An Improved GT Algorithm for Solving Complicated Dynamic Function Optimization Problems  

作　　者：ZHANG Qing LI Yan KANG Zhuo KANG Lishan 

机构地区：[1]School of Computer, China University of Geosciences, Wuhan 430074, Hubei, China [2]School of Physics and Technonlogy, Huanggang Normal University, Huanggang 438000, Hubei, China [3]Computer Center, Wuhan University, Wuhan 430072, Hubei, China [4]State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China

出　　处：《Wuhan University Journal of Natural Sciences》2009年第5期404-408,共5页武汉大学学报（自然科学英文版）

基　　金：Supported by the National Natural Science Foundation of China(60473081,60133010)

摘　　要：An improved Guo Tao algorithm （IGT algorithm） is proposed for solving complicated dynamic function optimization problems, and a function optimization benchmark problem with constrained condition and two dynamic parameters has been designed. The results achieved by IGT algorithm have been compared with the results from the Guo Tao algorithm （GT algorithm）. It is shown that the new algorithm （IGT algorithm） provides better results. This preliminarily demonstrates the efficiency of the new algorithm in complicated dynamic environments.An improved Guo Tao algorithm （IGT algorithm） is proposed for solving complicated dynamic function optimization problems, and a function optimization benchmark problem with constrained condition and two dynamic parameters has been designed. The results achieved by IGT algorithm have been compared with the results from the Guo Tao algorithm （GT algorithm）. It is shown that the new algorithm （IGT algorithm） provides better results. This preliminarily demonstrates the efficiency of the new algorithm in complicated dynamic environments.

关 键 词：dynamic function optimization Guo Tao algorithm （GT algorithm） benchmark problems 

分 类 号：O224[理学—运筹学与控制论] TK47[理学—数学]