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Water Distribution System Computer‐Aided Design by Agent Swarm Optimization
Author(s) -
Montalvo I.,
Izquierdo J.,
PérezGarcía R.,
Herrera M.
Publication year - 2014
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12062
Subject(s) - computer science , robustness (evolution) , swarm intelligence , mathematical optimization , exploit , multi swarm optimization , particle swarm optimization , sizing , optimization problem , engineering optimization , metaheuristic , multi objective optimization , artificial intelligence , machine learning , algorithm , mathematics , art , biochemistry , chemistry , computer security , visual arts , gene
Optimal design of water distribution systems (WDSs), including the sizing of components, quality control, reliability, renewal, and rehabilitation strategies, etc., is a complex problem in water engineering that requires robust methods of optimization. Classical methods of optimization are not well suited for analyzing highly dimensional, multimodal, nonlinear problems, especially given inaccurate, noisy, discrete, and complex data. Agent Swarm Optimization (ASO) is a novel paradigm that exploits swarm intelligence and borrows some ideas from multiagent‐based systems. It is aimed at supporting decision‐making processes by solving multiobjective optimization problems. ASO offers robustness through a framework where various population‐based algorithms coexist. The ASO framework is described and used to solve the optimal design of WDS. The approach allows engineers to work in parallel with the computational algorithms to force the recruitment of new searching elements, thus contributing to the solution process with expert‐based proposals.

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