云模型的布谷鸟搜索算法*

针对布谷鸟搜索算法(CS)存在的不足,优化布谷鸟搜索算法求解连续函数问题的性能,结合云模型在定性与定量之间相互转换的优良特性,设计出云模型的布谷鸟搜索算法(CCS)。其核心思想是通过云模型实现布谷鸟的进化学习过程,类似差分进化进行群体间的信息交流。经过10个测试函数的实验仿真,测试结果表明该文算法能有效改善求解连续函数优化问题的性能。同时,针对连续函数优化问题,该算法与其它算法相比是有更好性能的优化算法。

Cloud model cuckoo search algorithm

For lack of cuckoo search algorithm (CS) exist, solving optimization problems the performance of continuous functions, combined with the excellent characteristics of cloud model between qualitative and quantitative conversion ,design cloud model cuckoo search algorithm(CCS). The core idea is to achieve through the cloud model cuckoo evolutionary learning process, similar to the differential evolution for information exchange between groups. After experimental simulation 10 test functions, test results show that the algorithm can effectively improve the performance of solving the continuous function optimization problems. Meanwhile, for continuous function optimization problems, the algorithm is compared with other algorithms have better performance optimization algorithm.