Application of Particle Swarm Algorithm in the Optimal Allocation of Regional Water Resources Based on Immune Evolutionary Algorithm

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.2015and 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 ofers a new idea for solving the issue of optimal allocation of water resources.

基于免疫进化的粒子群混洗蛙跳算法

为了避免混洗蛙跳算法易于出现不成熟收敛,提高求解质量,提出了基于免疫进化的粒子群混洗蛙跳算法。该算法将粒子群算法中粒子追踪全局极值的思想融入混洗蛙跳算法中,对族群内的最差个体同时跟踪族群内和全局两个最优个体的信息,进行深度搜索;并引入免疫进化算法对群体中的最优个体进行免疫进化迭代计算,以达到充分利用最优个体的信息的目的。该算法不仅避免了陷入局部极值的局限,以更高的精度逼近全局最优解,而且能加速收敛。对多个典型测试函数的计算表明:基于免疫进化的粒子群混洗蛙跳算法比传统的混洗蛙跳算法具有更好的寻优能力、稳定效果和更快的收敛速度。

基于免疫进化的粒子群算法在灌区水资源优化配置中的应用研究

结合已有水资源优化配置模型,提出了基于免疫进化的粒子群算法,并将该方法应用于濮阳灌区,对其农业水资源进行优化配置.实例计算表明,该混合算法克服了已有算法中初期信息素匮乏,易陷于局部最优解等不足,结果合理,且计算较为简单,可为灌区水资源配置提供理论依据和决策参考.

可持续发展视角下的区域水资源优化配置模型

为了构建可持续发展视角下的区域水资源优化配置模型,针对水资源优化配置表现出的主从递阶决策、多目标决策、多阶段决策等特点,构建了优化配置模型,采用逻辑集成多种算法的求解思路。集成引入了多目标满意度计算、主从递阶博弈方法、基于粒子群算法的演化博弈求解方法、动态规划求解方法,研究建立了具有逻辑关系的算法体系。实例研究表明,模型与方法是可行的。提出的模型与算法为复杂决策问题的模型建立及求解提供了解决途径。

免疫粒子群优化算法在农业水资源优化配置中的应用

求解农业水资源优化配置模型(高维非线性优化模型),较常采用大系统分解协调原理和动态规划相结合的方法,这样减少了变量个数,便于优化求解,但协调的过程需要多次从低阶模型中返回信息,而且对于每层的寻优求解过程存在难以克服的矛盾.采用标准的粒子群优化算法则优化程度不易保证并容易陷入局部最优,优化结果对初始种群依赖性较强.因此应用免疫进化算法对标准粒子群优化算法进行改进并应用于灌区农业水资源优化配置模型的求解.算例分析表明,免疫粒子群算法为求解高维复杂的优化配置问题提供了新思路.