1 files changed, 11 insertions, 10 deletions
diff --git a/Master/texmf-dist/doc/latex/thuthesis/data/appendix01.tex b/Master/texmf-dist/doc/latex/thuthesis/data/appendix01.tex
index a98b36a2073..f34536ed5b7 100644
--- a/Master/texmf-dist/doc/latex/thuthesis/data/appendix01.tex
+++ b/Master/texmf-dist/doc/latex/thuthesis/data/appendix01.tex
@@ -20,25 +20,26 @@ throughout the book$^{[2,3]}$.
 \section{Single-Objective Programming}
 The general form of single-objective programming (SOP) is written
 as follows,
-\begin{equation}\tag*{(123)} % 如果附录中的公式不想让它出现在公式索引中，那就请
-                             % 用 \tag*{xxxx}
+\begin{equation*} % 如果附录中的公式不想让它出现在公式索引中，那就请
+                             % 用 equation*
 \left\{\begin{array}{l}
 \max \,\,f(x)\\[0.1 cm]
 \mbox{subject to:} \\ [0.1 cm]
 \qquad g_j(x)\le 0,\quad j=1,2,\cdots,p
 \end{array}\right.
-\end{equation}
+\end{equation*}
 which maximizes a real-valued function $f$ of
 $x=(x_1,x_2,\cdots,x_n)$ subject to a set of constraints.
 
+\newcommand\Real{\mathbf{R}}
 \newtheorem{mpdef}{Definition}[chapter]
 \begin{mpdef}
 In SOP, we call $x$ a decision vector, and
 $x_1,x_2,\cdots,x_n$ decision variables. The function
 $f$ is called the objective function. The set
-\begin{equation}\tag*{(456)} % 这里同理，其它不再一一指定。
-S=\left\{x\in\Re^n\bigm|g_j(x)\le 0,\,j=1,2,\cdots,p\right\}
-\end{equation}
+\begin{equation*}
+S=\left\{x\in\Real^n\bigm|g_j(x)\le 0,\,j=1,2,\cdots,p\right\}
+\end{equation*}
 is called the feasible set. An element $x$ in $S$ is called a
 feasible solution.
 \end{mpdef}
@@ -127,15 +128,15 @@ special-structural nonlinear programming based on the mathematical theory
 concerned with analyzing the structure of problems.
 \begin{figure}[h]
   \centering
-  \includegraphics{thu-lib-logo}
+  \includegraphics{thu-lib-logo.pdf}
   \caption*{Figure~1\quad This is an example for manually numbered figure,
     which would not appear in the list of figures}
   \label{tab:badfigure2}
 \end{figure}
 
 Now we consider a nonlinear programming which is confronted solely with
-maximizing a real-valued function with domain $\Re^n$.  Whether derivatives are
-available or not, the usual strategy is first to select a point in $\Re^n$ which
+maximizing a real-valued function with domain $\Real^n$.  Whether derivatives are
+available or not, the usual strategy is first to select a point in $\Real^n$ which
 is thought to be the most likely place where the maximum exists. If there is no
 information available on which to base such a selection, a point is chosen at
 random. From this first point an attempt is made to construct a sequence of
@@ -238,7 +239,7 @@ the {\em branch-and-bound enumeration} developed by Balas (1965) and Dakin
 跖，为天下害，而弗能教也，丘窃为先生羞之。丘请为先生往说之。”
 \begin{figure}[h]
   \centering
-  \includegraphics{thu-whole-logo}
+  \includegraphics{thu-whole-logo.pdf}
   \caption*{图~1\hskip1em 这是手动编号但不出现索引中的图片的例子}
   \label{tab:badfigure3}
 \end{figure}