水利水电科技进展2026，Vol.46Issue(2)：38-45,8.DOI:10.3880/j.issn.1006-7647.2026.02.005
基于改进人工鱼群-粒子群算法的梯级水库群多目标优化调度算法
A multi-objective optimal operation algorithm of cascade reservoirs based on improved artificial fish swarm-particle swarm optimization algorithm
摘要
Abstract
To address the high-dimensional and nonlinear complex optimization problems in the optimal operation of cascade reservoirs,a two-stage multi-objective improved artificial fish swarm-particle swarm optimization(TMIAFS-PSO)algorithm was proposed.This algorithm employs segmented mapping to expand the search space of the initial population,and enhances local and global search capabilities by adjusting the adaptive step size and introducing a diversified movement strategy.Additionally,the algorithm adopts a two-stage filtering strategy to retain particles that meet the constraint conditions and incorporates an improved artificial fish swarm optimization strategy to further expand the particle search range.A case study was conducted on the cascade reservoir group consisting of Wudongde,Baihetan,Xiluodu,and Xiangjiaba in the lower reaches of the Jinsha River.The results indicate that,compared to other algorithms,the Pareto solution set of the TMIAFS-PSO algorithm exhibits better convergence and uniformity,demonstrating the superiority of this algorithm.By analyzing the water level variations of the operation schemes generated by the TMIAFS-PSO algorithm,a relatively stable optimal operation scheme for this cascade reservoir group is summarized.关键词
梯级水库群优化调度/改进人工鱼群-粒子群算法/帕累托解集/多目标优化算法Key words
optimal operation of cascade reservoirs/improved artificial fish swarm-particle swarm optimization algorithm/Pareto solution set/multi-objective optimization algorithm引用本文复制引用
张侃侃,赵海峰,王兆才..基于改进人工鱼群-粒子群算法的梯级水库群多目标优化调度算法[J].水利水电科技进展,2026,46(2):38-45,8.基金项目
水能资源利用关键技术湖南省重点实验室开放研究基金面上项目(PKLHD202304) （PKLHD202304）
教育部人文社科规划基金项目(24YJAZH167) （24YJAZH167）
国家自然科学基金项目(11701363) （11701363）
