Integer Discrete Particle Swarm Optimization of Water Distribution Networks
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 5, Issue 1
Abstract
The integer discrete particle swarm algorithm is used as an optimization technique for the design of water distribution networks in order to minimize its total cost. Because the particle swarm is highly sensitive to its parameters and boundary conditions, the available restricted boundary conditions are applied. Also, a new boundary condition called the billiard boundary condition is introduced, which does not depend on the velocity clamping that mainly depends on human assumptions. The performance of the boundary conditions are tested under different populations, and a new initialization method by setting the initial position to one side of boundary solutions that is set to the maximum available diameter. The Newton-Raphson method is used as the hydraulic solver. The technique is applied to the optimal design of both the two-loop water distribution network, which is a well-known benchmark in the literature, and to a large-scale previously investigated two-source pipe network. The results show that the application of the integer discrete particle swarm algorithm with the proposed billiard boundary condition and initialization method in the least-cost design of water distribution networks is more effective when compared to others in reducing the pipe cost and the function evaluation number.
Get full access to this article
View all available purchase options and get full access to this article.
References
Abebe, A. J., and Solomatine, D. P. (1998). “Application of global optimization to the design of pipe networks.” Proc., 3rd Int. Conf. on Hydroinformatics, Balkema, Rotterdam, Netherlands.
Afshar, M. H., and Rajabpour, R., (2009). “Application of local and global particle swarm optimization algorithms to optimal design and operation of irrigation pumping systems.” Irrig. Drain., 58(3), 321–331.
Alperovits, E., and Shamir, U. (1977). “Design of optimal water distribution systems.” Water Resour. Res., 13(6), 885–900.
Babu, K. S. J., and Vijayalakshmi, D. P. (2013). “Self-adaptive PSO-GA hybrid model for combinatorial water distribution network design.” J. Pipeline Syst. Eng. Pract., 57–67.
Chandramouli, S., and Malleswararao, P. (2011). “Reliability based optimal design of a water distribution network for municipal water supply.” Int. J. Eng. Technol., 3(1), 13–19.
Cunha, M. D. C., and Sousa, J. (1999). “Water distribution network design optimization: Simulated annealing approach.” J. Water Resour. Plann. Manage., 215–221.
Datta, D., and Figueira, J. R. (2011). “A real-integer-discrete-coded particle swarm optimization for design problems.” Appl. Soft Comput., 11(4), 3625–3633.
Djebedjian, B., Abdel-Gawad, H. A. A., Ezzeldin, R., Yaseen, A., and Rayan, M. A. (2007). “Evaluation of capacity reliability-based and uncertainty-based optimization of water distribution systems.” Proc., 11th Int. Water Technology Conf. (IWTC11), Sharm El-Sheikh, Egypt, 565–587.
Engelbrecht, A. P. (2007). “Particle swarm optimization.” Chapter 16, Computational intelligence: An introduction, Wiley, Chichester, 289–358.
Eusuff, M. M., and Lansey, K. E. (2003). “Optimization of water distribution network design using the shuffled frog leaping algorithm.” J. Water Resour. Plann. Manage., 210–225.
Ezzeldin, R. M. (2007). “Reliability-based optimal design model for water distribution networks.” M.S. thesis, Mansoura Univ., El-Mansoura, Egypt.
Ganjali, A. (2008). “A requirements-based partition testing framework using particle swarm optimization technique.” M.S. thesis, Applied Science in Electrical and Computer Engineering, Univ. of Waterloo, Waterloo, ON, Canada.
Geem, Z. W. (2006). “Optimal cost design of water distribution networks using harmony search.” Eng. Optimiz., 38(3), 259–280.
Iglesias, P. L., Mora, D., Martinez, F. J., and Fuertes, V. S. (2007). “Study of sensitivity of the parameters of a genetic algorithm for design of water distribution networks.” J. Urban Environ. Eng., 1(2), 61–69.
