Genetic algorithm for biobjective urban transit routing problem
This paper considers solving a biobjective urban transit routing problem with a genetic algorithm approach. The objectives are to minimize the passengers’ and operators’ costs where the quality of the route sets is evaluated by a set of parameters. The proposed algorithm employs an adding-node pro...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Publishing Corporation
2013
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| Online Access: | https://eprints.nottingham.ac.uk/2994/ |
| _version_ | 1848801174763864064 |
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| author | Chew, J.S.C. Lee, L.S. Seow, H.V. |
| author_facet | Chew, J.S.C. Lee, L.S. Seow, H.V. |
| author_sort | Chew, J.S.C. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper considers solving a biobjective urban transit routing problem with a genetic algorithm approach. The objectives are to
minimize the passengers’ and operators’ costs where the quality of the route sets is evaluated by a set of parameters. The proposed
algorithm employs an adding-node procedure which helps in converting an infeasible solution to a feasible solution. A simple
yet effective route crossover operator is proposed by utilizing a set of feasibility criteria to reduce the possibility of producing an
infeasible network. The computational results from Mandl’s benchmark problems are compared with other published results in the
literature and the computational experiments show that the proposed algorithm performs better than the previous best published
results in most cases. |
| first_indexed | 2025-11-14T18:20:22Z |
| format | Article |
| id | nottingham-2994 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T21:03:16Z |
| publishDate | 2013 |
| publisher | Hindawi Publishing Corporation |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-29942025-09-09T14:59:26Z https://eprints.nottingham.ac.uk/2994/ Genetic algorithm for biobjective urban transit routing problem Chew, J.S.C. Lee, L.S. Seow, H.V. This paper considers solving a biobjective urban transit routing problem with a genetic algorithm approach. The objectives are to minimize the passengers’ and operators’ costs where the quality of the route sets is evaluated by a set of parameters. The proposed algorithm employs an adding-node procedure which helps in converting an infeasible solution to a feasible solution. A simple yet effective route crossover operator is proposed by utilizing a set of feasibility criteria to reduce the possibility of producing an infeasible network. The computational results from Mandl’s benchmark problems are compared with other published results in the literature and the computational experiments show that the proposed algorithm performs better than the previous best published results in most cases. Hindawi Publishing Corporation 2013 Article PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/2994/1/Seow.pdf Chew, J.S.C., Lee, L.S. and Seow, H.V. (2013) Genetic algorithm for biobjective urban transit routing problem. Journal of Applied Mathematics, 2013 (698645). ISSN 1110-757X http://www.hindawi.com/journals/jam/2013/698645/ doi:10.1155/2013/698645 doi:10.1155/2013/698645 |
| spellingShingle | Chew, J.S.C. Lee, L.S. Seow, H.V. Genetic algorithm for biobjective urban transit routing problem |
| title | Genetic algorithm for biobjective urban transit
routing problem |
| title_full | Genetic algorithm for biobjective urban transit
routing problem |
| title_fullStr | Genetic algorithm for biobjective urban transit
routing problem |
| title_full_unstemmed | Genetic algorithm for biobjective urban transit
routing problem |
| title_short | Genetic algorithm for biobjective urban transit
routing problem |
| title_sort | genetic algorithm for biobjective urban transit
routing problem |
| url | https://eprints.nottingham.ac.uk/2994/ https://eprints.nottingham.ac.uk/2994/ https://eprints.nottingham.ac.uk/2994/ |