动态改变邻域空间和搜索步的自由搜索算法

针对群体智能优化方法--自由搜索算法后期寻优效率降低、特别是多维空间寻优效果不佳的问题，提出一种动态改变邻域空间和搜索步的自由搜索算法，该算法前期邻域空间和搜索步变化不大，进行全局搜索；后期邻域空间和搜索步变化较大，进行局部寻优．给出了动态调整邻域空间及搜索步的方法．通过对4个经典的函数进行测试实验，结果表明，该算法在平均最优值和成功率上都有所提高，而且收敛速度快、精度高，尤其对多维多峰函数效果更加明显．

Free search algorithm with the variable neighbourhood and step

To overcome the problem of population-based optimisation algorithms-free search (FS) to find the best solution with the low efficient later stage, especially multi-dimensional search space, FS with the variable neighbourhood and step method is proposed. The previous neighbourhood space and step do not change much in searching for the overall situation and change relatively greatly in the later stage in local exploration by the algorithm. The methods for the varying neighbourhood and step are given and simulation results with four traditional functions show that the algorithm has a better probability of finding the global optimum and mean best value, with quick convergence and high precision, especially for the multi-dimensional and multimodal function.