Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations

This paper introduce a new variant of the Genetic Algorithm whichis developed to handle multivariable, multi-objective and very high search space optimization problems like the solving system of non-linear equations. It is an integer coded Genetic Algorithm with conventional cross over and mutation...

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Main Authors: SS Venkatesh, Mishra Deepak
Format: Article
Language:English
Published: De Gruyter 2020-07-01
Series:Journal of Intelligent Systems
Subjects:
Online Access:https://doi.org/10.1515/jisys-2019-0233
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author SS Venkatesh
Mishra Deepak
author_facet SS Venkatesh
Mishra Deepak
author_sort SS Venkatesh
collection DOAJ
description This paper introduce a new variant of the Genetic Algorithm whichis developed to handle multivariable, multi-objective and very high search space optimization problems like the solving system of non-linear equations. It is an integer coded Genetic Algorithm with conventional cross over and mutation but with Inverse algorithm is varying its search space by varying its digit length on every cycle and it does a fine search followed by a coarse search. And its solution to the optimization problem will converge to precise value over the cycles. Every equation of the system is considered as a single minimization objective function. Multiple objectives are converted to a single fitness function by summing their absolute values. Some difficult test functions for optimization and applications are used to evaluate this algorithm. The results prove that this algorithm is capable to produce promising and precise results.
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spelling doaj.art-cf041b07e80f4acfac6b117f493b7a9f2022-12-21T18:11:44ZengDe GruyterJournal of Intelligent Systems2191-026X2020-07-0130114216410.1515/jisys-2019-0233jisys-2019-0233Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear EquationsSS Venkatesh0Mishra Deepak1Dept. of Avionics, IIST Trivandrum, Kerala, IndiaDept. of Avionics, IIST Trivandrum, Kerala, IndiaThis paper introduce a new variant of the Genetic Algorithm whichis developed to handle multivariable, multi-objective and very high search space optimization problems like the solving system of non-linear equations. It is an integer coded Genetic Algorithm with conventional cross over and mutation but with Inverse algorithm is varying its search space by varying its digit length on every cycle and it does a fine search followed by a coarse search. And its solution to the optimization problem will converge to precise value over the cycles. Every equation of the system is considered as a single minimization objective function. Multiple objectives are converted to a single fitness function by summing their absolute values. Some difficult test functions for optimization and applications are used to evaluate this algorithm. The results prove that this algorithm is capable to produce promising and precise results.https://doi.org/10.1515/jisys-2019-0233genetic algorithmroulette wheel selectioncross overmutationmulti objective optimizationmulti variable optimizationgenetic algorithmmulti objective optimizationmulti variable optimizationcomputer scienceartificial intelligence
spellingShingle SS Venkatesh
Mishra Deepak
Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations
Journal of Intelligent Systems
genetic algorithm
roulette wheel selection
cross over
mutation
multi objective optimization
multi variable optimization
genetic algorithm
multi objective optimization
multi variable optimization
computer science
artificial intelligence
title Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations
title_full Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations
title_fullStr Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations
title_full_unstemmed Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations
title_short Variable Search Space Converging Genetic Algorithm for Solving System of Non-linear Equations
title_sort variable search space converging genetic algorithm for solving system of non linear equations
topic genetic algorithm
roulette wheel selection
cross over
mutation
multi objective optimization
multi variable optimization
genetic algorithm
multi objective optimization
multi variable optimization
computer science
artificial intelligence
url https://doi.org/10.1515/jisys-2019-0233
work_keys_str_mv AT ssvenkatesh variablesearchspaceconverginggeneticalgorithmforsolvingsystemofnonlinearequations
AT mishradeepak variablesearchspaceconverginggeneticalgorithmforsolvingsystemofnonlinearequations