Abstract: Optics Inspired Optimization（OIO） is a new optimization algorithm based on the principle of optics from physics. Because of the singularity of fitness function, weak searching ability and low precision of the basic Optics Inspired Optimization, this paper modifies the Optics Inspired Optimization algorithm by using the self-adaptive analysis of the genetic algorithm to improve the fixed fitness of the basic optics optimization algorithm, and thus proposes a kind of modified algorithm which is coded and implemented on computer. Series of typical benchmark instances are tested and solved. Results of computational experiments show the feasibility and effectiveness of the improved algorithm.

Key words: Optics Inspired Optimization（OIO）, fitness, genetic?algorithm, function optimization

摘要： 光学优化算法是一种新型优化算法，源自物理学中的光学原理。针对基本光学优化算法中适应度函数随进化过程恒定不变导致算法搜索能力差、精度低等不足之处，结合遗传算法中自适应度的改进方法，提出一种可随进化代数动态调整的非线性适应度函数，改进了光学优化算法的适应度函数。通过一系列典型的基准函数测试了改进算法的性能，实验结果验证了改进算法的可行性与有效性。

关键词: 光学优化算法, 适应度, 遗传算法, 函数优化