Classification of applied methods of combinatorial optimization

  • Authors:

  • I. V. Sergienko;L. F. Hulianytskyi;S. I. Sirenko

  • Affiliations:

  • V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine;V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine

  • Venue:
  • Cybernetics and Systems Analysis
  • Year:
  • 2009

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Abstract

The paper reviews most popular approaches to the development of applied methods of combinatorial optimization. A number of characteristics and criteria are proposed that underlie the classification of approximate algorithms. The classification continues the previous investigations in combinatorial optimization and allows determining key components of computational schemes used in constructing efficient hybrid metaheuristics.