Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh
This study explores transit-oriented development (TOD) in Dhaka City using optimization algorithms to provide urban planning and policy-making insights. The analysis examined the distribution of the TOD index values across the city and identified areas with varying levels of TOD potential. Two optim...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/atr/5625483 |
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| author | Md. Anwar Uddin Sumit Roy Tahsin Tamanna Rubayet Arafin Rimon |
| author_facet | Md. Anwar Uddin Sumit Roy Tahsin Tamanna Rubayet Arafin Rimon |
| author_sort | Md. Anwar Uddin |
| collection | DOAJ |
| description | This study explores transit-oriented development (TOD) in Dhaka City using optimization algorithms to provide urban planning and policy-making insights. The analysis examined the distribution of the TOD index values across the city and identified areas with varying levels of TOD potential. Two optimization algorithms, ant colony optimization (ACO) and particle swarm optimization (PSO), were employed to assess and compare the TOD index values. The results highlight the significance of transit infrastructure in promoting sustainable urban development, particularly in proximity to existing mass rapid transit (MRT) lines. PSO is more suitable for this study among the optimization algorithms because it offers a more precise TOD potential assessment. The findings suggest prioritizing investments in transit infrastructure and implementing TOD-friendly policies to foster sustainable urban growth and improve residents’ quality of life. Future studies can benefit from optimizing the algorithm parameters and incorporating real-world data to improve the accuracy of the TOD assessments. |
| format | Article |
| id | doaj-art-ad8c2c5aff234f2a9e995d57fe6f9a71 |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-ad8c2c5aff234f2a9e995d57fe6f9a712025-08-20T03:52:47ZengWileyJournal of Advanced Transportation2042-31952025-01-01202510.1155/atr/5625483Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, BangladeshMd. Anwar Uddin0Sumit Roy1Tahsin Tamanna2Rubayet Arafin Rimon3Military Institute of Science and TechnologyBangladesh University of Engineering and TechnologyMilitary Institute of Science and TechnologyRajshahi University of Engineering and TechnologyThis study explores transit-oriented development (TOD) in Dhaka City using optimization algorithms to provide urban planning and policy-making insights. The analysis examined the distribution of the TOD index values across the city and identified areas with varying levels of TOD potential. Two optimization algorithms, ant colony optimization (ACO) and particle swarm optimization (PSO), were employed to assess and compare the TOD index values. The results highlight the significance of transit infrastructure in promoting sustainable urban development, particularly in proximity to existing mass rapid transit (MRT) lines. PSO is more suitable for this study among the optimization algorithms because it offers a more precise TOD potential assessment. The findings suggest prioritizing investments in transit infrastructure and implementing TOD-friendly policies to foster sustainable urban growth and improve residents’ quality of life. Future studies can benefit from optimizing the algorithm parameters and incorporating real-world data to improve the accuracy of the TOD assessments.http://dx.doi.org/10.1155/atr/5625483 |
| spellingShingle | Md. Anwar Uddin Sumit Roy Tahsin Tamanna Rubayet Arafin Rimon Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh Journal of Advanced Transportation |
| title | Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh |
| title_full | Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh |
| title_fullStr | Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh |
| title_full_unstemmed | Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh |
| title_short | Leveraging Ant Colony and Particle Swarm Optimization Algorithms for Assessing the Transit-Oriented Development Potential: A Case Study of Dhaka, Bangladesh |
| title_sort | leveraging ant colony and particle swarm optimization algorithms for assessing the transit oriented development potential a case study of dhaka bangladesh |
| url | http://dx.doi.org/10.1155/atr/5625483 |
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