Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.697137
Title: The complexity of greedy algorithms on ordered graphs
Author: Puricella, Antonio
Awarding Body: University of Leicester
Current Institution: University of Leicester
Date of Award: 2002
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Abstract:
Let p be any fixed polynomial time testable, non-trivial, hereditary property of graphs. Suppose that the vertices of a graph G are not necessarily linearly ordered but partially ordered, where we think of this partial order as a collection of (possibly exponentially many) linear orders in the natural way. In the first part of this thesis, we prove that the problem of deciding whether a lexicographically first maximal (with respect to one of these linear orders) subgraph of G satisfying p, contains a specified vertex is NP-complete. For some of these properties p we then show that by applying certain restrictions the problem still remains NP-complete, and show how the problem can be solved in deterministic polynomial time if the restrictions imposed become more severe. Let H be a fixed undirected graph. An H-colouring of an undirected graph G is a homomorphism from G to H. In the second part of the thesis, we show that, if the vertices of G are partially ordered then the complexity of deciding whether a given vertex of G is in a lexicographically first maximal H-colourable subgraph of G is NP-complete, if H is bipartite, and Sp2-complete, if H is non-bipartite. We then show that if the vertices of G are linearly, as opposed to partially, ordered then the complexity of deciding whether a given vertex of G is in the lexicographically first maximal H-colourable subgraph of G is P-complete, if H is bipartite, and DP2-complete, if H is non-bipartite. In the final part of the thesis we show that the results obtained can be paralleled in the setting of graphs where orders are given by degrees of the vertices.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.697137  DOI: Not available
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