Let G be a graph and c(i) be a scoring function that assigns a nonnegative real number to each partition of vertices into n disjoint sets. We create an algorithm for finding a partition that minimizes the scoring function and show how this can be used to find, or approximate, solutions to well-known hard problems in graph theory.
This paper includes the r-package savi, which implements simulated annealing. Specifically, we implement it for three example vertex partitioning problems: vertex covering, identifying k-partite graphs, and the Erdős–Faber–Lovász Conjecture. The paper also shows which scoring functions to use for these examples and provides proofs that the scoring functions assign their lowest value to the optimal score.
|Commitee:||Johnson, Brody, Chambers, Erin Wolf|
|School:||Saint Louis University|
|School Location:||United States -- Missouri|
|Source:||MAI 81/7(E), Masters Abstracts International|
|Keywords:||Optimization, Simulated annealing, Vertex partitioning|
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