是否可以使用主标签来标记优化问题，并使用子标签来标记每一行？
例如，我想将优化问题标记为（AP），但我还想在单一方程环境中标记目标和每个约束。
这就是我能做的。
\documentclass{article}
\usepackage{amsmath}
\begin{document}
The assignment problem is the problem of assigning
agents $i = 1, 2, \ldots, N$
to tasks $j = 1, 2, \ldots N$
in order to minimize the total cost of the assignments.
Any agent could be assigned to any task,
incurring a cost that depends on the agent-task assignment.
The objective is to minimize the total cost of assignment.
\paragraph{Input data:}
\begin{itemize}
\item $N = $ number of agents $ = $ number of tasks
\item $c_{ij} = $ cost of assigning task $j$ to agent $i$
\end{itemize}
\paragraph{Decision variables:}
\begin{itemize}
\item $x_{ij} = 1$ if agent $i$ is assigned to task $j$,
$x_{ij} = 0$ otherwise
\end{itemize}
\paragraph{Optimization problem formulation:}
\begin{alignat}{3}
& \min\
&& \sum_{i=1}^N \sum_{j=1}^N c_{ij}x_{ij}
& \quad &
\label{objective}
\\
& \text{s.t.}
&& \sum_{i=1}^N x_{ij} = 1
&& \forall j \in \{1,2,\ldots,N\}
\label{each task must be assigned to an agent}
\\
&
&& \sum_{j=1}^N x_{ij} = 1
&& \forall i = \{1,2,\ldots,N\}
\label{each agent must be assigned to a task}
\\
&
&& 0 \leq x_{ij} \geq 1
&& \forall i \in \{1,2,\ldots,N\}, j \in \{1,2,\ldots,N\}
\label{binary variable constraint}
\end{alignat}
The objective \eqref{objective} is to minimize the total cost of assignment.
The constraint \eqref{each task must be assigned to an agent}
states that each task must be assigned to an agent.
The constraint \eqref{each agent must be assigned to a task}
states that each agent must be assigned to a task.
The constraint \eqref{binary variable constraint}
imposes binary lower and upper bounds on the assignment variables $x_{ij}$.
The assignment problem can be formulated as the following optimization problem
\begin{equation}
\tag{AP}
\label{assignment problem}
\begin{alignedat}{3}
& \min\
&& \sum_{i=1}^N \sum_{j=1}^N c_{ij}x_{ij}
& \quad &
\\
& \text{s.t.}
&& \sum_{i=1}^N x_{ij} = 1
&& \forall j \in \{1,2,\ldots,N\}
\\
&
&& \sum_{j=1}^N x_{ij} = 1
&& \forall i = \{1,2,\ldots,N\}
\\
&
&& 0 \leq x_{ij} \leq 1
&& \forall i \in \{1,2,\ldots,N\}, j \in \{1,2,\ldots,N\}
\end{alignedat}
\end{equation}
Are you looking for the formulation of the assignment problem?
It is in equation \eqref{assignment problem} above.
\end{document}
我希望输出类似于以下内容：
min sum sum c_ij x_ij (1)
(AP) s.t. sum_i x_ij = 1 (2)
sum_j x_ij = 1 (3)
0 <= x_ij <= 1 (4)
其中 (AP) 垂直对齐于中心，基本上是输出图像中两个方程的组合。
如果有更好的方法来实现主标签和子标签，我也想了解一下。
答案1
我假设您想用 (I) (II) 等替换 (AP)。您也可以轻松使用 (AP.1) 或 (A) 等。\rule 只是为了检查对齐。
这种方法的缺点是方程式不太居中。优点是您可以包含文本或很长的方程式而不会重叠。您甚至可以考虑使用 \llap 将作业编号移到左边距。
\documentclass{article}
\usepackage{amsmath}
\newcounter{AScount}
\renewcommand{\theAScount}{\Roman{AScount}}
\newlength{\ASlen}
\newenvironment{assignment}[1]% #1=label
{\refstepcounter{AScount}\label{#1}%
\ifvmode\noindent\else\newline\fi%
\makebox[\labelwidth][l]{(\theAScount)}%
\setlength{\ASlen}{\linewidth}%
\addtolength{\ASlen}{-\labelwidth}%
\minipage[c]{\ASlen}}%
{\endminipage}
\begin{document}
\noindent\rule{\textwidth}{1pt}
\begin{assignment}{assignment problem}
\begin{equation}
x=a
\end{equation}
\begin{equation}
y=b
\end{equation}
\end{assignment}
Assignment problem \eqref{assignment problem}.
