亲测有效
1、导入依赖包：
\usepackage[ruled]{algorithm2e}
\begin{
algorithm}[] %其中这里面不能有H不然会报错，不过不影响结果
\caption{
algorithm caption}%算法名字
\LinesNumbered %要求显示行号
\KwIn{
input parameters A, B, C}%输入参数
\KwOut{
output result}%输出
some description\; %\;用于换行
\For{
condition}{
only if\;
\If{
condition}{
1\;
}
}
\While{
not at end of this document}{
if and else\;
\eIf{
condition}{
1\;
}{
2\;
}
}
\ForEach{
condition}{
\If{
condition}{
1\;
}
}
\end{
algorithm}
2、导入依赖包：
\usepackage[noend]{algpseudocode}
\usepackage{algorithmicx,algorithm}
\begin{algorithm}[t]
\caption{algorithm caption} %算法的名字
\hspace*{0.02in} {\bf Input:} %算法的输入， \hspace*{0.02in}用来控制位置，同时利用 \\ 进行换行
input parameters A, B, C\\
\hspace*{0.02in} {\bf Output:} %算法的结果输出
output result
\begin{algorithmic}[1]
\State some description % \State 后写一般语句
\For{condition} % For 语句，需要和EndFor对应
\State ...
\If{condition} % If 语句，需要和EndIf对应
\State ...
\Else
\State ...
\EndIf
\EndFor
\While{condition} % While语句，需要和EndWhile对应
\State ...
\EndWhile
\State \Return result
\end{algorithmic}
\end{algorithm}
3、导入依赖包：
%\usepackage{algorithm}
%\usepackage{algorithmicx}
%\usepackage{algpseudocode} % 如果不想在算法伪代码模块中显示 end for 和 end while，则使用 %\usepackage[noend]{algpseudocode}
\begin{algorithm}[h]
\renewcommand{\algorithmicrequire}{\textbf{Input:}}
\renewcommand{\algorithmicensure}{\textbf{Output:}}
\caption{Environmental Selection}
\label{alg::conjugateGradient}
\begin{algorithmic}[1]
\Require
The population $ P_t $,the probabity for crossover operation
$ p_c $, the probability for mutation operation $ p_m $,
the mutation operation list $ l_m $,the probabilities
of selecting different mutation operations $ p_l $.
\Ensure
The offspring population $ Q_t $;
\State $ Q_t $ ← $\phi$;
\Repeat
\State $ p_1 $ ← Randomly select two individuals from $ P_t $,
and from the two then select the one with the better fitness;
\State $ p_2 $ ← Repeat Line 4;
\Repeat
\State Repeat Line 5;
\Until{($ p_1 $ == $ p_2 $)}
%\whiledo{$ p_1 $ == $ p_2 $}{\State Repeat Line 5;}
\State $ r $ ← Randomly generate a number from (0,1);
\Until{($\lvert Q_t \rvert < \lvert P_t \rvert$)}
\State Return the individual having the best fitness in $P_t$;
\end{algorithmic}
\end{algorithm}
