CAJ | 학술논문

萤火虫算法（ FA）是一种基于群体搜索的启发式随机优化算法，其模拟自然界中萤火虫利用发光的生物学特性而表现出来的社会性行为。针对萤火虫算法存在着收敛速度慢、易陷入局部最优、求解精度低等不足，利用单纯形法局部搜索速度快和萤火虫算法全局寻优的特点，提出一种基于单纯形法的改进型萤火虫算法（ SMFA）。通过对标准测试函数以及非线性方程组的实验仿真，并与其他算法进行的对比分析表明，改进后的算法在函数优化方面有较强的优势，在一定程度上有效地避免了陷入局部最优，提高了搜索的精度。
형화충산법（ FA）시일충기우군체수색적계발식수궤우화산법，기모의자연계중형화충이용발광적생물학특성이표현출래적사회성행위。침대형화충산법존재착수렴속도만、역함입국부최우、구해정도저등불족，이용단순형법국부수색속도쾌화형화충산법전국심우적특점，제출일충기우단순형법적개진형형화충산법（ SMFA）。통과대표준측시함수이급비선성방정조적실험방진，병여기타산법진행적대비분석표명，개진후적산법재함수우화방면유교강적우세，재일정정도상유효지피면료함입국부최우，제고료수색적정도。
The firefly algorithm ( FA) is a heuristic random optimization algorithm based on groupization. It simu?lates the social behavior of firefly in the natural environment represented in its biological characteristics of shining. FA has disadvantages in global searching, such as slow convergence speed, high possibility of being trapped in lo?cal optimum and low solving precision. An improved FA based on the simplex method is proposed. The proposed method combines the characteristics of speedy local search of simplex method with the global optimization of firefly algorithm. The simplex method modifies the firefly, which is located at poor positions through its reflection, expan?sion and compression operation. However, it improves the diversity of individuals and avoids falling into local opti?mum and improves the precision of the algorithm. The results showed that through simulations of standard bench?mark functions and nonlinear functions and contrasted with other algorithms, the improved algorithm has a strong advantage in function optimization. It also avoids trapping in local optimum and improves the calculation accuracy to a certain extent.