On the use of multi-objective particle swarm optimization for allocation of water resources

Abstract

Water resources allocation is a very complex issue involving social, economic, environmental, and political factors, which leads to multi-objective problems. In this paper, a multi-objective water resources allocation model was developed wherein a multi-objective particle swarm optimization (MOPSO) algorithm was introduced to generate a set of Pareto-optimal solutions. At the same time, to facilitate easy implementation for water resources managers, a simple but effective decision-making approach was presented to provide an opportunity for choosing the desired alternative from a set of Pareto-optimal solutions. Finally, the proposed approach was applied to a case study of optimal allocation of water resources for the water-receiving areas of the South-to-North Water Transfer Project in Hebei Province in China, with three objectives of water supply cost, square sum of relative water shortages and the amount of organic pollutants in water. The results show that the proposed approach is able to offer many alternative policies for the water resources managers, giving flexibility to choose the best out of them, and it is a viable alternative to solve multi-objective water resources and hydrology problems.