基于改进蚁群算法的电力线路检修的多目标优化

通过对辽宁省电力有限公司的线路检修问题的综合分析,考虑各种约束条件,提出了一种多目标优化数学模型.在优化的过程中采用了改进的蚁群算法,并结合了图论中的图着色问题.改进蚁群算法的核心是自适应动态调整路径上的信息素,信息素增量由小变大,增强局部搜索能力,再由大变小,增强全局搜索能力,循环变化,从而利于算法能够跳离局部最优解.改进蚁群算法的优点是在求得满意解的基础上,大大提高了算法的速度.仿真实验结果表明,新算法的优化质量优于基本的蚁群算法.

Multi-objective Optimization Based on Improved Ant Colony Algorithm for Electric Power Line Overhaul

A muLti-objective model is presented according to the comprehensive analysis of the electric power line overhaul in Liaoning province, taking account of various constraints. The coloring problem of graph theory is combined with an improved ant colony algorithm to plan optimally the overhaul. The core of the improved algorithm is to make dynamically the pheromones on routes adaptive so as to enable the increment of pheromones to become great from small to strengthen the ability for local search, and then become small from great to strengthen the ability for global search. Such a cyclical change is thus highly beneficial to an algorithm to get rid of locally optimal solution. The merit of the improved ant colony algorithm is that not only the satisfactory solution is obtained, but also the searching speed is improved. Simulation results showed that the improved ant colony algorithm is superior to the conventional one in quality.