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Urban bus transit route network design using genetic algorithm
Published in ASCE, Reston, VA, United States
1998
Volume: 124
   
Issue: 4
Pages: 368 - 375
Abstract
Urban bus route network design involves determining a route configuration with a set of transit routes and associated frequencies that achieves the desired objective. This can be formulated as an optimization problem of minimizing the overall cost (both the user's and the operator's) incurred. In this paper, the use of genetic algorithms (GAs), a search and optimization method based on natural genetics and selection, in solving the route network design problem is reported. The design is done in two phases. First, a set of candidate routes competing for the optimum solution is generated. Second, the optimum set is selected using a GA. The GA is solved by adopting the usual fixed string length coding scheme along with a new variable string length coding proposed in this study. The former assumes a solution route set size, and tries to find that many best routes from the candidate route set, using a GA. The route set size is varied iteratively to find the optimum solution. In the newly proposed variable string length coding method, the solution route set size and the set of solution routes are found simultaneously. The model is applied to a case study network, and results are presented.Urban bus route network design involves determining a route configuration with a set of transit routes and associated frequencies that achieves the desired objective. This can be formulated as an optimization problem of minimizing the overall cost (both the user's and the operator's) incurred. In this paper, the use of genetic algorithms (GAs), a search and optimization method based on natural genetics and selection, in solving the route network design problem is reported. The design is done in two phases. First, a set of candidate routes competing for the optimum solution is generated. Second, the optimum set is selected using a GA. The GA is solved by adopting the usual fixed string length coding scheme along with a new variable string length coding proposed in this study. The former assumes a solution route set size, and tries to find that many best routes from the candidate route set, using a GA. The route set size is varied iteratively to find the optimum solution. In the newly proposed variable string length coding method, the solution route set size and the set of solution routes are found simultaneously. The model is applied to a case study network, and results are presented.
About the journal
JournalJournal of Transportation Engineering
PublisherASCE, Reston, VA, United States
ISSN0733947X
Open AccessNo
Concepts (14)
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    Computer simulation
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    Genetic algorithms
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    Highway traffic control
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    Optimization
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    Transportation routes
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    ROUTE CONFIGURATION
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    URBAN BUS ROUTE NETWORK
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    Bus transportation
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    BUS TRANSPORT
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    Genetic algorithm
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    Planning method
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    ROUTE NETWORK
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    Traffic management
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    TRANSPORT PLANNING