计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
10期
58-61
,共4页
混合蛙跳算法%早熟收敛%高斯变异%柯西变异%优化
混閤蛙跳算法%早熟收斂%高斯變異%柯西變異%優化
혼합와도산법%조숙수렴%고사변이%가서변이%우화
Shuffled Frog Leaping Algorithm%premature convergence%Gaussian mutation%Cauchy mutation%optimization
蛙跳算法是一种受自然界生物现象启发产生的群体进化算法,计算速度快,寻优能力强,但局部搜索能力较弱,容易陷入早熟收敛.针对其缺点,结合高斯变异和柯西变异的优点,提出了一种改进的混合蛙跳算法.改进后的算法收敛速度加快,在一定程度上避免陷入局部最优,提高了蛙跳算法解决复杂函数问题的能力.实验验证了其有效性.
蛙跳算法是一種受自然界生物現象啟髮產生的群體進化算法,計算速度快,尋優能力彊,但跼部搜索能力較弱,容易陷入早熟收斂.針對其缺點,結閤高斯變異和柯西變異的優點,提齣瞭一種改進的混閤蛙跳算法.改進後的算法收斂速度加快,在一定程度上避免陷入跼部最優,提高瞭蛙跳算法解決複雜函數問題的能力.實驗驗證瞭其有效性.
와도산법시일충수자연계생물현상계발산생적군체진화산법,계산속도쾌,심우능력강,단국부수색능력교약,용역함입조숙수렴.침대기결점,결합고사변이화가서변이적우점,제출료일충개진적혼합와도산법.개진후적산법수렴속도가쾌,재일정정도상피면함입국부최우,제고료와도산법해결복잡함수문제적능력.실험험증료기유효성.
Shuffled Frog Leaping Algorithm(SFLA)is a new group evolutionary algorithm prompted by the natrural biological phenomena, and it has fast calculation speed and strong search capability. But its local search ability is weak and it is easily caught in prematrue convergence. Combining with the advantages of Cauchy mutation and Gaussian mutation, a modified SFLA (MSFLA)is proposed to overcome the shortcoming. The MSFLA’s convergence speed is enhanced and the pheonomena that SFLA is trapped in local optimal solution will be avoided to a certain extent, so its ability of problem sloving for complex func-tions is improved. And experimental results prove the validity of the new SFLA.
