Implementing Dejong Function by Random Initialization |
Author(s): |
| Noopur Tyagi , Modern Institute of Engeeniring and technology; Rakesh Kumar, 2Modern Institute of Engineering and Technology, Mohri, Haryana, India |
Keywords: |
| Dejong Function, Initialization, Genetic algorithm (GA) |
Abstract |
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Genetic Algorithm (GAs) are search procedures based on principles derived from the dynamics of natural population genetics. Performance of genetic algorithms mainly depends on type of genetic operators – Initialisation, Selection, Crossover, Mutation and Replacement used in it. Success of Genetic Algorithm mainly depends upon the individuals selected in the initial population and the size of population. If the individuals chosen in the initial population are poor, it will result in weaker solutions and premature convergence towards optima. There are different methods to initialize Genetic algorithms but most of the time random initialization is used. In this paper minimum value of dejong’s function is observed at different generations. |
Other Details |
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Paper ID: IJSRDV3I40295 Published in: Volume : 3, Issue : 4 Publication Date: 01/07/2015 Page(s): 588-590 |
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