CAJ | 학술논문

布谷鸟搜索算法( Cuckoo Search,CS)是一种新型的元启发式算法。针对CS算法局部搜索能力较弱、后期收敛速度偏慢和收敛精度不高等缺点,提出一种基于变尺度法(DFP)和自适应步长(Adaptive Step)的布谷鸟搜索算法(DACS),使Lévy飞行的步长非线性自适应变化来提高算法的收敛速度,同时使经过Lévy飞行机制和淘汰机制进化后的布谷鸟种群再运用DFP快速获取全局最优解。用6种具有各种代表性的测试函数分别测试DACS算法和CS算法的性能。实验结果表明,DACS算法在保持强大的全局搜索能力的同时,比CS算法具有更快的收敛速度、更高的收敛精度和更好的鲁棒性,尤其适合多峰及高维函数的优化。
포곡조수색산법( Cuckoo Search,CS)시일충신형적원계발식산법。침대CS산법국부수색능력교약、후기수렴속도편만화수렴정도불고등결점,제출일충기우변척도법(DFP)화자괄응보장(Adaptive Step)적포곡조수색산법(DACS),사Lévy비행적보장비선성자괄응변화래제고산법적수렴속도,동시사경과Lévy비행궤제화도태궤제진화후적포곡조충군재운용DFP쾌속획취전국최우해。용6충구유각충대표성적측시함수분별측시DACS산법화CS산법적성능。실험결과표명,DACS산법재보지강대적전국수색능력적동시,비CS산법구유경쾌적수렴속도、경고적수렴정도화경호적로봉성,우기괄합다봉급고유함수적우화。
Cuckoo Search ( CS) is a novel meta-heuristic algorithm. Aiming at the defects of weak local search ability,slow convergence velocity and low convergence accuracy,a modified CS algorithm based on DFP and adaptive step is proposed in this paper. In the im-proved cuckoo search algorithm,the step of Lévy flight nonlinear dynamic changes improve convergence velocity. After evolved from Lévy flights and elimination mechanism,the cuckoo populations rapidly access to global minima by DFP. Sixth representative benchmark functions are used to test the performance of DACS algorithm and CS algorithm respectively. The conclusions indicate that DACS algo-rithm has faster convergence speed,higher convergence accuracy and robustness,compared with CS algorithm. Meanwhile,DACS algo-rithm keeps strong global search capability,which is particularly suitable for the optimization of multimodal function and high dimension function.