Solving Constraint Satisfaction Problems with DNA Computing
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DNA8 Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing
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ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
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A goal of research on DNA computing is to solve problems that are beyond the capabilities of the fastest silicon-based supercomputers. Adleman and Lipton present exhaustive search algorithms for 3Sat and 3-Coloring, which can only be run on small instances and hence are not practical. In this paper, we show how improved algorithms can be developed for the 3-Coloring and Independent Set problems. Our algorithms use only the DNA operations proposed by Adleman and Lipton, but combine them in more powerful ways, and use polynomial preprocessing on a standard computer to tailor them to the specific instance to be solved. The main contribution of this paper is a more general model of DNA algorithms than that proposed by Lipton. We show that DNA computation for NP-complete problems can do more than just exhaustive search. Further research in this direction will help determine whether or not DNA computing is viable for NP-hard problems. A second contribution is the first analysis of errors that arise in generating the solution space for DNA computation.