The jMetal framework for multi-objective optimization: Design and architecture

By Juan José Durillo, Antonio J. Nebro, Enrique Alba. IEEE Congress on Evolutionary Computation, 2010

295 citations recorded by the source corpus.

jMetal is a Java-based framework for multi-objective optimization using metaheuristics. It is a flexible, extensible, and easy-to-use software package that has been used in a wide range of applications. In this paper, we describe the design issues underlying jMetal, focusing mainly on its internal architecture, with the aim of offering a comprehensive view of its main features to interested researchers. Among the covered topics, we detail the basic components facilitating the implementation of multi-objective metaheuristics (solution representations, operators, problems, density estimators, archives), the included quality indicators to assess the performance of the algorithms, and jMetal's support to carry out full experimental studies.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/98095e808e8ab7c5edc942bc60ef9f315ec012b3

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Citations in the corpus

jMetal: A Java framework for multi-objective optimization (2011, background): “A more detailed description of the jMetal architecture can be found in [45] and in the jMetal user manual [46].”
A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems (2016, methodology): “These software packages are briefly introduced in Table V, including BENSOLVE [233], the distributed evolutionary algorithms in Python (DEAP) [234], Decisionarium [235], D-Sight [236], the graphical user interface designed for multi-objective optimization (GUIMOO) [237], the intelligent decision sup”
Distributed evolutionary algorithms and their models: A survey of the state-of-the-art (2015, methodology): “To make further improvement, parallel nd distributed versions of MOEA/D are developed in [92,36,32,33].”