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Algorithm for global optimization of optical systems based on genetic competition

机译:基于遗传竞争的光学系统全局优化算法

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Global optimization of optical system designs is difficult because of the complex solution space and extreme non- linearity of system performance with respect to design parameters. Genetic algorithms (GA's) have been used to effectively solve complex non-linear optimizations in other fields of science. GA's model each design parameter as part of a genetic code for an imaginary creature, and the system performance is interpreted to be the fitness for survival of this creature. The GA's goal is to improve the system performance by selective breeding of simulated creatures to yield simulated offspring with desirable traits. An algorithm for doing this along with results will be presented.
机译:由于对设计参数的复杂解决方案空间和系统性能的极端非线性,因此难以实现光学系统设计的全局优化。遗传算法(GA)已被用于有效地解决其他科学领域的复杂非线性优化。 GA的模型每个设计参数作为虚构生物的遗传密码的一部分,系统性能被解释为这一生存的健身。 GA的目标是通过选择性繁殖模拟生物来提高系统性能,从而产生具有所需性状的模拟后代。将呈现用于执行此操作的算法。

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