PERFORMANCE ANALYSIS OF GENETIC OPERATORS ON TEST FUNCTIONS OF SINGLE OBJECTIVE OPTIMIZATION PROBLEMS

Authors

  • Deepika Pathak Dr. Sharad Gangele Author

Keywords:

Multi Clustered, Genetic Algorithm

Abstract

Multi Clustered Parallel Genetic Algorithm is a type of multi population based genetic algorithm which gives equal importance to low fit individuals. It has been applied to 0/1 knapsack problem and found to perform well compared to the Standard Genetic Algorithm. This paper investigates the working rule of multi grouped parallel hereditary calculation for the standard test capacities for the single target enhancement issues and contrasted and the standard hereditary calculation. The execution is contrasted and the standard hereditary calculation, the standard test elements of single target streamlining issues are utilized and the outcome demonstrates that proposed technique performs better with meeting speed

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Published

2017-06-11

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Section

Articles

How to Cite

PERFORMANCE ANALYSIS OF GENETIC OPERATORS ON TEST FUNCTIONS OF SINGLE OBJECTIVE OPTIMIZATION PROBLEMS. (2017). Global Journal of Advanced Engineering Technologies and Sciences, 4(6), 27-33. https://gjaets.com/index.php/gjaets/article/view/156

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