基于改进粒子群算法的水资源优化调配模型研究

Research on Optimal Allocation Model of Water Resources Based on Improved Particle Swarm Optimization Algorithm

为了缓解忻州-阳泉地区日益凸显的水资源供需矛盾,建立了以研究区供水、发电和生态为目标的区域水资源优化调配模型,同时提出了定权重目标比适应度函数,将复杂的多目标问题转化为易于求解的单目标问题。在求解模型过程中,使用S型递减函数计算惯性权重并结合定权重目标比适应度函数简化求解,改进了粒子群算法。通过丰、平、枯3种不同来水条件下的情景模拟验证发现:改进粒子群算法运行前期全局搜索能力得到提升、中期搜索速度加快、后期局部收敛能力得到保证,在求解过程中不易陷入局部最优解;根据模型计算得出的水资源优化调配方案能够真实有效地反映研究区域的供水要求、均衡优化年内水资源分配、平衡区域之间的水资源供需关系、协调各目标之间的满足情况,模型具有可行性。

In order to alleviate the increasingly prominent contradiction between supply and demand of water resources in Xinzhou-Yangquan area,a regional water resources optimal allocation model was established with the objectives of water supply,power generation and ecology in the study area.The issue was transformed into an easy-to-solve single-objective issue.In the process of solving the model,the sigmoid decreasing function was used as the inertia weight and combined with the fixed weight target ratio fitness function to simplify the solution and the particle swarm algorithm(PSO)was improved.Through the scenario simulation verification under three different water inflow conditions,it was found that the improved PSO algorithm could improve the global search ability in the early stage,speed up the mid-term search speed and ensure the local convergence ability in the later stage and it was not easy to fall into local optimum in the solution process.The optimal allocation scheme of water resources was calculated according to the model that could truly and effectively reflect the water supply requirements of the study area and the model was feasible.