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Selection Method of Multi-Objective Problems Using Genetic Algorithm in Motion Plan of AUV 被引量:3
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作者 ZHANG Ming-jun , ZHENG Jin-xing , ZHANG Jing College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001 ,China College of Computer and Information Science, Harbin Engineering University, Harbin 150001 , China 《Journal of Marine Science and Application》 2002年第1期81-86,共6页
To research the effect of the selection method of multi — objects genetic algorithm problem on optimizing result, this method is analyzed theoretically and discussed by using an autonomous underwater vehicle (AUV) as... To research the effect of the selection method of multi — objects genetic algorithm problem on optimizing result, this method is analyzed theoretically and discussed by using an autonomous underwater vehicle (AUV) as an object. A changing weight value method is put forward and a selection formula is modified. Some experiments were implemented on an AUV, TwinBurger. The results shows that this method is effective and feasible. 展开更多
关键词 AUV multi objective optimization genetic algorithm selection method
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Optimization approach hydroforming car beam billets based grey system theory 被引量:1
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作者 吴耀金 薛勇 段江年 《Journal of Beijing Institute of Technology》 EI CAS 2011年第1期48-53,共6页
Perfect combination of structural size parameters of the hydroforming billets is essential to obtain even wall thicknesses of the car beam. Finite element ( FE ) analysis on hydroforming car beam was carried out, a... Perfect combination of structural size parameters of the hydroforming billets is essential to obtain even wall thicknesses of the car beam. Finite element ( FE ) analysis on hydroforming car beam was carried out, and the results were optimized according to multiple quality objectives by the grey system theory. With bending angle, bending radius and hight difference along the axis direction as variables, orthogonal FE analyses were conducted and the minimum and maximum wall thicknes ses of the billets with different sizes were obtained. Taking the minimum and maximum wall thick nesses as two references, the correlation coefficient between the data for reference and those for comparison by the grey system theory reduced multi objectives to a single quality objective, and the average correlation level of every billet facilitated the optimization of size parameters for hydroform ing car beam. The trial production showed that the optimization approach satisfied the need of hy droforming car beams. 展开更多
关键词 car beam HYDROFORMING BILLET grey system theory multi objective optimization
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