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《JOURNAL OF NORTHEASTERN UNIVERSITY》 1997-05
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Improved Genetic Algorithm for Nonlinear Programming Problems

Tang Jiafu,Wang Dingwei  
Based on the method of penalty function,an improved Genetic Algorithm with mutation along the weighted gradient direction for nonlinear programming problems is proposed in this paper. It will avoid the computer difficulty existing in the penalty function method,but also it does not need the complex coding and decoding process necessary for traditional genetic algorithm. Simulation of some examples shows that this method is effective.
【Fund】: 国家自然科学基金
【CateGory Index】: O221.2
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3 GAO Zhen-hao;SU Gui-ying;YU Yan-wei;School of Economics and Management,North University of China;School of Management,Tianjin University of Technology;;Solving the Equilibrium Problem of Type Ⅱ Assembly Line Based on Genetic Algorithm of Group Technology[J];物流科技;2017-06
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6 Yan Shuaiyin;Bo Ruifeng;Li Ruiqin;Yin Shuyu;Shen Xingquan;Pan Hongjun;School of Mechanics and Power Engineering,North University of China;Shanxi Deep-Hole Cutting Research Center of Engineering Technology;;Dynamic Penalty Function Nonlinear Programming Genetic Algorithm and the Application in Automobile Gearbox[J];机械传动;2015-02
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9 LIU Zheng-long;YANG Yan-mei;LUO Yu-jun;Pre-clinic Medical College,North-Sichuan Medical University;Mathematics and Information College,West China Normal University;;Research of nonlinear system identification based on genetic algorithm[J];黑龙江大学自然科学学报;2014-03
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