Optimal Design of Water Distribution Systems Using Genetic Algorithms

This article proposes an optimal design methodology for the design of water distribution systems based on genetic algorithms. The objective of the optimization is to minimize the capital cost, subject to ensuring adequate pressures at all nodes. The proposed method differs from those of previous wor...

Full description

Saved in:
Bibliographic Details
Published inComputer-aided civil and infrastructure engineering Vol. 15; no. 5; pp. 374 - 382
Main Authors Vairavamoorthy, Kalanithy, Ali, Mohammed
Format Journal Article
LanguageEnglish
Published Boston, USA and Oxford, UK Blackwell Publishers Inc 01.09.2000
Blackwell
Subjects
Online AccessGet full text
ISSN1093-9687
1467-8667
DOI10.1111/0885-9507.00201

Cover

More Information
Summary:This article proposes an optimal design methodology for the design of water distribution systems based on genetic algorithms. The objective of the optimization is to minimize the capital cost, subject to ensuring adequate pressures at all nodes. The proposed method differs from those of previous workers who have applied genetic algorithms in that the strings in the genetic algorithm model are coded using real variables, and this avoids the problem of redundant states often found when using binary (and Gray) coding schemes. A fitness function is also proposed that incorporates a variable penalty coefficient that depends on the degree of violation of the pressure constraints. The method also differs from those of previous workers in that it does not require solution of the nonlinear equations governing the flows and pressures in the distribution system for each individual member within the population. Hence this method shows a significant advantage compared with previously published techniques in terms of computational efficiency. The method has been tested on several networks, including networks used for benchmark testing least‐cost design algorithms, and has been shown to be very efficient and robust.
Bibliography:ark:/67375/WNG-B1452XTW-5
ArticleID:MICE201
istex:3DC9908CFEDDC3807C3BBC40EEDA611FA7D617EA
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1093-9687
1467-8667
DOI:10.1111/0885-9507.00201