Abstract
We propose approximation algorithms for some facility location and
graph partitioning problems. Since most of the practically
important facility location and graph partitioning problems are
NP-Hard, the researchers are interested in approximation
algorithms of these problems. The major part of this thesis
presents approximation algorithms with better approximation ratio
for some already established important problems and the remaining
part proposes new problems with clear practical motivations.
We present a 8.29 factor LP-rounding based approximation algorithm
for the connected facility location problem which improves the
previous factor 8.55. Our algorithm gives a 7.00 approximation
ratio for the special case of the connected facility location
problem when all facilities have equal opening cost. We also give
a primal-dual based approximation algorithm for the connected
facility location problem with 6.55 approximation ratio. For the
lower bounded facility location problem we give a 322 + $\epsilon$
factor approximation algorithm which improves the previous factor
which is 558+$\epsilon$.
We study the minimum geometric mean layout (MGML) problem. In an
instance of the MGML problem we are given a graph $G=(V, E)$. The
objective is to find a one-to-one mapping $f:V \rightarrow \{1, 2,
..., |V|\}$ such that the cost $\sum_{\{u,v\} \in E} \log
(|f(u)-f(v)|)$ is minimized. Given graph $G=(V, E)$ representing a
polygonal mesh and one-to-one function $f: V \rightarrow \{1, 2,
..., |V|\}$ as the layout of the mesh in the main memory, Yoon and
Lindstrom [51] have shown that the number
of cache misses while accessing the mesh in the data layout has a
high linear correlation with the geometric mean of arc
lengths: $2^{\frac{1}{|E|}\sum_{\{u,v\} \in E} \log
(|f(u)-f(v)|)}$. Thus, getting a good solution to the minimum
geometric mean layout problem implies getting a good mesh
layout in terms of the number of cache misses for common computer
graphics application...