2024
doi: 10.12720/jait.15.3.414-421
A Biobjective Hub Location Model with Consideration of Congestion for Railway Transportation Planning
Sunarin Chanta1,*
,
Ornurai Sangsawang1 ,
Margaret M. Wiecek2 ,
Norio Tomii3
- 1Department of Industrial Management, Faculty of Industrial Technology and Management, King Mongkut’s University of Technology North Bangkok, Prachinburi, Thailand
- 2School of Mathematical and Statistical Sciences, Clemson University, Clemson, USA
- 3Department of Mechanical Engineering, College of Industrial Technology, Nihon University, Chiba, Japan
- Manuscript receivedSeptember 18, 2023
- revisedOctober 12, 2023
- acceptedOctober 26, 2023
- publishedMarch 26, 2024
Abstract
Transportation planning is highly essential and important, especially for railway systems. In this paper, we propose an optimization model to determine optimal station locations in a rail network. The objective is to minimize the total transportation cost, which is composed of operation costs and fixed costs. Congestion of the system is considered as the second objective, which is to minimize the longest travel time that a passenger spends on the trip. The problem is formulated as a multi-objective programming model and solved by the epsilon-constraint method. A case study of railway transportation is presented. By using the proposed optimization model, we are able to obtain all non-dominated solution points, which provides alternatives for decision-makers. The results are beneficial and support decision-making in railway transportation planning.
Keywords
- hub location
- railway
- transportation planning
- optimization
- congestion
How to Cite
Sunarin Chanta, Ornurai Sangsawang, Margaret M. Wiecek, and Norio Tomii, "A Biobjective Hub Location Model with Consideration of Congestion for Railway Transportation Planning," Journal of Advances in Information Technology, vol. 15, no. 3, pp. 414-421, 2024. https://doi.org/10.12720/jait.15.3.414-421
Copyright & License
Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