\end{document}
答案2
这个问题可能之前有人问过。希望你能灵活应对环境alignat。我改用了align。抱歉，习惯使然。如果这对你不起作用，请发表评论。
\documentclass{article}
\usepackage{amsmath}
\makeatletter
\newenvironment{mysubeqns}[1]
{%
\addtocounter{equation}{-1}%
\begin{subequations}
\renewcommand{\theparentequation}{#1}%
\def\@currentlabel{#1}%
}
{%
\end{subequations}
}
\makeatother
\begin{document}
The assignment problem is the problem of assigning
agents $i = 1, 2, \ldots, N$
to tasks $j = 1, 2, \ldots N$
in order to minimize the total cost of the assignments.
Any agent could be assigned to any task,
incurring a cost that depends on the agent-task assignment.
The objective is to minimize the total cost of assignment.
\paragraph{Input data:}
\begin{itemize}
\item $N = $ number of agents $ = $ number of tasks
\item $c_{ij} = $ cost of assigning task $j$ to agent $i$
\end{itemize}
\paragraph{Decision variables:}
\begin{itemize}
\item $x_{ij} = 1$ if agent $i$ is assigned to task $j$,
$x_{ij} = 0$ otherwise
\end{itemize}
\paragraph{Optimization problem formulation:}
\begin{alignat}{3}
& \min\
&& \sum_{i=1}^N \sum_{j=1}^N c_{ij}x_{ij}
& \quad &
\label{objective}
\\
& \text{s.t.}
&& \sum_{i=1}^N x_{ij} = 1
&& \forall j \in \{1,2,\ldots,N\}
\label{each task must be assigned to an agent}
\\
&
&& \sum_{j=1}^N x_{ij} = 1
&& \forall i = \{1,2,\ldots,N\}
\label{each agent must be assigned to a task}
\\
&
&& 0 \leq x_{ij} \geq 1
&& \forall i \in \{1,2,\ldots,N\}, j \in \{1,2,\ldots,N\}
\label{binary variable constraint}
\end{alignat}
The objective \eqref{objective} is to minimize the total cost of assignment.
The constraint \eqref{each task must be assigned to an agent}
states that each task must be assigned to an agent.
The constraint \eqref{each agent must be assigned to a task}
states that each agent must be assigned to a task.
The constraint \eqref{binary variable constraint}
imposes binary lower and upper bounds on the assignment variables $x_{ij}$.
The assignment problem can be formulated as the following optimization problem
\begin{mysubeqns}{AP}
\label{eq:assignment problem}
\begin{align}
\min\ &\sum_{i=1}^N \sum_{j=1}^N c_{ij}x_{ij} && & \label{eq:assignment problem1} \\
\text{s.t.} &\sum_{i=1}^N x_{ij} = 1 && \forall j \in \{1,2,\ldots,N\} & \label{eq:assignment problem2} \\
&\sum_{j=1}^N x_{ij} = 1 && \forall i = \{1,2,\ldots,N\} &\label{eq:assignment problem3} \\
&0 \leq x_{ij} \leq 1 && \forall i \in \{1,2,\ldots,N\}, j \in \{1,2,\ldots,N\} &\label{eq:assignment problem4}
\end{align}
\end{mysubeqns}
Another equation
\begin{equation}
2=2
\end{equation}
Are you looking for the formulation of the assignment problem?
It is in equation \eqref{eq:assignment problem} above.
\end{document}