【智能优化算法】基于人工兔群优化算法求解单目标优化问题附matlab代码

原创已于 2022-05-26 22:57:33 修改 · 410 阅读

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于 2022-05-25 18:16:18 首次发布

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本文介绍了一种新的生物启发式元启发式优化算法——人工兔子优化(ARO)，该算法适用于解决工程优化问题。提供了在MATLAB R2011b环境下实现ARO算法的代码示例，并展示了算法运行的仿真结果。

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)]);