From: Mart Lubbers <mart@martlubbers.net>
Date: Wed, 18 Jun 2014 20:43:49 +0000 (+0200)
Subject: Skeleton for report, small solver changes
X-Git-Url: https://git.martlubbers.net/?a=commitdiff_plain;h=056bb5864aa199b194a86dd2d3b5490c88d8713c;p=co1314.git

Skeleton for report, small solver changes
---

diff --git a/LubbersReport.tex b/LubbersReport.tex
index b2a9422..abda695 100644
--- a/LubbersReport.tex
+++ b/LubbersReport.tex
@@ -1,11 +1,20 @@
 \documentclass{article}
 
+\usepackage{listings}
 \usepackage[dvipdfm]{hyperref}
 
+\lstset{
+	basicstyle=\footnotesize,
+	breaklines=true,
+	numbers=left,
+	numberstyle=\tiny,
+	tabsize=2
+}
+
 \author{
 	Mart Lubbers\\
 	s4109503\\
-	\url{mailto:mart@martlubbers.net}
+	\href{mailto:mart@martlubbers.net}{mart@martlubbers.net}
 }
 \title{Complexity Assignment}
 \date{\today}
@@ -13,9 +22,46 @@
 \begin{document}
 \maketitle
 \tableofcontents
-\section{Introduction}
+\newpage
+
+\section{Problem description}
+\begin{center}
+	\textit{
+		Every day children come to the zoo to take care of the pets. After an
+		introductory meeting with all the pets, the kids are given one pet to
+		exclusively take care of for the rest of the visit. However, certain pets
+		do not go on well with certain kids, and vice-versa. Pets are also not
+		immortal; and the groups vary in size from time to time. Because these pets
+		require very special attention, exactly one child can take care of a single
+		pet. This implies that sometimes a child does not have a pet to take care
+		for and sometimes a pet is left without a caretaker.
+	}
+\end{center}
+
+The assignment is to implement a \textit{\href{http://www.java.com}{Java}}
+program that optimizes the assignment of pets to children so that the sum of
+all the compatibility values between pets and children is the maximum possible.
 
 \section{Implementation}
+\subsection{Brute Force}
+The first approach was to implement a brute force algorithm which calculates
+every possible combination of pets and children and then takes the one with the
+highest value. This corresponds with the pseudocode specified in
+Listing~\ref{lst:brute_force}. The algorithm, due to calculating all the values
+has a minimal complexity of $n!$. This is because there are $n!$ permutations
+possible for $n$ children.
+\begin{lstlisting}[
+	caption={Brute Force approach},
+	label={lst:brute_force},
+	keywords={[3]loop,put,return}
+]
+n! - loop over all permutations
+c1 -   put compatibility in list
+c1 - return maximum compatibility rating from list
+\end{lstlisting}
+
+
+\subsection{Improvements}
 
 \section{Conclusion}
 
diff --git a/LubbersSolver.java b/LubbersSolver.java
index bdb4ded..571bb26 100755
--- a/LubbersSolver.java
+++ b/LubbersSolver.java
@@ -77,27 +77,15 @@ public class LubbersSolver implements IPetproblemSolver {
 		for(int i = 0; i<n; i++){
 			possibilities[i] = i>=m ? -1 : i;
 		}
-		if(m<=n){
-			System.out.println("Wierd shizzleeee");
-			List<int[]> ps = new LinkedList<int[]>();
-			permute(possibilities, 0, ps);
-			for(int[] i : ps){
-				System.out.println(computeCompatibility(compatibility, i) + ": " + Arrays.toString(i));
-			}
-			System.exit(0);
 
-			return Collections.max(ps, new Comparator<int[]>(){
-				@Override
-				public int compare(int[] a, int[] b){
-					return computeCompatibility(compatibility, a) - computeCompatibility(compatibility, b);
-				}
-			});
-		}
-		else {
-			System.out.println("not equal...");
-			return new int[n];
-			//return null;
-		}
-		
+		List<int[]> ps = new LinkedList<int[]>();
+		permute(possibilities, 0, ps);
+
+		return Collections.max(ps, new Comparator<int[]>(){
+			@Override
+			public int compare(int[] a, int[] b){
+				return computeCompatibility(compatibility, a) - computeCompatibility(compatibility, b);
+			}
+		});
 	}
 }