💥💥💥💞💞💞欢迎来到本博客❤️❤️❤️💥💥💥
📝目前更新：🌟🌟🌟智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真。
🎉🎉欢迎您的到来🎉🎉
⛅⛅⛅ 📃CSDN主页：Matlab科研室🌈🌈🌈
📚📚📚📋所有代码目录见微信公众号：天天Matlab👨•💻👨•💻👨•💻
1 内容介绍
Jaya算法是一种基于群体的新兴智能优化算法,该算法区别于其他优化算法,具有无参数运行、求解速度快、不易陷入局部最优解等优点.自Jaya算法被提出以来,已经被广泛应用于诸多领域,并取得了卓越的成果,例如图像识别、机械设计、机器学习等.
2 仿真代码
clear all
close all
clc
%--------------------------------------------------------------------------
options.ObjFunctinotallow=@Binh;
options.ll=[-5 -5];% lower bounds
options.ul=[10 10]; % upper bounds
options.clsize=100; % Size of the population
options.nArchive=50; % Archive Size of the Pareto front
options.Nobj=2; % number of Objective Functions
options.var_num=size(options.ll,2); % dimension of the problem.
options.iteratinotallow=100; % Maximum number of iterations
%--------------------------------------------------------------------------
options.Display_Flag=1; % Flag for displaying results over iterations
options.run_parallel_index=0;
options.run=1;
tic
if options.run_parallel_index
stream = RandStream('mrg32k3a');
parfor index=1:options.run
% index
set(stream,'Substream',index);
RandStream.setGlobalStream(stream)
[bestX, bestFitness, bestFitnessEvolution]=MOJAYA_v1(options);
RESULTS{index}.bestX=bestX;
RESULTS{index}.bestFitness=bestFitness;
RESULTS{index}.bestFitnessEvolutinotallow=bestFitnessEvolution;
end
else
rng('default')
for index=1:options.run
% index
[bestX, bestFitness, bestFitnessEvolution]=MOJAYA_v1(options);
RESULTS{index}.bestX=bestX;
RESULTS{index}.bestFitness=bestFitness;
RESULTS{index}.bestFitnessEvolutinotallow=bestFitnessEvolution;
end
end
toc
3 运行结果
4 参考文献
[1]王建华, 潘宇杰, 孙瑞. 自适应Jaya算法求解多目标柔性车间绿色调度问题[J]. 2021.