Genetic-Algorithm Programming of Road Maintenance and Rehabilitation
Publication: Journal of Transportation Engineering
Volume 122, Issue 3
Abstract
This 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.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 122 • Issue 3 • May 1996
Pages: 246 - 253
Copyright
Copyright © 1996 American Society of Civil Engineers.
History
Published online: May 1, 1996
Published in print: May 1996
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