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International Conference on Evolutionary Multi-Criterion Optimization

EMO 2005: Evolutionary Multi-Criterion Optimization pp 736–751Cite as

A Two-Level Evolutionary Approach to Multi-criterion Optimization of Water Supply Systems

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 3410)

Abstract

Purpose of the paper is to introduce a methodology for a parameter-free multi-criterion optimization of water distribution networks. It is based on a two-level approach, with a population of inner multi-objective genetic algorithms (MOGAs) and an outer simple GA (without crossover). The inner MOGAs represent the network optimizers, while the outer GA – the meta GA – is a supervisor process adapting mutation and crossover probabilities of the inner MOGAs. The hypervolume metric has been adopted as fitness for the individuals at the meta-level. The methodology has been applied to a small system often studied in the literature, for which an exhaustive search of the entire decision space has allowed the determination of all Pareto-optimal solutions of interest: the choice of this simple system was done in order to compare the hypervolume metric to two performance measures (a convergence and a sparsity index) introduced on purpose. Simulations carried out show how the proposed procedure proves robust, giving better results than a MOGA alone, thus allowing a considerable ease in the network optimization process.

Keywords

  • Pareto Front
  • Water Distribution System
  • Water Resource Research
  • Water Distribution Network
  • Water Resource Planning

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Dipartimento di Georisorse e Territorio, University of Udine, via Cotonificio 114, 33100, Udine, Italy

    Matteo Nicolini

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  1. Matteo Nicolini
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Editors and Affiliations

  1. Departamento de Computación, CINVESTAV-IPN (Evolutionary Computation Group), 07300, México, D.F., México

    Carlos A. Coello Coello

  2. Centro de Investigación en Matemáticas (CIMAT), A.P. 402, Guanajuato, 36000, Mexico

    Arturo Hernández Aguirre

  3. Computer Engineering and Networks Laboratory, ETH, Zurich, Switzerland

    Eckart Zitzler

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Nicolini, M. (2005). A Two-Level Evolutionary Approach to Multi-criterion Optimization of Water Supply Systems. In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds) Evolutionary Multi-Criterion Optimization. EMO 2005. Lecture Notes in Computer Science, vol 3410. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31880-4_51

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  • DOI: https://doi.org/10.1007/978-3-540-31880-4_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24983-2

  • Online ISBN: 978-3-540-31880-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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