and sequence 68
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