Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses
This paper considers an urban transit network design problem (UTNDP) that deals with construction of an efficient set of transit routes and associated service frequencies on an existing road network. The UTNDP is an NP-hard problem, characterized by a huge search space, multiobjective nature, and mu...
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| Format: | Article |
| Language: | English |
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Hindawi Limited
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/80106/1/Hybrid%20Differential%20Evolution-Particle%20Swarm%20Optimization%20Algorithm%20for%20Multiobjective%20Urban%20Transit%20Network%20Design%20Problem%20with%20Homogeneous%20Buses.pdf |
| _version_ | 1796980725777432576 |
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| author | Tarajo, Buba Ahmed Lee, Lai Soon |
| author_facet | Tarajo, Buba Ahmed Lee, Lai Soon |
| author_sort | Tarajo, Buba Ahmed |
| collection | UPM |
| description | This paper considers an urban transit network design problem (UTNDP) that deals with construction of an efficient set of transit routes and associated service frequencies on an existing road network. The UTNDP is an NP-hard problem, characterized by a huge search space, multiobjective nature, and multiple constraints in which the evaluation of candidate route sets can be both time consuming and challenging. This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. Computational experiments are conducted based on the well-known benchmark data of Mandl’s Swiss network and a large dataset of the public transport system of Rivera City, Northern Uruguay. The computational results of the proposed hybrid algorithm improve over the benchmark obtained in most of the previous studies. From the perspective of multiobjective optimization, the proposed hybrid algorithm is able to produce a diverse set of nondominated solutions, given the passengers’ and operators’ costs are conflicting objectives. |
| first_indexed | 2024-03-06T10:27:17Z |
| format | Article |
| id | upm.eprints-80106 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:27:17Z |
| publishDate | 2019 |
| publisher | Hindawi Limited |
| record_format | dspace |
| spelling | upm.eprints-801062020-09-22T01:49:51Z http://psasir.upm.edu.my/id/eprint/80106/ Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses Tarajo, Buba Ahmed Lee, Lai Soon This paper considers an urban transit network design problem (UTNDP) that deals with construction of an efficient set of transit routes and associated service frequencies on an existing road network. The UTNDP is an NP-hard problem, characterized by a huge search space, multiobjective nature, and multiple constraints in which the evaluation of candidate route sets can be both time consuming and challenging. This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. Computational experiments are conducted based on the well-known benchmark data of Mandl’s Swiss network and a large dataset of the public transport system of Rivera City, Northern Uruguay. The computational results of the proposed hybrid algorithm improve over the benchmark obtained in most of the previous studies. From the perspective of multiobjective optimization, the proposed hybrid algorithm is able to produce a diverse set of nondominated solutions, given the passengers’ and operators’ costs are conflicting objectives. Hindawi Limited 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/80106/1/Hybrid%20Differential%20Evolution-Particle%20Swarm%20Optimization%20Algorithm%20for%20Multiobjective%20Urban%20Transit%20Network%20Design%20Problem%20with%20Homogeneous%20Buses.pdf Tarajo, Buba Ahmed and Lee, Lai Soon (2019) Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses. Mathematical Problems in Engineering, 2019. art. no. 963240,. pp. 1-16. ISSN 1024-123X; ESSN: 1563-5147 https://www.hindawi.com/journals/mpe/2019/5963240/ 10.1155/2019/5963240 |
| spellingShingle | Tarajo, Buba Ahmed Lee, Lai Soon Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses |
| title | Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses |
| title_full | Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses |
| title_fullStr | Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses |
| title_full_unstemmed | Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses |
| title_short | Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses |
| title_sort | hybrid differential evolution particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses |
| url | http://psasir.upm.edu.my/id/eprint/80106/1/Hybrid%20Differential%20Evolution-Particle%20Swarm%20Optimization%20Algorithm%20for%20Multiobjective%20Urban%20Transit%20Network%20Design%20Problem%20with%20Homogeneous%20Buses.pdf |
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