Computer Science ›› 2009, Vol. 36 ›› Issue (11): 140-142.
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LI Tai-yong,TANG Chang-jie,WU Jiang,QIU Jiang-tao
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Abstract: 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 basic GEP, the precision of DEGEPO increased 2-4 orders of magnitude averagely.
Key words: Genetic algorithm(GA),Gene expression programming(GEP),Differential evolution,Function optimization
LI Tai-yong,TANG Chang-jie,WU Jiang,QIU Jiang-tao. Global Function Optimization Based on Gene Expression Programming with Differential Evolution[J].Computer Science, 2009, 36(11): 140-142.
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