DNA base-code generation for reliable computing by using standard multi-objective evolutionary algorithms

  • Authors:

  • Jose M. M. Chaves-González;Miguel A. A. Vega-Rodríguez

  • Affiliations:

  • University of Extremadura, Cáceres, Spain;University of Extremadura, Cáceres, Spain

  • Venue:
  • Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
  • Year:
  • 2013

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Abstract

Artificially generated DNA strands have to meet several complex bio-chemical constraints when they are used to solve any computational problem. In this context, DNA sequences have to satisfy several design criteria to prevent DNA strands from producing undesirable reactions which usually lead to incorrect computations. This study is focused on six different design criteria that ensure the reliability and efficiency of the operations performed with the generated DNA sequences. We have formulated DNA base-code generation as a multiobjective optimization problem in which there is not only a unique optimal solution, but a Pareto set of high-quality solutions. Reliable DNA sequences have been generated by using two well-known multiobjective approaches: the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Strength Pareto Evolutionary Algorithm 2 (SPEA 2). We have performed experiments with three different-sized realistic datasets. Results show that the multiobjective algorithms developed are very appropriate for our problem, especially NSGA-II, which provides more reliable DNA sequences than other relevant approaches previously published in the literature.