An Improved Shuffled Frog Leaping Algorithm
Shi Qiu-hong · 2013
Aiming at the weaknesses of shuffled frog leaping algorithm(SFLA) such as easily trapping into local optimum and population degeneration with the growth of iteration,an improved shuffled frog leaping algorithm was proposed.The worst individual was updated according to the center pointer of subgroup and the global optimum point,which can make the worst individual obtain more information from other individuals within the subgroup.When the subgroups combined after one iteration,the entire population was updated by selection operator.The median strategy kept the balance between the global search and local search,and the selection strategy maintained the diversity of the population in the process of evolution.The experimental results evidenced that the new algorithm has better performance.