Kadu, M. S., Gupta, R., and Bhave, P. R. (2008). “Optimal design of water networks using a modified genetic algorithm with reduction in search space.” J. Water Resour. Plann. Manage., 147–160.
Kanakoudis, V. K. (2004). “Vulnerability based management of water resources systems.” J. Hydroinf., 6(2), 133–156.
Kanakoudis, V., and Tolikas, D. (2001). “The role of leaks and breaks in water networks—Technical and economical solutions.” J. Water Supply: Res. Technol.-AQUA, 50(5), 301–311.
Kanakoudis, V. K., and Tolikas, D. K. (2004). “Assessing the performance level of a water system.” Water Air Soil Pollut., (4–5), 307–318.
Kennedy, J., and Eberhart, R. (1995). “Particle swarm optimization.” Proc., 1995 IEEE Int. Conf. on Neural Networks, Vol. IV, IEEE Service Center, Piscataway, 1942–1948.
Kennedy, J., and Eberhart, R. (1997). “A discrete binary version of the particle swarm algorithm.” IEEE Conf. on System, Man, and Cybernetics, Vol. 5, IEEE Service Center, Piscataway, 4104–4108.
Larock, B. E., Jeppson, R. W., and Watters, G. Z. (2000). Hydraulics of pipeline systems, CRC Press, Boca Raton.
Li, L. J., Huang, Z. B., and Liu, F. (2009). “A heuristic particle swarm optimization method for truss structures with discrete variables.” Comput. Struct., 87(7–8), 435–443.
Liong, S.-Y., and Atiquzzaman, Md. (2004). “Optimal design of water distribution network using shuffled complex evolution.” J. Inst. Eng., 44(1), 93–107.
Montalvo, I., Izquierdo, J., Pérez, R., and Tung, M. M. (2008). “Particle swarm optimization applied to the design of water supply systems.” Comput. Math. Appl., 56(3), 769–776.
Montalvo, I., Izquierdo, J., Pérez-García, R., and Herrera, M. (2010). “Improved performance of PSO with self-adaptive parameters for computing the optimal design of water supply systems.” Eng. Appl. Artif. Intell., 23(5), 727–735.
Pugh, J., and Martinoli, A. (2006). “Discrete multivalued particle swarm optimization.” Proc., IEEE Swarm Intelligence Symp., Vol. 1, IEEE, New York, 103–110.
Savic, D. A., and Walters, G. A. (1997). “Genetic algorithms for least-cost design of water distribution networks.” J. Water Resour. Plann. Manage., 67–77.
Shi, Y., and Eberhart, R. C. (1998). “A modified particle swarm optimizer.” Proc., 1998 IEEE Int. Conf. on Evolutionary Computation, IEEE Press, Piscataway, 69–73.
Suribabu, C. R. (2010). “Differential evolution algorithm for optimal design of water distribution networks.” J. Hydroinf., 12(1), 66–82.
Suribabu, C. R. (2012). “Heuristic-based pipe dimensioning model for water distribution networks.” J. Pipeline Syst. Eng. Pract., 115–124.
Suribabu, C. R., and Neelakantan, T. R. (2006). “Design of water distribution networks using particle swarm optimization.” Urban Water J., 3(2), 111–120.
Talukder, S. (2011). “Mathematical modeling and applications of particle swarm optimization.” M.S. thesis, Blekinge Institute of Technology, Karlskrona, Sweden.
Xu, S., and Rahamat-Samii, Y. (2007). “Boundary conditions in particle swarm optimization revisited.” IEEE Trans. Antennas Propag., 55(3), 760–765.
Zecchin, A. C., Simpson, A. R., Maier, H. R., and Nixon, J. B. (2005). “Parametric study for an ant algorithm applied to water distribution system optimization.” IEEE Trans. Evol. Comput., 9(2), 175–191.
Information & Authors
Information
Published In
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Aug 24, 2012
Accepted: Jul 24, 2013
Published online: Sep 13, 2013
Published in print: Feb 1, 2014
Discussion open until: Feb 13, 2014
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.