Affiliation:
1. Ulm University
2. University of Bergen
3. University of Warsaw
4. Charles University
5. Chennai Mathematical Institute
6. UMI ReLaX
Abstract
When modeling an application of practical relevance as an instance of a combinatorial problem X, we are often interested not merely in finding one optimal solution for that instance, but in finding a sufficiently diverse collection of good solutions. In this work we initiate a systematic study of diversity from the point of view of fixed-parameter tractability theory. We consider an intuitive notion of diversity of a collection of solutions which suits a large variety of combinatorial problems of practical interest. Our main contribution is an algorithmic framework which --automatically-- converts a tree-decomposition-based dynamic programming algorithm for a given combinatorial problem X into a dynamic programming algorithm for the diverse version of X. Surprisingly, our algorithm has a polynomial dependence on the diversity parameter.
Publisher
International Joint Conferences on Artificial Intelligence Organization
Cited by
5 articles.
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