水力发电学报2012，Vol.31Issue(4)：28-33,6.
粗粒度并行遗传算法在水库调度问题中的应用
Application of coarse.grained genetic algorithm to reservoir operation
摘要
Abstract
Real-time optimal operation of giant reservoirs is characterized by large-scale, high-dimensional and nonlinear problems. Large, dynamic and complex search space makes it almost impossible to solve such problems with a simple genetic algorithm. In addition to the advantage of simple genetic algorithm, parallel genetic algorithm can make full use of the computing power of parallel computers in improving solution quality and increasing solution speed, showing a promising prospect in resolving these difficult problems. This paper applies a coarse-grained genetic algorithm based on bi-directional ring topology to optimal operation of the Three Gorgest-Gezhouba cascade reservoirs. Results show that this algorithm can effectively improve the solution quality and increase the solution speed. In terms of convergence performance, it ensures the personality of each population through population isolation and allows populations to evolve constantly throughout the calculations, thus avoiding assimilation of the populations. In terms of parallel computing efficiency, the speedup of CGGA is much greater than the linear one, indicating its full use of calculation processes with less resources waste.关键词
并行遗传算法/水库调度/粗粒度模型/三峡-葛洲坝梯级Key words
parallel genetic algorithm/reservoir operation/coarse-grained genetic algorithm/the Three Gorges project and Gezhouba project cascade reservoirs分类
建筑与水利引用本文复制引用
李想,魏加华,傅旭东..粗粒度并行遗传算法在水库调度问题中的应用[J].水力发电学报,2012,31(4):28-33,6.基金项目
国家“十一五”科技支撑计划项目 （）
