Harmony search optimisation to the pump-included water distribution network design

This work is to present an optimisation model for the design of water distribution networks which include pumps. Pump-included water distribution networks have not been featured in the literature of hydrosystems optimisation as often as simple gravity-based water networks, which have gained popularity in the optimisation field. The optimisation model for the pump-included water network uses a music-inspired evolutionary algorithm, harmony search (HS), which mimics a music improvisation process in order to find better design solutions. Use of HS would obtain better results in terms of average design cost, number of function evaluations, and hydraulic simulation condition as compared to those of another evolutionary algorithm, simulated annealing.

[1]  Angus R. Simpson,et al.  Genetic algorithms compared to other techniques for pipe optimization , 1994 .

[2]  Mehmet Polat Saka,et al.  Optimum Geometry Design of Geodesic Domes Using Harmony Search Algorithm , 2007 .

[3]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[4]  S. O. Degertekin.  Optimum design of steel frames using harmony search algorithm , 2008 .

[5]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[6]  U. Shamir,et al.  Design of optimal water distribution systems , 1977 .

[7]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[8]  Maria da Conceição Cunha,et al.  Water Distribution Network Design Optimization: Simulated Annealing Approach , 1999 .

[9]  Zong Woo Geem,et al.  Novel derivative of harmony search algorithm for discrete design variables , 2008, Appl. Math. Comput..

[10]  M. Tamer Ayvaz,et al.  Simultaneous determination of aquifer parameters and zone structures with fuzzy c-means clustering and meta-heuristic harmony search algorithm , 2007 .

[11]  Kenneth Alan De Jong,et al.  An analysis of the behavior of a class of genetic adaptive systems. , 1975 .

[12]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[13]  K. Lee,et al.  The harmony search heuristic algorithm for discrete structural optimization , 2005 .

[14]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[15]  François Pachet,et al.  Constraints and Multimedia , 1999 .

[16]  Z. Geem.  Optimal cost design of water distribution networks using harmony search , 2006 .

[17]  K. Lee,et al.  A new structural optimization method based on the harmony search algorithm , 2004 .

[18]  Maria da Conceição Cunha,et al.  Hydraulic infrastructures design using simulated annealing , 2001 .

[19]  F. Glover.  HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS , 1977 .

[20]  Zong Woo Geem,et al.  Harmony Search in Water Pump Switching Problem , 2005, ICNC.

[21]  James P. Heaney,et al.  Robust Water System Design with Commercial Intelligent Search Optimizers , 1999 .

[22]  Zong Woo Geem,et al.  Optimal Scheduling of Multiple Dam System Using Harmony Search Algorithm , 2007, IWANN.

[23]  André L.H. Costa,et al.  Optimization of pipe networks including pumps by simulated annealing , 2000 .

[24]  Z. Geem.  Optimal Design of Water Distribution Networks Using Harmony Search , 2009 .

[25]  Z. Geem,et al.  PARAMETER ESTIMATION OF THE NONLINEAR MUSKINGUM MODEL USING HARMONY SEARCH 1 , 2001 .

[26]  Zong Woo Geem,et al.  Application of Harmony Search to Vehicle Routing , 2005 .

[27]  Dragan Savic,et al.  Genetic Algorithms for Least-Cost Design of Water Distribution Networks , 1997 .