Picture map of Europe with pins indicating European capital cities

Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

Explore research outputs by the European Policies Research Centre...

Penalty-free evolutionary algorithm optimization for the long term rehabilitation and upgrading of water distribution systems

Siew, Calvin and Tanyimboh, Tiku (2011) Penalty-free evolutionary algorithm optimization for the long term rehabilitation and upgrading of water distribution systems. In: Proceedings of the ASCE/EWRI World Environmental & Water Resources Congress. American Society of Civil Engineers. ISBN 978‐0‐7844‐1173‐5

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

The rehabilitation and upgrading of a water distribution system (WDS) involves a great amount of capital and hence the optimization of factors such as the phasing, timing and magnitude of the upgrading with regard to cost is a necessity. This paper presents a penalty‐free multi‐objective evolutionary algorithm (PFMOEA) model for the optimal long term upgrading of water distribution systems. The model couples a pressure dependent analysis within a multi‐objective optimization frame work and has proven to be effective and efficient in locating the optimal/ near optimal solution. Herein, a real life network in Wobulenzi was used to demonstrate the efficacy of the model. Results generated by PFMOEA and the conventional linear programming (LP) are presented and compared. It is shown that PFMOEA outperforms LP in that it succeeded in finding lower network rehabilitation and upgrading cost.