GenMin: An enhanced genetic algorithm for global optimization

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@Article{Tsoulos2008843,
  author =       "Ioannis G. Tsoulos and I. E. Lagaris",
  title =        "{GenMin:} An enhanced genetic algorithm for global
                 optimization",
  journal =      "Computer Physics Communications",
  volume =       "178",
  number =       "11",
  pages =        "843--851",
  year =         "2008",
  ISSN =         "0010-4655",
  DOI =          "doi:10.1016/j.cpc.2008.01.040",
  URL =          "http://www.sciencedirect.com/science/article/B6TJ5-4RR8YW1-2/2/9b76a8b289abccf9ec864e11a54573a7",
  keywords =     "genetic algorithms, genetic programming, Grammatical
                 evolution, Global optimization, Stochastic methods,
                 Stopping rule",
  abstract =     "A new method that employs grammatical evolution and a
                 stopping rule for finding the global minimum of a
                 continuous multidimensional, multimodal function is
                 considered. The genetic algorithm used is a hybrid
                 genetic algorithm in conjunction with a local search
                 procedure. We list results from numerical experiments
                 with a series of test functions and we compare with
                 other established global optimization methods. The
                 accompanying software accepts objective functions coded
                 either in Fortran 77 or in C++.

                 Program summary

                 Program title: GenMin

                 Catalogue identifier: AEAR_v1_0

                 Program summary
                 URL:http://cpc.cs.qub.ac.uk/summaries/AEAR_v1_0.html

                 Program obtainable from: CPC Program Library, Queen's
                 University, Belfast, N. Ireland

                 Licensing provisions: Standard CPC licence,
                 http://cpc.cs.qub.ac.uk/licence/licence.html

                 No. of lines in distributed program, including test
                 data, etc.: 35[thin space]810

                 No. of bytes in distributed program, including test
                 data, etc.: 436[thin space]613

                 Distribution format: tar.gz

                 Programming language: GNU-C++, GNU-C, GNU Fortran
                 77

                 Computer: The tool is designed to be portable in all
                 systems running the GNU C++ compiler

                 Operating system: The tool is designed to be portable
                 in all systems running the GNU C++ compiler

                 RAM: 200 KB

                 Word size: 32 bits

                 Classification: 4.9

                 Nature of problem: A multitude of problems in science
                 and engineering are often reduced to minimizing a
                 function of many variables. There are instances that a
                 local optimum does not correspond to the desired
                 physical solution and hence the search for a better
                 solution is required. Local optimization techniques are
                 frequently trapped in local minima. Global optimization
                 is hence the appropriate tool. For example, solving a
                 nonlinear system of equations via optimization,
                 employing a least squares type of objective, one may
                 encounter many local minima that do not correspond to
                 solutions (i.e. they are far from zero).

                 Solution method: Grammatical evolution and a stopping
                 rule.

                 Running time: Depending on the objective function. The
                 test example given takes only a few seconds to run.",
}

Genetic Programming entries for Ioannis G Tsoulos Ioannis G Tsoulos

Citations