动态规划-粒子群算法在水库优化调度中的应用  

Optimal operation of reservoir based on dynamic programming and particle swarm optimization

作　　者：李顺新[1] 杜辉[1] 

机构地区：[1]武汉科技大学计算机科学与技术学院,武汉430081

出　　处：《计算机应用》2010年第6期1550-1551,1580,共3页journal of Computer Applications

摘　　要：水库优化调度是一个典型的具有多约束条件的、动态的、非线性的优化问题。针对这些问题,利用动态规划-粒子群(DP-PSO)算法加以求解。利用动态规划中的多阶段最优策略原理,将水库优化调度问题转化为多阶段决策子问题,各个子问题采用粒子群算法优化求解。数值实验表明,在计算时段较多时,DP-PSO算法计算的可靠性明显优于一般的动态规划(DP)算法,在计算时间上,DP-PSO算法用时较动态规划-遗传算法(DP-GA)少。Reservoir optimal scheduling is a typical multi-constrained,dynamic,non-linear optimization problem.To solve this problem,a Dynamic Programming-Particle Swarm Optimization （DP-PSO） algorithm was used to solving.This algorithm used the optimal Dynamic Programming （DP） principle to convert the reservoir optimal scheduling problem to multistage decision-making sub-problems;the solution of each sub-problem was got by particle swarm optimization algorithm.The numerical experiments show that with more time in calculation,the reliability of the DP-PSO is superior to the general DP algorithm,and the calculation time of DP-PSO is less than DP-Genetic Algorithm （DP-GA）.

关 键 词：水库调度 粒子群算法 动态规划 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]