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Design of Water Distribution Networks using a Pseudo-Genetic Algorithm and Sensitivity of Genetic Operators

Author

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  • D. Mora-Melia
  • P. Iglesias-Rey
  • F. Martinez-Solano
  • V. Fuertes-Miquel

Abstract

Genetic algorithms (GA) are optimization techniques that are widely used in the design of water distribution networks. One of the main disadvantages of GA is positional bias, which degrades the quality of the solution. In this study, a modified pseudo-genetic algorithm (PGA) is presented. In a PGA, the coding of chromosomes is performed using integer coding; in a traditional GA, binary coding is utilized. Each decision variable is represented by only one gene. This variation entails a series of special characteristics in the definition of mutation and crossover operations. Some benchmark networks have been used to test the suitability of a PGA for designing water distribution networks. More than 50,000 simulations were conducted with different sets of parameters. A statistical analysis of the obtained solutions was also performed. Through this analysis, more suitable values of mutation and crossover probabilities were discovered for each case. The results demonstrate the validity of the method. Optimum solutions are not guaranteed in any heuristic method. Hence, the concept of a “good solution” is introduced. A good solution is a design solution that does not substantially exceed the optimal solution that is obtained from the simulations. This concept may be useful when the computational cost is critical. The main conclusion derived from this study is that a proper combination of population and crossover and mutation probabilities leads to a high probability that good solutions will be obtained. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • D. Mora-Melia & P. Iglesias-Rey & F. Martinez-Solano & V. Fuertes-Miquel, 2013. "Design of Water Distribution Networks using a Pseudo-Genetic Algorithm and Sensitivity of Genetic Operators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(12), pages 4149-4162, September.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:12:p:4149-4162
    DOI: 10.1007/s11269-013-0400-6
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    References listed on IDEAS

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    1. Sara Nazif & Mohammad Karamouz & Massoud Tabesh & Ali Moridi, 2010. "Pressure Management Model for Urban Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(3), pages 437-458, February.
    2. Mohamed Louati & Sihem Benabdallah & Fethi Lebdi & Darko Milutin, 2011. "Application of a Genetic Algorithm for the Optimization of a Complex Reservoir System in Tunisia," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(10), pages 2387-2404, August.
    3. J. Reca & J. Martínez & C. Gil & R. Baños, 2008. "Application of Several Meta-Heuristic Techniques to the Optimization of Real Looped Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1367-1379, October.
    4. Milan Cisty, 2010. "Hybrid Genetic Algorithm and Linear Programming Method for Least-Cost Design of Water Distribution Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(1), pages 1-24, January.
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    Cited by:

    1. Shiono, Naoshi & Suzuki, Hisatoshi, 2016. "Optimal pipe-sizing problem of tree-shaped gas distribution networks," European Journal of Operational Research, Elsevier, vol. 252(2), pages 550-560.
    2. Zhang, Yang & Andrews, John & Reed, Sean & Karlberg, Magnus, 2017. "Maintenance processes modelling and optimisation," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 150-160.
    3. Jimmy H. Gutiérrez-Bahamondes & Daniel Mora-Melia & Bastián Valdivia-Muñoz & Fabián Silva-Aravena & Pedro L. Iglesias-Rey, 2023. "Infeasibility Maps: Application to the Optimization of the Design of Pumping Stations in Water Distribution Networks," Mathematics, MDPI, vol. 11(7), pages 1-16, March.
    4. Hossein Fallah & Ozgur Kisi & Sungwon Kim & Mohammad Rezaie-Balf, 2019. "A New Optimization Approach for the Least-Cost Design of Water Distribution Networks: Improved Crow Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3595-3613, August.
    5. D. Mora-Melia & P. Iglesias-Rey & F. Martinez-Solano & P. Ballesteros-Pérez, 2015. "Efficiency of Evolutionary Algorithms in Water Network Pipe Sizing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(13), pages 4817-4831, October.
    6. Mohammad Rahimi & Ali Haghighi, 2015. "A Graph Portioning Approach for Hydraulic Analysis-Design of Looped Pipe Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5339-5352, November.
    7. Sheyda Bahoosh & Reza Bahoosh & Ali Haghighi, 2019. "Development of a Self-Adaptive Ant Colony Optimization for Designing Pipe Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4715-4729, November.

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