Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/65651
DC FieldValue
dc.titleGenetic-algorithm programming of road maintenance and rehabilitation
dc.contributor.authorFwa, T.F.
dc.contributor.authorChan, W.T.
dc.contributor.authorTan, C.Y.
dc.date.accessioned2014-06-17T08:19:09Z
dc.date.available2014-06-17T08:19:09Z
dc.date.issued1996-05
dc.identifier.citationFwa, T.F., Chan, W.T., Tan, C.Y. (1996-05). Genetic-algorithm programming of road maintenance and rehabilitation. Journal of Transportation Engineering 122 (3) : 246-253. ScholarBank@NUS Repository.
dc.identifier.issn0733947X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/65651
dc.description.abstractThis paper describes the development of a computer model (known as PAVENET-R) based on genetic algorithms, an optimization tool capable of overcoming combinatorial explosion, to solve the pavement maintenance-rehabilitation trade-off problem at the network level. The formulation of the PAVENET-R model is described in detail. An integer coding scheme is selected for parameter representation in the model. Two genetic-algorithm operators, namely the crossover operator and the mutation operator, are used. A change table encodes constraints to the genetic-algorithm operations to ensure that only valid offspring are generated from a parent pool. Four numerical examples of road networks of 30 pavement segments, each with different relative costs of rehabilitation and maintenance activities, are analyzed to demonstrate the trade-off relationship between pavement rehabilitation and maintenance activities. The detailed maintenance and rehabilitation schedules of the solutions, and the convergence characteristics of each solution are presented.
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCIVIL ENGINEERING
dc.description.sourcetitleJournal of Transportation Engineering
dc.description.volume122
dc.description.issue3
dc.description.page246-253
dc.identifier.isiutNOT_IN_WOS
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