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Diffstat (limited to 'Master/texmf-dist/doc/latex/thuthesis/data/appendix-survey.tex')
-rw-r--r-- | Master/texmf-dist/doc/latex/thuthesis/data/appendix-survey.tex | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/Master/texmf-dist/doc/latex/thuthesis/data/appendix-survey.tex b/Master/texmf-dist/doc/latex/thuthesis/data/appendix-survey.tex index a3c5ef6205a..5c09088a383 100644 --- a/Master/texmf-dist/doc/latex/thuthesis/data/appendix-survey.tex +++ b/Master/texmf-dist/doc/latex/thuthesis/data/appendix-survey.tex @@ -119,7 +119,7 @@ extreme point is the optimal solution. \subsection{Nonlinear Programming} -If at least one of the functions $f(x),g_j(x),j=1,2,\cdots,p$ is nonlinear, then +If at least one of the functions $f(x),g_j(x),j=1,2,\dots,p$ is nonlinear, then SOP is called a \emph{nonlinear programming}. A large number of classical optimization methods have been developed to treat @@ -167,7 +167,7 @@ the \emph{branch-and-bound enumeration} developed by Balas (1965) and Dakin \hfill\textit{Uncertain Programming\/}\quad(\textsl{BaoDing Liu, 2006.2}) -\bibliographystyle{plainnat} +\bibliographystyle{unsrtnat} \bibliography{ref/refs,ref/appendix} \end{survey} |