Improved shuffled frog-leaping algorithm and its convergent analysis
Jiwei Xu · Computer Engineering and Applications Journal · 2011
To improve the ability of shuffled frog-leaping algorithm(SFLA)for solving function optimization problems,an improved efficiently shuffled frog-leaping algorithm(ESFLA) is proposed,which adopts the evolutionary methods of particle swarm optimization and differential evolution,and its time complexity is analysed.The global convergence of ESFLA is proved by using limit Markov chain.In order to test and verify the ability of ESFLA for solving the function optimization problems,the performance of ESFLA is compared with that of SFLA and ISFLA2.The experimental results indicate that the performance of ESFLA is superior to SFLA and ISFLA2,and it is more suitable for solving complex function optimization problems.