Global Function Optimization Based on Gene Expression Programming with Differential Evolution
Qiu Jiang-tao · 2009
To improve the efficiency in function optimization via Gene Expression Programming(GEP),Differential Evolution(DE) was introduced into GEP.A novel algorithm called DEGEPO was proposed.The main work of this paper included(1) the gene in GEP was redesigned to adapt global function optimization;(2) novel mutation and crossover operations were applied;(3) a parameter optimization algorithm based on GEP with DE called DEGEPO was proposed and it was also analyzed;(4)experiments demonstrated the efficiency and effectiveness of DEGEPO.Compared with ba-sic GEP,the precision of DEGEPO increased 2～4 orders of magnitude averagely.