Optimization of a feeder-bus route design by using a multiobjective programming approach
Table Of Contents
Chapter ONE
1.1 Introduction1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Research
1.9 Definition of Terms
Chapter TWO
2.1 Overview of Feeder-Bus Systems2.2 Evolution of Feeder-Bus Route Design
2.3 Multiobjective Programming in Transportation
2.4 Factors Influencing Feeder-Bus Route Optimization
2.5 Case Studies on Feeder-Bus Route Design
2.6 Challenges in Feeder-Bus Route Optimization
2.7 Benefits of Optimized Feeder-Bus Routes
2.8 Integration of Technology in Route Design
2.9 Best Practices in Feeder-Bus Route Optimization
2.10 Future Trends in Feeder-Bus Transportation
Chapter THREE
3.1 Research Methodology Overview3.2 Data Collection Methods
3.3 Sampling Techniques
3.4 Feasibility Analysis
3.5 Mathematical Modeling for Optimization
3.6 Software Tools for Analysis
3.7 Validation and Testing Procedures
3.8 Ethical Considerations in Research
Chapter FOUR
4.1 Data Analysis and Interpretation4.2 Feasibility Study Results
4.3 Optimization Models Implemented
4.4 Comparison of Different Route Designs
4.5 Impact Assessment of Optimized Routes
4.6 Stakeholder Feedback and Recommendations
4.7 Cost-Benefit Analysis
4.8 Sustainability Assessment
Chapter FIVE
5.1 Summary of Findings5.2 Conclusions Drawn from the Study
5.3 Recommendations for Future Research
5.4 Implications for Feeder-Bus Route Planning
5.5 Contributions to Transportation Optimization
Project Abstract
This paper presents a feeder-bus route design model, capable of minimizing route length, minimizing maximum route travel time of planned routes, and maximizing service coverage for trip generation. The proposed model considers constraints of route connectivity, subtour prevention, travel time upper bound of a route, relationships between route layout and service coverage, and value ranges of decision variables. Parameter uncertainties are dealt with using fuzzy numbers, and the model is developed as a multiobjective programming problem. A case study of a metro station in Taichung City, Taiwan is then conducted. Next, the programming problem in the case study is solved, based on the technique for order preference by similarity to ideal solution approach to obtain the compromise route design. Results of the case study confirm that the routes of the proposed model perform better than existing routes in terms of network length and service coverage. Additionally, increasing the number of feeder-bus routes decreases maximum route travel time, increases service coverage, and increases network length. To our knowledge, the proposed model is the first bus route design model in the literature to consider simultaneously various stakeholder needs and support for bus route planners in developing alternatives for further evaluation efficiently and systematically.
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