Public transportation can have an efficient role ingainingtraveler satisfaction while decreasing operation costs through establishing an integrated public transit system. The main objective of this research is to propose an integrated multimodal transit model to design the best combination of both railway and feeder bus mode transit systems, while minimizing total cost. In this paper, we have proposed a strategy for designing transit networks that provide multimodal services at each stop, and for consecutively assigning optimum demand to the different feeder modes. Optimum transit networks have been achieved using single and multi-objective approaches via metaheuristic optimization algorithms, such as simulated annealing, genetic algorithms, and the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The used input data and study area were based on the real transit network of Petaling Jaya, located in Kuala Lumpur, Malaysia. Numerical results of the presented model, containing the statistical results, the optimum demand ratio, optimal solution, convergence rate, and comparisons among best solutions have been discussed in detail.
Bibliographical noteFunding Information:
Acknowledgments: This research was supported by Jungseok Logistics Foundation Grant, and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2018R1A2B6005729) Author Contributions: In this study, all of the authors contributed to the writing of the manuscript. Their individual contributions are as follows: Mohammad HadiAlmasi and Ali Sadollah designed the experiments, performed the experiments and analyzed the data; Yoon-Seok Oh and Dong-Kyu Kim contributed analysis tools; Seungmo Kang contributed to drafting the manuscript and coordinated the overall research.
© 2018 by the authors.
- Integrated transit
- Multi-objective optimization
- Multimodal feeder
- Network design
ASJC Scopus subject areas
- Geography, Planning and Development
- Renewable Energy, Sustainability and the Environment
- Environmental Science (miscellaneous)
- Energy Engineering and Power Technology
- Management, Monitoring, Policy and Law