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 proce...

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Main Authors: Chew, J. S. C., Lee, Lai Soon, Seow, Hsin Vonn
Format: Article
Language:English
Published: Hindawi Publishing Corporation 2013
Online Access:http://psasir.upm.edu.my/id/eprint/30330/
http://psasir.upm.edu.my/id/eprint/30330/1/Genetic%20algorithm%20for%20biobjective%20urban%20transit%20routing%20problem.pdf
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author Chew, J. S. C.
Lee, Lai Soon
Seow, Hsin Vonn
author_facet Chew, J. S. C.
Lee, Lai Soon
Seow, Hsin Vonn
author_sort Chew, J. S. C.
building UPM Institutional 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.
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spelling upm-303302016-02-15T04:48:49Z http://psasir.upm.edu.my/id/eprint/30330/ Genetic algorithm for biobjective urban transit routing problem Chew, J. S. C. Lee, Lai Soon Seow, Hsin Vonn 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 http://psasir.upm.edu.my/id/eprint/30330/1/Genetic%20algorithm%20for%20biobjective%20urban%20transit%20routing%20problem.pdf Chew, J. S. C. and Lee, Lai Soon and Seow, Hsin Vonn (2013) Genetic algorithm for biobjective urban transit routing problem. Journal of Applied Mathematics, 2013. art. no. 698645. pp. 1-15. ISSN 1110-757X; ESSN: 1687-0042 http://dx.doi.org/10.1155/2013/698645 10.1155/2013/698645
spellingShingle Chew, J. S. C.
Lee, Lai Soon
Seow, Hsin Vonn
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 http://psasir.upm.edu.my/id/eprint/30330/
http://psasir.upm.edu.my/id/eprint/30330/
http://psasir.upm.edu.my/id/eprint/30330/
http://psasir.upm.edu.my/id/eprint/30330/1/Genetic%20algorithm%20for%20biobjective%20urban%20transit%20routing%20problem.pdf