Ant colony optimization for water distribution network design: a comparative study

  • Authors:

  • C. Gil;R. Baños;J. Ortega;A. L. Márquez;A. Fernández;M. G. Montoya

  • Affiliations:

  • Dept. Arquitectura de Computadores y Electrónica, Universidad de Almería, Almería, Spain;Dept. Arquitectura de Computadores y Electrónica, Universidad de Almería, Almería, Spain;Dept. Arquitectura y Tecnología de Computadores, Universidad de Granada, Granada, Spain;Dept. Arquitectura de Computadores y Electrónica, Universidad de Almería, Almería, Spain;Dept. Arquitectura de Computadores y Electrónica, Universidad de Almería, Almería, Spain;Dept. Arquitectura de Computadores y Electrónica, Universidad de Almería, Almería, Spain

  • Venue:
  • IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
  • Year:
  • 2011

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Abstract

The optimal design of looped water distribution networks is a major environmental and economic problem with applications in urban, industrial and irrigation water supply. Traditionally, this complex problem has been solved by applying single-objective constrained formulations, where the goal is to minimize the network investment cost subject to pressure constraints. In order to solve this highly complex optimization problem some authors have therefore proposed using heuristic techniques for their solution. Ant Colony Optimization (ACO) is a metaheuristic that uses strategies inspired by real ants to solve optimization problems. This paper presents and evaluates the performance of a new ACO implementation specially designed to solve this problem, which results in two benchmark networks outperform those obtained by genetic algorithms and scatter search.