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A Performance Study of Real Coded Genetic Algorithm on Gear Design Optimization

机译:实际编码遗传算法在齿轮设计优化中的绩效研究

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The major problem that deals with practical engineers is the mechanical design and creativeness. Mechanical design can be defined as the choice of materials and geometry, which satisfies, specified functional requirements of that design. A good design has to minimize the most significant adverse result and to maximize the most significant desirable result. An evolutionary algorithm offers efficient ways of creating and comparing a new design solution in order to complete an optimal design. In this paper a type of Genetic Algorithm, Real Coded Genetic Algorithm (RCGA) is used to optimize the design of helical gear pair and a combined objective function with maximizes the Power, Efficiency and minimizes the overall Weight, Centre distance. The performance of the proposed algorithms is validated through LINGO Software and the comparative results are analyzed.
机译:处理实用工程师的主要问题是机械设计和创造性。机械设计可以定义为材料和几何形状的选择,满足该设计的规定功能要求。良好的设计必须尽量减少最显着的不利效果,并最大限度地提高最显着的理想结果。进化算法提供了创建和比较新设计解决方案的有效方法,以便完成最佳设计。在本文中,一种遗传算法,实际编码遗传算法(RCGA)用于优化螺旋齿轮对的设计和最大化功率,效率,最小化总重量,中心距离的组合目标函数。通过Lingo软件验证所提出的算法的性能,并分析了比较结果。

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