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Lattice-based approaches to integer optimization - a tutorial
Student-Run Discrete Mathematics| Speaker: | Bala Krishnamoorthy, Washington State University |
| Location: | 2112 MSB |
| Start time: | Thu, Apr 29 2010, 12:10PM |
Description
This tutorial will introduce the fundamentals of lattices,
and problems on lattices such as the shortest vector problem (SVP) and
closest vector problem (CVP). We will discuss these problems from a
computational complexity point of view. Basis reduction (BR) is one of
the widely used methods to solve instances of SVP and CVP
approximately. After motivating procedures for BR in two dimensions,
we will discuss BR algorithms in general. We will also talk about the
efficiencies of such algorithms in practice. BR is one of the key
steps in Lenstra-type algorithms for solving integer optimization or
integer programming (IP) problems in polynomial time when the
dimension is fixed. But such algorithms have not been implemented so
far. We will focus on BR-based approaches to IP that have sound
mathematical foundations but have also proven effective in
practice. We will discuss BR-based reformulations for general IP
instances, and the effectiveness of standard branch-and-bound
approaches for solving these instances. We will also discuss
lattice-based approaches to specific class of problems such as number
partitioning.
