基于PSO与DE混合算法的水资源优化配置

A Hybrid Algorithm Based on Particle Swarm Optimization and Differential Evolution for Rational Allocation of Water Resources

基于公平性原则构建水资源优化配置模型,针对模型的特点,将模型的可行解进行粒子化处理。利用基于粒子群(PSO)和差分进化(DE)的混合算法(PSODE)对模型进行求解。该算法通过双种群间的信息共享机制,大大降低了求解陷入局部最优的风险。此外,还采用了一种粒子变异机制进一步提高PSODE算法的性能,并通过漳河流域四大灌区水资源配置实例表明PSODE算法比PSO和DE算法收敛速度更快、准确度更高。

On the basis of the principle of fairness,this paper built an optimal water resources allocation model. And a feasible solution in the mod-el was treated as a particle on the characteristics of the model. It used a hybrid optimization algorithm based on particle swarm optimization and dif-ferential evolutionto solve the model. The algorithm greatly reduced the risk of falling into local optimal solution through information sharing between double populations. In addition,we also used a variation mechanism to further improve the performance. Using the four irrigation districts in the Zhanghe River basin,it evaluated the result of this model. The result shows that PSODE algorithm is faster in convergence speed and more accurate than PSO and DE algorithms.