GA-QP Model to Optimize Sewer System Design
Publication: Journal of Environmental Engineering
Volume 135, Issue 1
Abstract
Sanitary sewer systems are fundamental and expensive facilities for controlling water pollution. Optimizing sewer design is a difficult task due to its associated hydraulic and mathematical complexities. Therefore, a genetic algorithm (GA) based approach has been developed. A set of diameters for all pipe segments in a sewer system is regarded as a chromosome for the proposed GA model. Hydraulic and topographical constraints are adopted in order to eliminate inappropriate chromosomes, thereby improving computational efficiency. To improve the solvability of the proposed model, the nonlinear cost optimization model is approximated and transformed into a quadratic programming (QP) model. The system cost, pipe slopes, and pipe buried depths of each generated chromosome are determined using the QP model. A sewer design problem cited in literature has been solved using the GA-QP model. The solution obtained from the GA model is comparable to that produced by the discrete differential dynamic programming approach. Finally, several near-optimum designs produced using the modeling to generate alternative approach are discussed and compared for improving the final design decision.
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Acknowledgments
The writers would like to thank the National Science Council, R.O.C., for providing partial financial support of this research under Grant No. UNSPECIFIEDNSC94-2211-E-009-010.
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Information & Authors
Information
Published In
Journal of Environmental Engineering
Volume 135 • Issue 1 • January 2009
Pages: 17 - 24
Copyright
© 2009 ASCE.
History
Received: Aug 20, 2007
Accepted: Jun 20, 2008
Published online: Jan 1, 2009
Published in print: Jan 2009
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