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Offline parameter tuning (OPT) of multi-objective evolutionary algorithms (MOEAs) has the goal of finding an appropriate set of parameters for solving a large number of problems. According to the no free lunch theorem (NFL), no algorithm can have the best performance in all classes of optimization problems. However, it is possible to find an appropriate set of parameters of an algorithm for solving a particular class of problems. For that sake, we need to study how to estimate the aggregationdoi:10.1109/ssci.2018.8628704 dblp:conf/ssci/Pescador-RojasP18 fatcat:egrv3gus35dkjc2jyvyt3kudru