OPTIMIZATION OF NON-LINEAR FUNCTIONS USING EVOLUTIONARY COMPUTATION

Global optimization is important if the function has a number of optima of which some are local and some global. Since many real world problems contain multiple optima, traditional methods may not be adequate to solve such problems due to the possibility of getting trapped at local optimum. Hence they do not ensure global optima. Differential Evolution (DE) is an evolutionary optimization technique which is exceptionally simple, significantly faster & robust at numerical optimization and is more likely to find a function’s true global optimum. In this paper, a non-linear function with three local optima and one global optima has been solved by using DE. The results obtained from DE are compared with that of Genetic Algorithms (GA). The results indicate that performance of DE is better than GA.

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