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--- info:tech_report_example.tex [1998/12/03 12:11]
+++ info:tech_report_example.tex [2016/03/25 16:46]
sertalpbilal
@@ Line 1: / Line 1: @@
+<code latex tech_report_example.tex>
+\def\coralreport{1}
+%\documentclass{./llncs2e/llncs}
+\documentclass{article}
+\usepackage{ifthen}
+%\usepackage{float}
+\usepackage{complexity}
+\usepackage{algorithm} % for algorithm environment
+\usepackage{algpseudocode} % for algorithmic environment
+   %\usepackage[pdftex]{graphicx} for pdflatex
+   %\usepackage{graphicx} for latex
+\usepackage{amsmath}
+\usepackage{amssymb}
+\usepackage{graphicx}
+\usepackage[authoryear]{natbib}
+% for tiles and keywords
+\usepackage{authblk}
+\usepackage{geometry}
+\usepackage{fullpage}
+\newtheorem{theorem}{Theorem}
+\newtheorem{claim}{Claim}
+\newtheorem{definition}{Definition}
+\renewcommand{\Re}{\mathbb{R}}
+\algdef{SE}[DOWHILE]{Do}{doWhile}{\algorithmicdo}[1]{\algorithmicwhile\ #1}
+% todo(aykut) this will create a problem with \P command of complexity package.
+\renewcommand{\P}{\mathcal{P}}
+\setlength{\evensidemargin}{0in}
+\setlength{\oddsidemargin}{0in}
+\setlength{\parindent}{0in}
+\setlength{\parskip}{0.06in}
+\ifthenelse{\coralreport = 1}{
+\usepackage{isetechreport}
+\def\reportyear{15T}
+% The report number is the same one used in the ISE tech report series
+\def\reportno{001}
+% This is the revision number (increment for each revision)
+\def\revisionno{0}
+% This is the date f the original report
+\def\originaldate{March 13, 2015}
+% This is the date of the latest revision
+\def\revisiondate{March 13, 2015}
+% Set these variables according to whether this should be a CORAL or CVCR
+% report
+\coralfalse
+\cvcrfalse
+\isetrue
+}{}
+\begin{document}
+\title{On the Complexity of Inverse MILP}
+\ifthenelse{\coralreport = 1}{
+  \author{Aykut Bulut\thanks{E-mail: \texttt{aykut@lehigh.edu}}}
+  \author{Ted K. Ralphs\thanks{E-mail: \texttt{ted@lehigh.edu}}}
+  \affil{Department of Industrial and Systems Engineering, Lehigh University, USA}
+  \titlepage
+}{
+  \author{Aykut Bulut}
+  \author{Ted K. Ralphs}
+  \affil{COR@L Lab, Department of Industrial and Systems Engineering, Lehigh University, USA}
+  \date{\today}
+}
+\maketitle
+\begin{abstract}
+Inverse optimization problems determine problem parameters that are closest to
+the estimates and will make a given solution optimum. In this study we work
+inverse \textbf{m}ixed \textbf{i}nteger \textbf{l}inear \textbf{p}roblems (MILP)
+where we seek the objective function coefficients. This is the inverse problem
+\cite{AhujaSeptember2001} studied for linear programs (LP). They
+show that inverse LP can be solved in polynomial time under mild conditions. We
+extend their result for the MILP case. We prove that the decision version of
+the inverse MILP is $\coNP$--complete. We also propose a cutting plane algorithm for
+solving inverse MILPs for practical purposes.
+\ifthenelse{\coralreport = 0}{
+\bigskip\noindent
+{\bf Keywords:} Inverse optimization, mixed integer linear program,
+computational complexity, polynomial hierarchy
+}{}
+\end{abstract}
+\section{Introduction}
+\label{sec:introduction}
+Optimization problems arise in many fields ...
+\end{document}
+</code>

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