Ant Colony Optimization for Design of Water Distribution Systems
Publication: Journal of Water Resources Planning and Management
Volume 129, Issue 3
Abstract
During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the optimal design and operation of water distribution systems. More recently, ant colony optimization algorithms (ACOAs), which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to a number of benchmark combinatorial optimization problems. In this paper, a formulation is developed which enables ACOAs to be used for the optimal design of water distribution systems. This formulation is applied to two benchmark water distribution system optimization problems and the results are compared with those obtained using genetic algorithms (GAs). The findings of this study indicate that ACOAs are an attractive alternative to GAs for the optimal design of water distribution systems, as they outperformed GAs for the two case studies considered both in terms of computational efficiency and their ability to find near global optimal solutions.
Get full access to this article
View all available purchase options and get full access to this article.
References
Abbaspour, K. C., Schulin, R., and van Genuchten, M. T.(2001). “Estimating unsaturated soil hydraulic parameters using ant colony optimization.” Adv. Water Resour., 24(8), 827–933.
Bonabeau, E., Dorigo, M., and Theraulaz, G.(2000). “Inspiration for optimization from social insect behaviour.” Nature (London), 406, 39–42.
Bonabeau, E., and Theraulaz, G.(2000). “Swarm ants.” Sci. Am., 282(3), March72–79.
Brater, E. F., and King, H. W. (1976). Handbook of hydraulics for the solution of hydraulic engineering problems, McGraw-Hill, New York.
Dandy, G. C., Simpson, A. R., and Murphy, L. J.(1996). “An improved genetic algorithm for pipe network optimization.” Water Resour. Res., 32(2), 449–458.
Dorigo, M., Bonabeau, E., and Theraulaz, G.(2000). “Ant algorithms and stigmergy.” Future Generation Comput. Systems, 16, 851–871.
Dorigo, M., and Di Caro, G. (1999). “The ant colony optimization meta-heuristic.” New ideas in optimization, D. Corne, M. Dorigo, and F. Glover, eds., McGraw-Hill, London, 11–32.
Dorigo, M., and Gambardella, L. M.(1997). “Ant colonies for the travelling salesman problem.” BioSystems, 43, 73–81.
Dorigo, M., Maniezzo, V., and Colorni, A.(1996). “The ant system: optimization by a colony of cooperating ants.” IEEE Trans. Syst. Man Cybern., 26, 29–42.
Goldberg, D. E., and Kuo, C. H.(1987). “Genetic algorithms in pipeline optimization.” J. Comput. Civ. Eng., 1(2), 128–141.
Halhal, D., Walters, G. A., Ouazar, D., and Savic, D. A.(1997). “Water network rehabilitation with structured messy genetic algorithm.” J. Water Resour. Plan. Manage., 123(3), 137–146.
Lippai, I., Heany, J. P., and Laguna, M.(1999). “Robust water system design with commercial intelligent search optimizers.” J. Comput. Civ. Eng., 13(3), 135–143.
Morgan, D. R., and Goulter, I. C.(1985). “Optimal urban water distribution design.” Water Resour. Res., 21(5), 642–652.
Murphy, L. J., Simpson, A. R., and Dandy, G. C.(1993). “Design of a pipe network using genetic algorithms.” Water, 20(4), August, 40–42.
Savic, D. A., and Walters, G. A.(1997). “Genetic algorithms for least-cost design of water distribution networks.” J. Water Resour. Plan. Manage., 123(2), 67–77.
Schaake, J. C., and Lai, D. (1969). “Linear programming and dynamic programming applications to water distribution network design.” Rep. No. 116, Hydrodynamics Laboratory, MIT, Cambridge, Mass.
Simpson, A. R., Dandy, G. C., and Murphy, L. J.(1994). “Genetic algorithms compared to other techniques for pipe optimization.” J. Water Resour. Plan. Manage., 120(4), 423–443.
Simpson, A. R., and Goldberg, D. E. (1994). “Pipeline optimization via genetic algorithms: From theory to practice.” Proc., 2nd Int. Conf. on Pipeline Systems, Edinburgh, Scotland, May, 309–320.
Simpson, A. R., Maier, H. R., Foong, W. K., Phang, K. Y., Seah, H. Y., and Tan, C. L. (2001). “Selection of parameters for ant colony optimisation applied to the optimal design of water distribution systems.” Proc., Int. Congress on Modelling and Simulation, Canberra, Australia, 1931–1936.
Stützle, T., and Hoos, H. H.(2000). “MAX-MIN ant system.” Future Generation Comput. Systems, 16, 889–914.
Wu, Z. Y., Boulos, P. F., Orr, C. H., and Ro, J. J.(2001). “Using genetic algorithms to rehabilitate distribution systems.” J. Am. Water Works Assoc., 93(11), 74–85.
Wu, Z. Y., and Simpson, A. R.(2001). “Competent genetic-evolutionary optimization of water distribution systems.” J. Comput. Civ. Eng., 15(2), 89–101.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 129 • Issue 3 • May 2003
Pages: 200 - 209
Copyright
Copyright © 2003 American Society of Civil Engineers.
History
Received: Jan 22, 2001
Accepted: Apr 19, 2002
Published online: Apr 15, 2003
Published in print: May 2003
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.