基于模拟退火粒子群算法的水资源优化配置

为了缓解水资源供需矛盾、提高水资源利用率,并在水资源优化配置中探寻新的求解方法,构建了以社会、经济、生态效益为目标的综合评价函数,建立了基于模拟退火粒子群算法的优化配置模型.将模拟退火的思想引入基本粒子群算法当中,解决了粒子易陷入局部极小值的问题.以陕西省渭南市大荔县为研究区域,设置了地表水、地下水、其他水3种水源以及5类不同用水户;利用模拟退火粒子群算法,对该区域2020,2030年2个水平年,3种不同来水水平(P=50%,75%,95%)下的水资源优化配置方案进行了求解.结果表明:在75%的来水下,2020年大荔县地表水、地下水和其他水的供水量分别为19 641.89,12 000.29和8 655.69万m³;2030年的供水量分别为25 936.30,17 345.87和7 685.42万m³.与优化前的供水量相比,节水量分别为333.11和404.76万m³.

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

In order to alleviate the contradiction between supply and demand of water resources and improve the utilization rate of water resources,a new solution method was explored for optimizing allocation of water resources.The benefits of the society,economy and ecology were set up as the comprehensive objective function.The optimal configuration model based on simulated annealing particle swarm optimization was designed.Meanwhile,the particle swarm optimization algorithm was combined with simulated anneating to solve the problem that the particles are easily falling into the local minimums.Dali County,Weinan City,Shaanxi Province was taken as the research area,three kinds of water sources including surface water,groundwater,other water and five kinds of different water users were set up.The simulated annealing particle swarm optimization algorithm was used to solve the optimal allocation scheme of water resources under three guarantee levels(P=50%,75%,95%)in two level years of 2020 and 2030.The results show that:under 75%of the incoming water,the water supply of surface water,groundwater and other water are 19601.89×104 m3,12000.29×104 m3 and 8655.69×104 m3 in 2020;the water supply are 25936.30×104 m3,17345.87×104 m3 and 7685.42×104 m3 in 2030.Compared with the water supply before optimization,the water saving amount is 333.11×104 m3 and 404.76×104 m3,respectively.