基于改进混沌遗传算法的水资源优化调度  

Optimized scheduling of water resource based on improved chaos genetic algorithm

作　　者：赵小强[1] 何智娥 

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050

出　　处：《兰州理工大学学报》2015年第4期65-70,共6页Journal of Lanzhou University of Technology

基　　金：国家自然科学基金(51265032;61263003);甘肃省高校基本科研业务费项目(1203ZTC061)

摘　　要：水资源调度是解决水资源短缺的重要方法,具有多目标、大规模和不确定性的特点.针对混沌遗传算法(CGA)求解水资源调度存在收敛速度慢及易陷入局部优化等问题,提出一种改进的混沌遗传算法(DE-CGA).该算法结合差分算法的全局搜索性、混沌的遍历性和遗传算法的反演性形成了双层结构,较好地克服了收敛速度慢及易陷入局部优化的缺点.仿真结果表明,在水资源实际调度中本文提出的DE-CGA比CGA得到更大的综合效益.Water resource scheduling is an important way to solve the shortage of water resources. It has such characteristics as multiple objectives, large scale, and uncertainty. Aimed at the problems in water resource scheduling with chaos genetic algorithm （CGA） such as low convergence speed and easy to fall into local optimization, an improved chaos genetic algorithm （DE-CGA） is proposed. In this algorithm, the global searching capability of finite difference algorithm, the ergodicity of chaos, and inversion of genetic algorithm （GA） are integrated to form the double-decked structure, so that the above-mentioned problems are well solved. The simulation results show that by using DE-CGA proposed in this article, much more comprehensive benefits will be gained in actual water resource scheduling than using CGA.

关 键 词：水资源优化调度 双层结构 混沌遗传算法(CGA) 

分 类 号：TV212[水利工程—水文学及水资源]