【摘要】 在基本蚁群算法的基础上,引入排序选择策略,使用一定的线性或非线性关系将信息素的差别转化为次序,通过改变选择压力控制个体被选中的概率,具有很好的整体优化性,能有效抑制非成熟收敛。为提高算法的局部搜索性能,在每次迭代后全局更新以前采用的混沌搜索方法,以求在当前最优蚂蚁附近搜索到更好的解。IEEE14、IEEE30和IEEE57系统的仿真分析验证了该算法的有效性,指出了混沌搜索对算法稳定的作用。更多还原

【Abstract】 Leading raking selection strategy into basic ant colony algorithm and using a definite linear or nonlinear relation,the pheromone differences are changed into raking,and the selection probability of individual is controlled by changing selection pressure,such a selection rule possesses good global optimization performance and can inhibit premature convergence effectively. To improve the local searching performance of the algorithm,before global updating of pheromone the chaotic searching method is performed after each time of iteration to search out better solution near current optimal ants. Simulation results of IEEE 14-bus,IEEE 30-bus and IEEE 57-bus system validate the effectiveness of the proposed algorithm. In addition,the action of chaotic search to algorithm stability is pointed out.更多还原