When integer programming (IP) models are used in operational situations there is a need to consider the tradeoff between the conflicting goals of solution quality and solution time, since for many problems solving realistic-size instances to a tight tolerance is still beyond the capability of state-of-the-art solvers. However, by appropriately defining small instances, good primal solutions frequently can be found quickly. We explore this approach in this thesis by studying the design of algorithms that produce solutions to an integer program by solving restrictions of the problem via integer programming technology. We refer to this type of algorithm as IP-based search and present algorithms for network design problems of both real-world and academic interest. Along with algorithms that exploit the structure of the problem studied we also present a general integer programming algorithm that uses column generation to choose the restrictions to solve.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/31641 |
| Date | 21 August 2009 |
| Creators | Hewitt, Michael R. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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