Linear Programming Tools and Approximation Algorithms for Combinatorial Optimization by
David Alexander Griﬃth Pritchard
A thesis presented to the University of Waterloo in fulﬁllment of the thesis requirement for the degree of Doctor of Philosophy in Combinatorics and Optimization
Waterloo, Ontario, Canada, 2009
c David Alexander Griﬃth Pritchard 2009
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required ﬁnal revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public.
Abstract We study techniques, approximation algorithms, structural properties and lower bounds related to applications of linear programs in combinatorial optimization. The following Steiner tree problem is central: given a graph with a distinguished subset of required vertices, and costs for each edge, ﬁnd a minimum-cost subgraph that connects the required vertices. We also investigate the areas of network design, multicommodity ﬂows, and packing/covering integer programs. All of these problems are NP-complete so it is natural to seek approximation algorithms with the best provable approximation ratio. Overall, we show some new techniques that enhance the already-substantial corpus of LP-based approximation methods, and we also look for limitations of these techniques. The ﬁrst half of the thesis deals with linear programming relaxations for the Steiner tree problem. The crux of our work deals with hypergraphic relaxations obtained via the well-known full component decomposition of Steiner trees; explicitly, in this view the fundamental building blocks are not edges, but hyperedges containing two or more required vertices. We introduce a new hypergraphic LP based on partitions. We show the new LP has the same value as several previously-studied hypergraphic ones; when no Steiner nodes are adjacent, we show that the value of the well-known bidirected cut relaxation is also the same. A new partition uncrossing technique is used to demonstrate these equivalences, and to show that extreme points of the new LP are well-structured. We improve the best known integrality gap on these LPs in some special cases. We show that several approximation algorithms from the literature on Steiner trees can be re-interpreted through linear programs, in particular our hypergraphic relaxation yields a new view of the Robins-Zelikovsky  1.55-approximation algorithm for the Steiner tree problem. The second half of the thesis deals with a variety of fundamental problems in combinatorial optimization. We show how to apply the iterated LP relaxation framework to the problem of multicommodity integral ﬂow in a tree, to get an approximation ratio that is asymptotically optimal in terms of the minimum capacity. Iterated relaxation gives an infeasible solution, so we need to ﬁnesse it back to feasibility without losing too much value. Iterated LP relaxation similarly gives an O(k 2 )-approximation algorithm for packing integer programs with at most k occurrences of each variable; new LP rounding techniques give a k-approximation algorithm for covering integer programs with at most k variable per constraint. We study extreme points of the standard LP relaxation for the traveling salesperson problem and show that they can be much more complex than was previously known. The k-edge-connected spanning multi-subgraph problem has the same LP and we prove a lower bound and conjecture an upper bound on the approximability of variants of this problem. Finally, we show that for packing/covering integer programs with a bounded number of constraints, for any ǫ > 0, there is an LP with integrality gap at most 1 + ǫ.
Acknowledgements I warmly thank my family in Scarborough — Karen, Bradley and Hilary — for their support throughout my studies, especially their cheerful hospitality during random unannounced visits. I thank my friends, my...
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