论文部分内容阅读
蝙蝠算法(BA)是一类基于试探技巧的群智能优化算法,该算法已被广泛用于诸多领域问题的求解.本文提出一个改进的蝙蝠算法NIBA.在算法中,为了加强蝙蝠算法的局部和全局搜索能力,提出了三个改进策略.首先,为了改进蝙蝠的局部搜索能力,在当前最优解处给出了一个新的搜索方程.其次,为了改进算法的全局搜索能力,平衡算法的开发能力和探索能力,算法吸收并改进了和声搜索机制.最后,为了进一步提高NIBA算法的搜索能力,在当前最优解处,算法采用了混沌搜索机制.为了验证算法的性能,针对18个标准测试函数进行了数值实验.与其它算法的比较结果显示,NIBA算法具有更好的稳定性,且效率更高.
Bats algorithm (BA) is a group of heuristic intelligence optimization algorithm based on heuristic, which has been widely used in many fields to solve the problem.In this paper, an improved bat algorithm NIBA is proposed.In order to enhance the local and Global search ability, three improved strategies are proposed.First, in order to improve the bat’s local search ability, a new search equation is given at the current optimal solution.Secondly, in order to improve the global search ability of the algorithm, the development of the balance algorithm Ability and exploratory ability.The algorithm absorbs and improves the harmony search mechanism.Finally, in order to further improve the search ability of NIBA algorithm, the chaos search mechanism is adopted in the current optimal solution.In order to verify the performance of the algorithm, 18 standards The experimental results show that the proposed NIBA algorithm is more stable and efficient than other algorithms.