摘要：新型元启发式算法例如粒子群算法，萤火虫算法，和声搜索算法已经成为现今复杂的优化问题的有效解决方法。该文基于蝙

蝠的回声定位行为提出了一种新型的元启发式算法———蝙蝠算法，同时也将现有的一些算法的优点引入到该算法中。 改文对该算

法进行了详细的公式化表述并对其执行流程的作出了说明，并且将该算法与遗传算法、粒子群优化算法等算法进行了比较。仿真结

果表明,蝙蝠算法明显优于其他算法，并对进一步的研究作出了展望。-Summary: The new meta-heuristic algorithms such as particle swarm optimization, firefly algorithm, harmony search algorithm has become an effective solution to today' s complex optimization problems. In this paper, based on bat echolocation behavior presents a new meta-heuristic algorithm--- bat, but also some of the advantages of the existing algorithms is introduced into the algorithm. Change the text of the algorithm in detail and make a note formulaic expressions its implementation process, and the algorithm and genetic algorithms, particle swarm optimization algorithm are compared. Simulation results show that the algorithm is superior to other algorithms bat, and made the prospects for further research.