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针对基本布谷鸟搜索(Cuckoo Search,CS)算法在寻优过程中收敛速度慢、寻优结果精度不高的问题,提出一种混合模拟退火(Simulated Annealing,SA)算法的布谷鸟算法(SA-CS).算法采用退火时机的判断准则判断是否陷入局部最优,若陷入则让算法进入模拟退火机制,以一定的概率得到一个更差的解,使得算法跳出局部最优,增强算法寻找最优解的能力.通过对经典测试函数和旅行商问题进行测试,结果表明,改进后的SA-CS算法提高了基本CS算法的收敛速度以及寻优精度,对于函数优化问题和组合优化问题都具有一定的优势.
Aiming at the problem that the Cuckoo Search (CS) algorithm converges slowly in the process of optimization and the precision of the search results is not high, a Simulated Annealing (SA) algorithm called the cuckoo algorithm (SA- CS) .The algorithm adopts the judgment criterion of annealing opportunity to judge whether it falls into the local optimum or not, if it gets into, the algorithm enters the simulated annealing mechanism to obtain a worse solution with a certain probability, so that the algorithm jumps out of the local optimum and the enhancement algorithm looks for the optimal The test results show that the improved SA-CS algorithm can improve the convergence rate and accuracy of the basic CS algorithm, and have a certain effect on both the function optimization problem and the combinatorial optimization problem The advantages.