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遗传算法求制造系统中工件三维空间尺寸

Genetic algorithm calculate the three-dimensional space for workpiece of manufacturing system
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摘要 浮点遗传算法 (FGA)用于求制造系统工件空间尺寸。用算术交叉算子 ,对传统遗传算法进行改进 ,给出了在线工件的目标函数 ,建立了数学模型。该方法具有计算精度高的特点 ,可获得全局最优解 ,用C + +编程 ,收敛速度快 ,在计算机上容易实现。适用于离散数据的工件空间尺寸及在线三维空间尺寸主动计算。最后 ,给出了一个形状复杂的工件的应用实例 ,得到了球半径和其公差的最优解。 Floating-point genetic algorithm (FAG)is used to calculate the three-dimensional space for workpiece of manufacturing system. Applying arithmetic crossover operators, the traditional GA mathematical model has been modified. This method has fast convergent speed. It is an effective method and its calculating precision is accurate. Its program used to C ++, and it can be realized easily using computer and CAPP. This method is the same with workpiece, which its data is discrete. It also measures workpiece of three-dimensional space for on-line product .It can find the global optimal solution. Finally, an instance is given that the process of internal spherical surface is more complex than other′s workpiece. It gets optimal solution of spherical radius and its tolerance.
出处 《组合机床与自动化加工技术》 北大核心 2003年第8期14-15,19,共3页 Modular Machine Tool & Automatic Manufacturing Technique
基金 国家 8 63高技术研究发展计划资助项目 (863 - 51 1 - 0 80 - 0 0 6)
关键词 制造系统 工件 三维空间尺寸 遗传算法 离散数据 最优解 FGA FGA discrete data manufacturing system three-dimensional space optimal solution
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