量子光学优化算法

Quantum-behaved optics inspired optimization

通过分析光学优化算法的特性,将光学优化算法中每个光源点都用量子空间中的一个粒子来描述,利用群体智慧的聚集性,建立了光学优化算法的量子势能场模型,并根据势能场模型的群体自组织性和协同性等特点提出了量子光学优化算法。通过对多个经典测试函仿真分析,得出量子光学优化算法在量子力学收敛理论下比光学优化算法控制参数少,设置简单,优化性能更好,收敛速度更快,优化了算法的收敛精度和速度。

By analyzing the character of optics optimization algorithm,this paper described every light point in the algorithm as a particle in the quantum space and found the quantum potential field model with the aggregation of swarm intelligence.Because of the points of self-organize and cooperation,this paper raised the quantum-behaved optics algorithm.Using several functions to analyze,the results show that the algorithm with the theory of quantum mechanics has fewer control parameters and simpler setup,and it has better performance and faster convergent speed than OIO algorithms.