A Pareto-based memetic algorithm for optimization of looped water distribution systems

Looped water distribution networks have traditionally been used in urban and industrial water supply. Nowadays, they are also being introduced in certain irrigation water distribution systems, such as in greenhouse horticultural systems. The design of looped networks is a much more complex problem than the design of branched ones, but their greater reliability can compensate for the increase in cost. Most articles found in the literature try to minimize the network investment cost, while other designing objectives are considered as constraints. This article introduces a multi-objective memetic algorithm that simultaneously optimizes the total investment cost, and also the reliability of the network in terms of total surplus power at the demand nodes. This memetic algorithm uses the Pareto-dominance concept to determine the quality of the solutions. The results obtained in two small water supply networks, and a large irrigation water supply network denote the good performance of the memetic algorithm here proposed in comparison with other well known meta-heuristics.

[1]  F. Glover,et al.  In Modern Heuristic Techniques for Combinatorial Problems , 1993 .

[2]  Chengchao Xu,et al.  Reliability-Based Optimal Design of Water Distribution Networks , 2001 .

[3]  Christian Blum,et al.  Metaheuristics in combinatorial optimization: Overview and conceptual comparison , 2003, CSUR.

[4]  Prasad Tumula,et al.  Multi-Objective genetic algorithms for the design of pipe networks. , 2004 .

[5]  D. Aklog,et al.  Reliability-based optimal design of water distribution networks , 2003 .

[6]  J. Periaux,et al.  Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems , 2001 .

[7]  Angus R. Simpson,et al.  Ant Colony Optimization for Design of Water Distribution Systems , 2003 .

[8]  Yuval Davidor,et al.  The Interplay Among the Genetic Algorithm Operators: Information Theory Tools Used in a Holistic Way , 1992, PPSN.

[9]  C. Reeves.  Modern heuristic techniques for combinatorial problems , 1993 .

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

[11]  Li Jianping,et al.  An empirical investigation on elitism in multiobjective genetic algorithms , 2001 .

[12]  Pablo Moscato,et al.  A Gentle Introduction to Memetic Algorithms , 2003, Handbook of Metaheuristics.

[13]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[14]  P. Hajela,et al.  Genetic search strategies in multicriterion optimal design , 1991 .

[15]  Ezio Todini,et al.  Looped water distribution networks design using a resilience index based heuristic approach , 2000 .

[16]  M. R. Rao,et al.  Combinatorial Optimization , 1992, NATO ASI Series.

[17]  Consolación Gil,et al.  Implementation of scatter search for multi-objective optimization: a comparative study , 2009, Comput. Optim. Appl..

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

[19]  R. Lewontin.  ‘The Selfish Gene’ , 1977, Nature.

[20]  Joshua D. Knowles,et al.  Memetic Algorithms for Multiobjective Optimization: Issues, Methods and Prospects , 2004 .

[21]  Dragan Savic,et al.  Trade-off between Total Cost and Reliability for Anytown Water Distribution Network , 2005 .

[22]  Andrzej Jaszkiewicz,et al.  Genetic local search for multi-objective combinatorial optimization , 2022 .

[23]  Muzaffar Eusuff,et al.  Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization , 2006 .

[24]  Pablo Moscato,et al.  On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms , 1989 .

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

[26]  Joshua D. Knowles,et al.  M-PAES: a memetic algorithm for multiobjective optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[27]  William E. Hart,et al.  Recent Advances in Memetic Algorithms , 2008 .

[28]  J. L. Ayuso,et al.  Water distribution network optimization using a modified genetic algorithm , 1999 .

[29]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[30]  Martin J. Oates,et al.  The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation , 2000, PPSN.

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

[32]  S. Narasimhan,et al.  Optimal design of water distribution system using an NLP method , 1997 .

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

[34]  Pablo Moscato,et al.  Handbook of Applied Optimization , 2000 .

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

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

[37]  Consolación Gil,et al.  A Memetic Algorithm for Water Distribution Network Design , 2007 .

[38]  Marco Laumanns,et al.  SPEA2: Improving the Strength Pareto Evolutionary Algorithm For Multiobjective Optimization , 2002 .

[39]  P. Khanna,et al.  Optimization of water distribution system , 1993 .

[40]  Juan Martínez,et al.  Genetic algorithms for the design of looped irrigation water distribution networks , 2006 .

[41]  David Corne,et al.  The Pareto archived evolution strategy: a new baseline algorithm for Pareto multiobjective optimisation , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[42]  K. Srinivasan,et al.  Performance‐based optimal design and rehabilitation of water distribution networks using life cycle costing , 2008 .

[43]  Hisao Ishibuchi,et al.  Effectiveness of Genetic Local Search Algorithms , 1997, ICGA.

[44]  Prabhat Hajela,et al.  Genetic search strategies in multicriterion optimal design , 1991 .