From b04ac0a038f4733c6c008af35da0e0577c34d286 Mon Sep 17 00:00:00 2001
From: msurl <masur101@hhu.de>
Date: Wed, 3 Jun 2020 12:16:59 +0200
Subject: [PATCH] added notes to myself
---
Latex/ilp.tex | 8 +++++---
1 file changed, 5 insertions(+), 3 deletions(-)
diff --git a/Latex/ilp.tex b/Latex/ilp.tex
index cf5be82..04b72f9 100644
--- a/Latex/ilp.tex
+++ b/Latex/ilp.tex
@@ -11,11 +11,13 @@ $x \in \mathbb{R}$ is a vector describing possible solutions. If $x \in \mathbb{
Integer linear programms (ILPs) are linear programms with the additional restriction that all variables have to be integers: $x \in \mathbb{Z}$.
The decision variant of an ILP is NP-complete.
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-In this thesis we use a more readable notation which does not completely sticks to this definition. We write down the inequalities in a sum notation. (Maybe an example?) But it is possible to transform them into the matrix notation.
+In this thesis we use a more readable notation which does not completely sticks to this definition. We write down the inequalities(and the objective function?) in a sum notation. (Maybe an example?) But it is possible to transform them into the matrix notation.
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-Decision problems can be modelles with ILPs. Every variable $x_i \in \{0,1\}$ denotes a possible decision. In our case we assign a decision variable for each vertex to decide if it is included in a dominating set or not.
-
+Decision problems(combinatorical optimisation problems?/ \textbf{Decisions}. Not Decision Problems) can be modelled with ILPs. Every variable $x_i \in \{0,1\}$ denotes a possible decision(To include or not?). In our case we assign a decision variable for each vertex to decide if it is included in a dominating set or not.
+\\
+\\
+(Maybe to "formal". Maybe introduce the used notation right away and try to find textbook or publication which also uses this notation to cite)
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