Title: Optimal water distribution network design with improved particle swarm optimisation

Authors: Jun-Fei Qiao, Yu-Fang Wang, Wei Chai, Lin-Bo Sun

Addresses: Intelligent Systems Institute, College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China. ' Intelligent Systems Institute, College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China. ' Intelligent Systems Institute, College of Electronic and Control Engineering, Beijing University of Technology, Beijing, 100124, China. ' Everbright Water Treatment (Jinan) Co., Ltd., No. 1995, Huang Gang Road, Tianqiao District of Jinan City, Shandong, China

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.

Keywords: improved PSO; particle swarm optimisation; IPSO; optimisation design; water distribution networks; WDN; extremum disturbed PSO; differential evolution.

DOI: 10.1504/IJCSE.2011.041210

International Journal of Computational Science and Engineering, 2011 Vol.6 No.1/2, pp.34 - 42

Published online: 13 Jul 2011 *

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