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This paper discusses the use of several heuristic techniques for problems of cobinatorial optimization. We especially consider the advantages and disadvantages of naturally inspired generic techniques like Simulated Anealing, Evolution Strategies, or Genetic Algorithms. This reflection gives a quite intuitive motivation for hybrid approaches that aim to combine advantageous aspects of certain strategies. Among those we formulate some new hybrid multidisciplinary ideas that are mainly based upon Genetic Algorithms and Evolution Strategies. These algorithms aim to improve the global solution quality by retarding the effects of unwanted premature convergence. The experimental part of the paper gives a brief overview of archieved results.