Assessment of penalty-free multi-objective evolutionary optimization approach for the design and rehabilitation of water distribution systems

Siew, Calvin and Tanyimboh, Tiku and Seyoum, Alemtsehay Gebremeskel (2014) Assessment of penalty-free multi-objective evolutionary optimization approach for the design and rehabilitation of water distribution systems. Water Resources Management, 28 (2). pp. 373-389. ISSN 0920-4741 (https://doi.org/10.1007/s11269-013-0488-8)

[thumbnail of Siew_Tanyimboh_Seyoum-WARM-2014]
Preview
PDF. Filename: Siew_Tanyimboh_Seyoum_WARM_2014.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (459kB)| Preview

Abstract

This paper describes a penalty-free multi-objective evolutionary optimization approach for the phased whole-life design and rehabilitation of water distribution systems. The optimization model considers the initial construction, rehabilitation and upgrading costs. Repairs and pipe failure costs are included. The model also takes into consideration the deterioration over time of both the structural integrity and hydraulic capacity of every pipe. The fitness of each solution is determined from the trade-off between its lifetime costs and its actual hydraulic properties. The hydraulic analysis approach used, known as pressure-dependent modelling, considers explicitly the pressure dependency of the water supply consumers receive. Results for two sample networks in the literature are included that show the algorithm is stable and finds optimal and near-optimal solutions reliably and efficiently. The results also suggest that the evolutionary sampling efficiency is very high. In other words, the number of solutions evolved and analysed on average before finding a near-optimal solution is small in comparison to the total number of feasible and infeasible solutions. We found better solutions than those reported previously in the literature for the two networks considered. For the Kadu network, for example, the new best solution costs Rs125,460,980 – a significant improvement. Additional statistics that are based on extensive testing are included.