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>\r\n","references":"[1]\tK. Metaxiotis & K. Liagkouras (2012) Multiobjective Evolutionary Algorithms for Portfolio Management: A comprehensive literature review. Expert Systems with Applications, Elsevier, 39 (14): 11685-1169.\r\n[2]\tK. Liagkouras & K. 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Evolutionary Computation 8(2): 173\u2013195.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 126, 2017"}