Author(s): Lijie Cui; N. S. Mohammad Mortazavi; George Kuczera
Linked Author(s):
Keywords: Multi-objective optimization; Ant colony; Genetic algorithm; Water supply
Abstract: Planning and management of urban water supply headworks systems is a complex task which gives rise to a large number of infrastructure and operating policy options. This is often complicated by the existence of multiple competing objectives, whereby a gain in one particular objective may result in a loss in another objective. The solution to these problems requires simultaneous consideration of conflicting objectives. Multi-objective optimization deals with the process of simultaneously optimizing two or more conflicting objectives. In this study, two optimization methods, the genetic algorithm and ant colony optimization algorithm, are explored and compared for an urban water supply system.
Year: 2009