Optimization Of Pump Operations In A Complex Water Supply Network: New Genetic Algorithm Frameworks

In previous papers, a simple genetic algorithm (GA) was developed for the optimization of pump operations in water-distribution networks. Its application at the water supply network of Milano showed the possibility of a great improvement of its performance in terms of both energy and economic savings. In the present paper is now investigated the possibility of using different and improved GAs to obtain better results. Improvements concerned the description of the pump conditions with a real number (and therefore in continuous form) and the introduction of elitism and of a slightly modified form of mutation. Simulations were obviously performed with reference to the same model under the same assumptions of the previous papers. Results showed significant improvements in the passage from a discrete to a continuous description of the pumps functioning and a slight improvement using elitism and no differences using mutation. The latter result might need some more research: mutation is introduced to enlarge the space in which the ‘individuals’ perform their search, and there is the need to understand whether this little improvement is due to the poor performance of this mutation or instead, because the space of search is already well defined. The need for more in-depth investigations is also investigated in the present paper.

[1]  John H. Holland,et al.  Outline for a Logical Theory of Adaptive Systems , 1962, JACM.

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

[3]  Hans-Paul Schwefel,et al.  Numerical Optimization of Computer Models , 1982 .

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

[5]  Ingo Rechenberg,et al.  Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .

[6]  T. Devi Prasad,et al.  Multiobjective Genetic Algorithms for Design of Water Distribution Networks , 2004 .

[7]  Elad Salomons,et al.  Development of a real-time, near-optimal control process for water-distribution networks , 2006 .

[8]  Stefano Mambretti Optimization of the pumping station of the Milano water supply network with Genetic Algorithms. , 2011 .

[9]  Jakobus E. van Zyl,et al.  Operational Optimization of Water Distribution Systems using a Hybrid Genetic Algorithm , 2004 .

[10]  Morad Behandish,et al.  Concurrent Pump Scheduling and Storage Level Optimization Using Meta-Models and Evolutionary Algorithms , 2017, ArXiv.

[11]  R. Farmani,et al.  Evolutionary multi-objective optimization in water distribution network design , 2005 .

[12]  Slobodan P. Simonovic,et al.  Evolutionary Algorithm for Minimization of Pumping Cost , 1998 .

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

[14]  D. B. Khang,et al.  A two‐phase decomposition method for optimal design of looped water distribution networks , 1990 .

[15]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[16]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .

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

[18]  E. Hansen Numerical Optimization of Computer Models (Hans-Paul Schwefel) , 1983 .

[19]  Hong-Sen Yan,et al.  Kinematic optimization of ball-screw transmission mechanisms , 2007 .

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

[21]  Godfrey A. Walters,et al.  Application of genetic algorithms to pump scheduling for water supply , 1995 .

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