This paper outlines a multi-objective genetic algorithm methodology for the design of a water distribution network. In order to obtain the Pareto-front, the objectives: minimization of network cost and maximization of a reliability measure are considered. A new reliability measure, called network resilience, is introduced. This measure tries to provide (i) surplus head above the minimum allowable head at nodes and (ii) reliable loops with practicable pipe diameters. A set of Pareto-optimal solutions is obtained in the search space of cost and network resilience. Genetic algorithms are observed to be poor in handling constraints. To handle constraints in a better way, a constraint handling technique that does not require a penalty coefficient and applicable to water distribution systems is presented. The present model is applied to two example problems, which were widely reported. Comparison of the results has revealed that the network resilience based approach gave better results.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Reliability based design of water distribution networks using multi-objective genetic algorithms


    Additional title:

    KSCE J Civ Eng


    Contributors:

    Published in:

    Publication date :

    2003-05-01


    Size :

    11 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Multi-objective and constrained design of gratings using genetic algorithms

    Poladian, L. / Manos, S. / Ashton, B. | IEEE | 2005



    Piston design using multi-objective reliability-based design optimization

    Patel,P. / Mourelatos,Z.P. / Shah,P. et al. | Automotive engineering | 2010


    Piston Design Using Multi-Objective Reliability-Based Design Optimization

    Shah, Paras / Patel, Prashant / Mourelatos, Zissimos P. | SAE Technical Papers | 2010


    Inverse Design Optimization of Transonic Wings Based on Multi-Objective Genetic Algorithms

    Shinichi Takahashi / Shigeru Obayashi / Kazuhiro Nakahashi | AIAA | 1999