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PLoS One. 2013;8(1):e53437. doi: 10.1371/journal.pone.0053437. Epub 2013 Jan 14.

Solving hard computational problems efficiently: asymptotic parametric complexity 3-coloring algorithm.

Author information

  • 1Computer Architecture and Automation, Complutense University of Madrid, Madrid, Spain. jamartinh@fdi.ucm.es

Abstract

Many practical problems in almost all scientific and technological disciplines have been classified as computationally hard (NP-hard or even NP-complete). In life sciences, combinatorial optimization problems frequently arise in molecular biology, e.g., genome sequencing; global alignment of multiple genomes; identifying siblings or discovery of dysregulated pathways. In almost all of these problems, there is the need for proving a hypothesis about certain property of an object that can be present if and only if it adopts some particular admissible structure (an NP-certificate) or be absent (no admissible structure), however, none of the standard approaches can discard the hypothesis when no solution can be found, since none can provide a proof that there is no admissible structure. This article presents an algorithm that introduces a novel type of solution method to "efficiently" solve the graph 3-coloring problem; an NP-complete problem. The proposed method provides certificates (proofs) in both cases: present or absent, so it is possible to accept or reject the hypothesis on the basis of a rigorous proof. It provides exact solutions and is polynomial-time (i.e., efficient) however parametric. The only requirement is sufficient computational power, which is controlled by the parameter α∈N. Nevertheless, here it is proved that the probability of requiring a value of α>k to obtain a solution for a random graph decreases exponentially: P(α>k)≤2(-(k+1)), making tractable almost all problem instances. Thorough experimental analyses were performed. The algorithm was tested on random graphs, planar graphs and 4-regular planar graphs. The obtained experimental results are in accordance with the theoretical expected results.

PMID:
23349711
PMCID:
PMC3544923
DOI:
10.1371/journal.pone.0053437
[PubMed - indexed for MEDLINE]
Free PMC Article
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