Application of particle swarm algorithm in the optimal allocation of regional water resources based on immune evolutionary algorithm

Abstract

The optimal allocation model of regional water resources is built with the purpose of maximizing the comprehensive economic, social and environmental benefits of regional water consumption. In order to solve the problems that easily appear during the model solution of regional water resource optimal allocation with multiple water sources, multiple users and multiple objectives like “curse of dimensionality” or sinking into local optimum, this paper proposes a particle swarm optimization (PSO) algorithm based on immune evolutionary algorithm (IEA). This algorithm introduces immunology principle into particle swarm algorithm. Its immune memorizing and self-adjusting mechanism is utilized to keep the particles in the fitness level at a certain concentration and guarantee the diversity of population. Also, the global search characteristics of IEA and the local search capacity of particle swarm algorithm have been fully utilized to overcome the dependence of PSO on initial swarm and the deficiency of vulnerability to local optimum. After applying this model to the allocation of water resources in Zhoukou, we obtain the scheme for optimization allocation of water resources in the planning level years, i.e. 2015 and 2025 under the guarantee rate of 50%. The calculation results indicate that the application of this algorithm to solve the issue of optimal allocation of regional water resources is reliable and reasonable. Thus it offers a new idea for solving the issue of optimal allocation of water resources.