Optimal water distribution network design with improved particle swarm optimisation
by Jun-Fei Qiao, Yu-Fang Wang, Wei Chai, Lin-Bo Sun
International Journal of Computational Science and Engineering (IJCSE), Vol. 6, No. 1/2, 2011

Abstract: Water distribution network optimisation is highly complex and possesses non-linear relationship of the problem variables, cascading nature of hydraulic network that make the problem of finding global optimum difficulty using standard optimisation methods. An improved particle swarm optimisation (IPSO) algorithm is presented to overcome the drawback that the basic particle swarm optimisation (PSO) algorithm is easy to fall into local optimal solutions in the optimal design of water distribution network. The procedure of optimisation is divided into two phases and searched by PSO with extremum disturbed arithmetic operator and differential evolution (DE) respectively. Extremum disturbed PSO accelerates the particles to overstep the local extremum and DE keeps the diversity of population, with two swarms exchanging information in each iteration to avoid local optimum and reduce iterations. Water distribution networks are designed by improved particle swarm algorithm to achieve the goal of lowest cost of network. Application results show that IPSO reduces the cost of network with rapid convergence rate and strong global searching ability.

Online publication date: Wed, 18-Mar-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com