… various multi-objective evolutionary algorithms have been widely applied in the field of
search-based software … Such discovery is our objective, and it may lead the community to better …

… use of multi-objective evolutionary computation approaches … also a performance evaluation
of a set of six multi-objective … the literature that involve the discovery of an architecture [27, 28]…

… the space of features using a multi-objective evolutionary algorithm that contains a set of
generalization operators in addition to conventional evolutionary operators. Both variables and …

… process, not only the model performance, but also the above factors should be taken into
account. Usually, when there are conflicts among several objectives, it is impossible for a …

… is a function of the performance of its corresponding architecture. … genetic algorithm is used
to drive the optimization parameters of multiple lower-level multi-objective genetic algorithms. …

… To test the effectiveness of the LSM-PSO, it is applied over five software projects and … -scale
may-objective evolutionary algorithm (LMEA). To make the NSGA-III algorithms suitable for …

… Performance metrics are used to compare several evolutionary algorithms. Results indicate
… Hence, this paper analyzes several evolutionary multi-objective algorithms (EMOAs). Some …

… solving multi-objective problems, the development and the application of Evolutionary Algorithm
… that are applied to solve MOPs are called multiobjective Evolutionary Algorithm (MOEA). …

… An MOP comprises multiple objective functions to be minimized … These algorithms discover
hidden patterns or data … efforts in improving the performance of three evolutionary modules (ie…

… effectiveness in solving multi-objective optimization problems [16]. MOEAs mainly include
multi-objective genetic algorithms (… as the result of the service discovery strategy in Section III. …