智能优化算法如何应用人工兔群算法解决单目标问题并附Matlab实现?

2026-06-09 16:566阅读0评论SEO基础
  • 内容介绍
  • 文章标签
  • 相关推荐

本文共计282个文字,预计阅读时间需要2分钟。

智能优化算法如何应用人工兔群算法解决单目标问题并附Matlab实现?

1. 简介 + Artificial Rabbits Optimization (ARO):一种新颖的仿生元启发式算法,用于解决工程优化问题

2.部分代码 + -------------------------------------------------------------------------- +

+-------------------------------------------------------------------------- ++ Artific


智能优化算法如何应用人工兔群算法解决单目标问题并附Matlab实现?

1 简介

Artificial rabbits optimization (ARO): a new bio-inspired meta-heuristic algorithm for solving engineering optimization problems

2 部分代码

%--------------------------------------------------------------------------
%%% Artificial Rabbits Optimization (ARO) for 23 functions %%%
% ARO code v1.0.
% Developed in MATLAB R2011b
% --------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%BestX:The best solution %
% BestF:The best fitness %
% HisBestF:History of the best fitness %
% FunIndex:Index of functions %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clc;
clear;
MaxIteration=1000;
PopSize=50;
FunIndex=1;
[BestX,BestF,HisBestF]=ARO(FunIndex,MaxIteration,PopSize);
% display(['FunIndex=', num2str(FunIndex)]);
display(['The best fitness of F',num2str(FunIndex),' is: ', num2str(BestF)]);
%display(['The best solution is: ', num2str(BestX)]);
if BestF>0
semilogy(HisBestF,'r','LineWidth',2);
else
plot(HisBestF,'r','LineWidth',2);
end
xlabel('Iterations');
ylabel('Fitness');
title(['F',num2str(FunIndex)]);

3 仿真结果

编辑

4 参考文献


博主简介:擅长智能优化算法、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,相关matlab代码问题可私信交流。


本文共计282个文字,预计阅读时间需要2分钟。

智能优化算法如何应用人工兔群算法解决单目标问题并附Matlab实现?

1. 简介 + Artificial Rabbits Optimization (ARO):一种新颖的仿生元启发式算法,用于解决工程优化问题

2.部分代码 + -------------------------------------------------------------------------- +

+-------------------------------------------------------------------------- ++ Artific


智能优化算法如何应用人工兔群算法解决单目标问题并附Matlab实现?

1 简介

Artificial rabbits optimization (ARO): a new bio-inspired meta-heuristic algorithm for solving engineering optimization problems

2 部分代码

%--------------------------------------------------------------------------
%%% Artificial Rabbits Optimization (ARO) for 23 functions %%%
% ARO code v1.0.
% Developed in MATLAB R2011b
% --------------------------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%BestX:The best solution %
% BestF:The best fitness %
% HisBestF:History of the best fitness %
% FunIndex:Index of functions %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clc;
clear;
MaxIteration=1000;
PopSize=50;
FunIndex=1;
[BestX,BestF,HisBestF]=ARO(FunIndex,MaxIteration,PopSize);
% display(['FunIndex=', num2str(FunIndex)]);
display(['The best fitness of F',num2str(FunIndex),' is: ', num2str(BestF)]);
%display(['The best solution is: ', num2str(BestX)]);
if BestF>0
semilogy(HisBestF,'r','LineWidth',2);
else
plot(HisBestF,'r','LineWidth',2);
end
xlabel('Iterations');
ylabel('Fitness');
title(['F',num2str(FunIndex)]);

3 仿真结果

编辑

4 参考文献


博主简介:擅长智能优化算法、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,相关matlab代码问题可私信交流。