Th original version of this algorithm can be found here:http://au.mathworks.com/matlabcentral/fileexchange/52269-moth-flame-optimization--mfo--algorithm All of the source codes and extra information as well as
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In this paper, a novel Moth-Flame Optimization (MFO) algorithm, namely MFO algorithm enhanced by Multiple Improvement Strategies (MISMFO) is proposed for solving parameter optimization in Multi-Kernel Support Vector Regressor (MKSVR), and the MISMFO-MKSVR model is further employed to deal with ...
如果用Matlab画图就发现2D解空间中Moth并不是绕螺旋线。所谓螺旋线只是让Moth解中每一维的元素有更大取值空间(更强的开发能力exploitation),因为他让新Moth取值不局限于Flame和旧Moth,可以大于这两点,可以小于这两点,也可以在两点之间活动。这是圆的优势,而粒子群PSO的直线让新粒子只能选最优粒子和旧粒子之间的值。
This paper presents a novel hybrid algorithm, the Moth-Flame Particle Swarm Optimization (MFPSO), which combines moth-flame optimization (MFO) and particle swarm optimization (PSO) to address the slow convergence of MFO and the premature convergence of PSO. The MFPSO is deployed for real-time ...
To enhance the performance of the DSR, a novel and efficient routing mechanism based on a hybrid approach using the minimum execution time (MET) scheduling and moth flame optimization (MFO) scheme is proposed. This hybridization version of DSR is called the (MET-MFODSR) algorithm, and it ...
Algorithm 1: Improved Moth-Flame Optimization Algorithm Input: case data, number of iterations, population size Output: the best solutions 1: Initialize the moth population as solutions. 2: while (t < maximum number of iterations) do 3: for each individual do 4: The objective function value ...