Evolving Fixed-parameter Tractable Algorithms
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2008-06-30
Language
en
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Abstract
One effective means of computing NP-hard problems is provided by fixed-parameter tractable (fpt-) algorithms.
An fpt-algorithm is an algorithm whose running time is polynomial in the input size and superpolynomial
only as a function of an input parameter. Provided that the parameter is small enough, an
fpt-algorithm runs fast even for large inputs. In this paper, we report on an investigation of the evolvability
of fpt-algorithms via Genetic Programming (GP). The problem used in this investigation is the NP-hard
2D-Euclidean Traveling Salesman Problem (TSP), which is known to be fpt if the number of points not on
the convex hull is taken as the parameter. The algorithm evolved in our GP study turns out to have clear
characteristics of an fpt-algorithm. The results suggest GP can be utilized for generating fpt-algorithms
for NP-hard problems in general, as well as for discovering input parameters that could be used to develop
fpt-algorithms.
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Faculteit der Sociale Wetenschappen