Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization

Faculty	Computer Science	Year:	2015
Type of Publication:	ZU Hosted	Pages:
Authors:	Saber Mohamed Staff Zu Site Abstract In Staff Site
Journal:	Applied Soft Computing ELSEVEIR	Volume:

Keywords :	Training , Testing , Self-Adaptive Multi-Operator Evolutionary Algorithm
Abstract:	Over the last two decades, many different evolutionary algorithms (EAs) have been introduced for solving constrained optimization problems (COPs). Due to the variability of the characteristics in different COPs, no single algorithm performs

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