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实际工程中存在许多大规模、非线性多约束的序贯决策问题,传统算法解决起来较为困难。蚁群系统(ACS)是一个用来解决大规模多约束组合优化问题的现代启发式算法,根据序贯决策的特点设计了多层结构的蚁群系统,给出了算法的组成结构;为了节约计算内存和优化时间,详细阐述了淘汰劣质解机制的精英策略;并通过梯级水电站短期优化调度这一实际工程序贯决策问题,来验证所构造的算法,给出了优化调度的数学模型及算法的求解思路。最后,采用我国西南地区某梯级流域中三个水电站的相关数据建立了调度仿真模型,仿真结果证实了所采用算法的有效性和可行性。
There are many large-scale, nonlinear and multi-constrained sequential decision-making problems in practical engineering. The traditional algorithms are more difficult to solve. Ant Colony System (ACS) is a modern heuristic algorithm used to solve large-scale multi-constraint combinatorial optimization problems. According to the characteristics of sequential decision-making, an ant colony system with multi-layer structure is designed, and the composition of the algorithm is given. Calculate the memory and optimization time, elaborate the elite strategy of eliminating inferior quality solution mechanism; verify the constructed algorithm through the short-term optimal scheduling of cascade hydropower stations, and give the mathematical model and algorithm of optimal scheduling Solution ideas. Finally, the simulation model of dispatching is established by using the data of three hydropower stations in a cascade watershed in the southwestern region of China. The simulation results verify the effectiveness and feasibility of the proposed algorithm.