| 标记平面立体线图的自适应遗传算法 |
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| 作者姓名： | 熊思颖 董黎君 |
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| 作者单位： | 太原理工大学机械工程学院，山西 太原 030024 |
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| 摘 要： | 针对由理查德·迈尔斯提出的标记线图的遗传算法进行改进：采取自适应参数调 整法，同一代中适应度高于平均的个体杂交和变异率动态变化，适应度低于平均的个体杂交和 变异率设为定值；在创建初始种群时加入了约束条件，旨在改善初始种群覆盖空间的不确定性 和个体分布的相对不合理性；修正了遗传算法的适应度函数，使得以个体适应度为指标的选择 算子能正确引导算法搜索解空间。用遗传算法标记 6 幅不同的线图，变量为杂交率、变异率公 式中的参数 a 和 c，分析算法标记成功率曲线的变化趋势，探讨算子参数设置对遗传算法性能 的影响，结果表明 c 属于区间0，0.05]，a 属于区间0.8，1.0]且为标记线图的遗传算法的最优 参数设置。
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| 关 键 词： | 线图标记 遗传算法 二进制编码 适应度 |
A Self-Adaptive Genetic Algorithm for Labeling Line Drawings of Planar Objects |
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| Authors: | XIONG Siying DONG Lijun |
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| Affiliation: | College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan Shanxi 030024, China |
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| Abstract: | This paper improves the genetic algorithm for labeling line drawings presented by Richard Myers in the following areas: self-adaption parameter adjustment method was used, the hybridization rate and mutation rate of individuals with high fitness in the same generation were dynamically changed, and the rate of hybridization and mutation of individuals with lower fitness was set as a fixed value; the constraints were established when the initial population was created, with the aim of improving the uncertainty of the initial population coverage space and the relative irrationality of the individual distribution; the fitness function of the genetic algorithm was modified so that the selection operator with the individual fitness as the index could correctly guide the algorithm to search the solution space. The genetic algorithm was employed to mark six different line drawings, the parameter a and c in the formula of hybridization rate and mutation rate were used as experimental variables, the change tendency of the algorithm’s mark success rate curve was analyzed, and the influence of operator parameter setting on the performance of genetic algorithm was discussed. The results show that c belongs to interval 0, 0.05] and a belongs to interval 0.8, 1.0] and a is the optimal parameter setting of the genetic algorithm for labeling line drawings. |
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| Keywords: | line drawing label genetic algorithm binary coding fitness |
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