Optimal allocation of regional water resources based on simulated annealing particle swarm optimization algorithm

Given the fast growth of economy in Ningxia, China, contradictions between the increase of water resources and the decrease of water supply become increasingly prominent. Therefore, it is critical to utilize limited water resources in a rational manner. This study uses the multi-objective programming theory and forms a multi-objective optimum allocation model for the purpose of using regional water resources sustainably. By aiming at maximizing the comprehensive benefits of society, the model solves the problem that particles are prone to be trapped into local minima by introducing the idea of simulated annealing into the basic particle swarm optimization (PSO) algorithm. The simulated annealing (SA) particle swarm algorithm is applied to solve the model and obtain the optimum allocation schemes of water resources at three different precipitation frequencies in the planning year of Yinchuan (2025), the capital city of Ningxia, China. With this, the model provides a scientific basis for the management of water resources in the city. The results indicate that the model is built upon a scientific and practical foundation, and the algorithm has practical significances. (C) 2022 The Author(s). Published by Elsevier Ltd.