三种常见现代优化算法的比较.pdfVIP

Value Engineering · · 301 三种常见现代优化算法的比较 Studies on Three Modern Optimization Algorithms 郝思齐 HAO Si-qi曰池慧 CHI Hui （华北水利水电大学，郑州 ） 450011 （ ， ， ） North China University of Water Resources and Electric Power Zhengzhou 450011 China 摘要院 现代最优化算法比较常见的有遗传算法、蚁群算法、粒子群算法、鱼群算法和模拟退火算法。这些算法主要是解决优化问 题中的难解问题。文章主要是对遗传算法、粒子群算法和模拟退火算法三个算法的优化性能进行比较。首先介绍了三个算法的基本思 想，以此可以了解三种算法有着自身的特点和优势，而后用这三种算法对典型函数进行计算，并对优化结果比较分析，提出了今后研 究的方向。 Abstract: Modern optimization includes genetic algorithm (GA), ant colony algorithm (ACO), particle swarm algorithm optimization (PSO), fish-swarm algorithm and simulated annealing algorithm (SA) and so on. They are mainly applied to solve some difficult optimization problems. The paper mainly makes a comparative study of the optimization performance of GA, PSO and SA. First the basic principles of the three algorithms are introduced, and the characteristics and advantages of these algorithms are understood. At last, the three algorithms are used for typical functions calculation, and comparative analysis is made to the results. And the future research directions are put forward. 关键词院 遗传算法；粒子群算法；模拟退火算法；比较；优化 Key words: （ ）； ； ； ； genetic algorithm GA particle swarm algorithm optimization (PSO) simulated annealing algorithm (SA) comparison optimization 中图分类号院 文献标识码院 文章编号院 （ ）