Evolutionary algorithms are a commonly applied optimisation approach in water distribution systems. However, the algorithms are time consuming when applied to large optimisation problems. The aim of this paper is to evaluate the application of a penalty-free multi-objective evolutionary optimisation algorithm to solve a real-life network design problem. The optimization model uses pressure-dependent analysis that accounts for the pressure dependency of the nodal flows and thus avoids the need for penalties to address violations of the nodal pressure constraints. The algorithm has been tested previously using benchmark optimisation problems in the literature. In all cases, the algorithm found improved solutions and/or the best solution reported previously in the literature with considerably fewer function evaluations. In this paper, a real-life network with over 250 pipes was considered. The network comprises multiple sources, multiple demand categories, many fire flows and involves extended period simulation. Due to the size and complexity of the optimization problem, a high performance computer that comprises multiple cores was used for the computational solution. Multiple optimisation runs were performed concurrently. Overall, the algorithm performs well; it consistently provides least cost solutions that satisfy all the system requirements quickly. The least-cost design obtained was over 40% cheaper than the existing network in terms of the pipe costs.
|Number of pages||7|
|Publication status||Published - 13 Jun 2015|
|Event||9th World Congress of the European Water Resources Association, Water Resources Management in a Changing World: Challenges and Opportunities - Istanbul, Turkey|
Duration: 10 Jun 2015 → 13 Jun 2015
|Conference||9th World Congress of the European Water Resources Association, Water Resources Management in a Changing World: Challenges and Opportunities|
|Period||10/06/15 → 13/06/15|
- penalty-free multi-objective evolutionary optimisation
- water distribution systems
- pressure-dependent analysis
- genetic algorithm
- high performance computing
- redundant binary codes
Seyoum, A. G., Tanyimboh, T. T., & Siew, C. (2015). Practical application of penalty-free evolutionary multi-objective optimisation of water distribution systems. 9th World Congress of the European Water Resources Association, Water Resources Management in a Changing World: Challenges and Opportunities, Istanbul, Turkey.