Abstract
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.
| Original language | English |
|---|---|
| Article number | 734 |
| Journal | Sustainability (Switzerland) |
| Volume | 10 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2018 Mar 7 |
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Keywords
- Integrated transit
- Metaheuristics
- Multi-objective optimization
- Multimodal feeder
- Network design
ASJC Scopus subject areas
- Geography, Planning and Development
- Renewable Energy, Sustainability and the Environment
- Management, Monitoring, Policy and Law
Cite this
Optimal coordination strategy for an integrated multimodal transit feeder network design considering multiple objectives. / Almasi, Mohammad Hadi; Sadollah, Ali; Oh, Yoonseok; Kim, Dong Kyu; Kang, Seungmo.
In: Sustainability (Switzerland), Vol. 10, No. 3, 734, 07.03.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Optimal coordination strategy for an integrated multimodal transit feeder network design considering multiple objectives
AU - Almasi, Mohammad Hadi
AU - Sadollah, Ali
AU - Oh, Yoonseok
AU - Kim, Dong Kyu
AU - Kang, Seungmo
PY - 2018/3/7
Y1 - 2018/3/7
N2 - 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.
AB - 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.
KW - Integrated transit
KW - Metaheuristics
KW - Multi-objective optimization
KW - Multimodal feeder
KW - Network design
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UR - http://www.scopus.com/inward/citedby.url?scp=85043337401&partnerID=8YFLogxK
U2 - 10.3390/su10030734
DO - 10.3390/su10030734
M3 - Article
AN - SCOPUS:85043337401
VL - 10
JO - Sustainability
JF - Sustainability
SN - 2071-1050
IS - 3
M1 - 734
ER -