【摘要】 针对当前各种启发式算法,如遗传算法(GA),粒子群算法(PSO),模拟退火算法(SA)等在求解水库优化调度中的不足,提出了将新型的集群智能算法-人工鱼群算法AFSA(Artificial Fish School Algorithm)用于求解水库优化调度问题。该算法通过模拟鱼群的一些基本行为,如捕食、聚群、追尾,来求解问题的最优解。根据水库优化调度问题的情况及数学模型,给出了基于人工鱼群算法的水库优化调度的求解策略,详细讨论了求解步骤,最后给出了实验仿真结果。结果表明该算法具有较强的局部搜索能力,同时也有更高的搜索效率,与其它方法相比,该算法能够找到更优解,验证了该算法的可行性和有效性。更多还原

【Abstract】 To reservoir operation optimization problem,people tried to find the precise method for result with many heuristic algorithms,such as Genetic algorithm(GA),Simulated Annealing algorithm(SA),Particle Swarm Optimization(PSO),etc.But these algorithms have some flaws at the moment.This paper puts forward Artificial Fish Swarm Algorithm(AFSA) for Reservoir operation optimization.The algorithm searches best result through simulating fish’s basic action,such as prey,swarm and follow.To the problem of reservoir operation optimization,it discusses the solving strategy based on AFSA.According to the mathematic model,the detailed steps are put forward.At last,by calculations of the example and comparison with other algorithms,it proves the algorithm has much stronger ability of local search and better search efficiency.It also can find better solution.It certifies that this method is feasible and valid.更多还原