【摘要】 利用切比雪夫(Chebyshev)映射在[-1,1]区间上的遍历性和随机性,提出了一种基于切比雪夫映射的新型混沌粒子群优化(CPSO)算法.该算法在粒子群算法求出的最优解附近进行混沌搜索,提高了混沌粒子群算法的全局优化能力,能有效避免算法容易陷入局部最优以及解决逻辑斯谛(logistic)映射不能在负值区间进行搜索的问题.针对模型中复杂的约束条件,采用分段线性插值函数实现了对目标函数的求解,并通过对采用丰枯电价时三峡梯级水电系统长期优化调度问题的计算及与其他算法的对比,验证了该算法可解决具有复杂约束条件的工程优化问题.更多还原

【Abstract】 Applying the ergodicity and stochastic property of Chebyshev map within the range of ,a novel hybrid chaotic particle swarm optimization(CPSO) algorithm based on Chebyshev map is introduced.This approach,which process chaotic search nearby the optimal solution computed by PSO algorithm,improves the global optimization capability of CPSO algorithm to solve the problems that particle swarm optimization(PSO) algorithm is easy to trap in local optima and logistic map can′t search in the negative region effectively.At last,the piecewise linear interpolation function is applied to deal with complicated constraints conditions for solving the objective function.The simulation results on the three gorges cascaded hydropower system long term optimal dispatch under the flood and dry power price and the comparison with other algorithms show that it is greatly efficient to solve engineering optimal problems with complicated constraints.更多还原