%0 Journal Article
	%A Konstantinos Metaxiotis and  Konstantinos Liagkouras
	%D 2017
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 126, 2017
	%T Examining the Performance of Three Multiobjective Evolutionary Algorithms Based on Benchmarking Problems
	%U https://publications.waset.org/pdf/10007189
	%V 126
	%X The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

	%P 660 - 665