Chapter
Apr 26, 2012
Multiscale Strategies for Solving Water Resources Management Problems with Genetic Algorithms
Authors: Meghna Babbar and Barbara MinskerAuthor Affiliations
Publication: World Water & Environmental Resources Congress 2003
Abstract
Genetic Algorithms (GAs) face major computational bottlenecks when numerical models are used for estimating the fitness of the objective function. Especially in large-scale water resources design problems, where the scale of the spatial grids is important in determining the numerical accuracy of the design, a tradeoff exists in the precision of the fitness function and the computational expenses endured. This paper discusses multiscale strategies that can be utilized for improving the performance of GAs when working with spatial grid dependant fitness functions. The strategy uses fine grid and coarse grid fitness functions strategically to maintain the accuracy and computational speed of the problem and drive the GA towards better and more accurate solutions faster. The algorithm's efficacy is tested using a groundwater remediation design case study.
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© 2003 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
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ASCE Technical Topics:
- Algorithms
- Case studies
- Design (by type)
- Engineering fundamentals
- Freight transportation
- Grid systems
- Hydraulic design
- Infrastructure
- Logistics
- Mathematics
- Methodology (by type)
- Models (by type)
- Numerical models
- Research methods (by type)
- Resource management
- Systems engineering
- Systems management
- Transportation engineering
- Water and water resources
- Water management
- Water policy
- Water resources
Authors
Affiliations
Meghna Babbar
Department of Civil and Environmental Engineering, University of Illinois at Urbana Champaign, Urbana, IL 61801
Barbara Minsker
Department of Civil and Environmental Engineering, University of Illinois at Urbana Champaign, Urbana, IL 61801
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