改进的蜣螂优化算法性能分析及其应用  

Performance analysis and application of improved dung beetle optimizer algorithm

作　　者：郝海霞 张磊 Hao Haixia;Zhang Lei(Jinzhong University,Jinzhong 030600,China)

机构地区：[1]晋中学院,晋中030600

出　　处：《国外电子测量技术》2024年第12期24-33,共10页Foreign Electronic Measurement Technology

基　　金：山西省立校项目(2021L493)资助。

摘　　要：针对传统蜣螂优化算法(DBO)容易陷入局部最优、收敛较慢、无法平衡局部开发和全局收敛等问题,提出了一种改进的蜣螂优化算法(IDBO)。首先,采用Logistic混沌映射的方法对种群进行随机初始化,结合折射反向学习策略对种群进行优化,增加了种群的多样性;其次,在繁殖阶段,利用螺旋搜索策略对位置更新的公式进行改进,提高了算法的收敛速度;最后在觅食阶段,通过最优值策略引入当前最优值来指导候选解的生成,提升了算法的全局搜索能力。将提出的IDBO算法与其他算法在10个基准测试函数上进行性能比较,IDBO算法在最优值方面均达到了最优,在标准差方面除了函数F5和F9外均达到最小,在收敛性方面,F_(1)~F_(4)以更快的速度收敛于最优值,F6~F_(10)收敛曲线趋于最优值更快且波动小,验证了IDBO算法的有效性、稳定性和收敛性。此外,将改进的IDBO算法应用于旅行商问题的求解,进一步验证了其实际应用的可行性和有效性。An improved beetle optimization algorithm(IDBO)is proposed to address the problems of traditional beetle optimization algorithm(DBO)being prone to local optima and slow convergence.Firstly,the population is initialized using logistic chaotic mapping,and optimized using the refraction reverse learning strategy to increase the diversity of the population.Secondly,during the breeding stage,the formula for position update was improved using a spiral search strategy,which increased the convergence speed of the algorithm.Finally,during the foraging phase,the current optimal value is introduced through the optimal value strategy to guide the generation of candidate solutions,enhancing the algorithm's global search capability.The proposed IDBO algorithm is compared with other algorithms on 10 benchmark test functions,and the results show that the IDBO algorithm reaches the value in terms of the optimal value,and the standard deviation is the smallest except for the function and,and in terms of convergence,it converges to the optimal at a faster speed,and the convergence curve tends to the optimal value faster and with less fluctuation,which verifies the effectiveness,stability and convergence of the IDBO.In addition,the enhanced IDBO algorithm was utilized to address the traveling salesman problem,further verifying its feasibility and effectiveness in practical applications.

关 键 词：蜣螂算法 LOGISTIC混沌映射 折射反向学习 螺旋搜索策略 旅行商问题 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] TN9[自动化与计算机技术—计算机科学与技术]