Harmony Search Optimization: Application to Pipe Network Design

Abstract The Pipe network design problem is considered by choosing least-cost diameter pipes to satisfy flow demands and minimum head restrictions. Harmony and innovation are brought together as in music to devise a search pattern that can identify a large number of local optima in pipe network design. Improvization is brought in by varying the pitch rate parameter, and harmony is maintained by accumulating improving solutions. Because in pipe networks optimization by its very nature removes any redundancy, a minimum power loss criterion is introduced to enhance feasibility. The efficacy of the algorithm is demonstrated by solving a test nonlinear program and a pipe network problem from the literature to global optimum. Several near-optimal solutions are reported.

[1]  A. Simpson,et al.  An Improved Genetic Algorithm for Pipe Network Optimization , 1996 .

[2]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

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

[4]  Andrew B. Templeman,et al.  Discussion of Optimization of Looped Water Distribution Systems by Gerald E. Quindry, Jon C. Liebman and E. Downey Brill , 1982 .

[5]  Graeme C. Dandy,et al.  Genetic algorithms compared to other techniques for pipe optimization , 1994 .

[6]  U. Shamir,et al.  Analysis of the linear programming gradient method for optimal design of water supply networks , 1989 .

[7]  L. Mays,et al.  Hydrosystems engineering and management , 1991 .

[8]  Abdollah Homaifar,et al.  Constrained Optimization Via Genetic Algorithms , 1994, Simul..

[9]  I. G. Nidekker,et al.  Selected applications of non-linear programming: J. Bracken and G. P. McCormick, John Wiley, New York — London — Sydney — Toronto. XII + 110 pp., 84 sh. 1968☆ , 1969 .

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

[11]  G. Loganathan,et al.  Design Heuristic for Globally Minimum Cost Water-Distribution Systems , 1995 .

[12]  David E. Goldberg,et al.  Genetic Algorithms in Pipeline Optimization , 1987 .

[13]  David B. Fogel,et al.  A Comparison of Evolutionary Programming and Genetic Algorithms on Selected Constrained Optimization Problems , 1995, Simul..

[14]  I. Goulter,et al.  Implications of Head Loss Path Choice in the Optimization of Water Distribution Networks , 1986 .

[15]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[16]  Hanif D. Sherali,et al.  Enhanced lower bounds for the global optimization of water distribution networks , 1998 .

[17]  David Mautner Himmelblau,et al.  Applied Nonlinear Programming , 1972 .

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

[19]  David Karmeli,et al.  Design of Optimal Water Distribution Networks , 1968 .