A genetic algorithm with a self-reproduction operator to solve systems of nonlinear equations

William La Cruz ()
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William La Cruz: Universidad Central de Venezuela

Journal of Global Optimization, 2022, vol. 84, issue 4, No 8, 1005-1032

Abstract: Abstract A genetic algorithm for solving systems of nonlinear equations that uses a self-reproduction operator bases on residual approaches is presented and analyzed. To ensure convergence the elitist model is used. A convergence analysis is given. With the aim of showing the advantages of the proposed genetic algorithm an extensive set of numerical experiments with standard test problems and some specific applications are reported.

Keywords: Genetic algorithm; Systems of nonlinear equations; Fitness Function; Residual approach; 65K05; 68T20 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10898-022-01189-1

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