METCO: A parallel plugin-based framework for multi-objective optimization. This paper presents a parallel framework for the solution of multi-objective optimization problems. The framework implements some of the best known multi-objective evolutionary algorithms. The plugin-based architecture of the framework minimizes the end user effort required to incorporate their own problems and evolutionary algorithms, and facilitates tool maintenance. A wide variety of configuration options can be specified to adapt the software behavior to many different parallel models. An innovation of the framework is that it provides a self-adaptive parallel model that is based on the cooperation of a set of evolutionary algorithms. The aim of the new model is to raise the level of generality at which most current evolutionary algorithms operate. This way, a wider range of problems can be tackled since the strengths of one algorithm can compensate for the weaknesses of another. The model proposed is a hybrid algorithm that combines a parallel island-based scheme with a hyperheuristic approach. The model grants more computational resources to those algorithms that show a more promising behavior. The flexibility and efficiency of the framework were tested and demonstrated by configuring standard and self-adaptive models for test problems and real-world applications.
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References in zbMATH (referenced in 6 articles , 1 standard article )
Showing results 1 to 6 of 6.
- Segredo, Eduardo; Lalla-Ruiz, Eduardo; Hart, Emma; Voß, Stefan: A similarity-based neighbourhood search for enhancing the balance exploration-exploitation of differential evolution (2020)
- Segredo, Eduardo; Paechter, Ben; Segura, Carlos; González-Vila, Carlos I.: On the comparison of initialisation strategies in differential evolution for large scale optimisation (2018)
- Segura, Carlos; Aguirre, Arturo Hernández; Valdez Peña, Sergio Ivvan; Botello Rionda, Salvador: The importance of proper diversity management in evolutionary algorithms for combinatorial optimization (2017)
- Segredo, Eduardo; Segura, Carlos; León, Coromoto: Memetic algorithms and hyperheuristics applied to a multiobjectivised two-dimensional packing problem (2014)
- Segura, Carlos; Segredo, Eduardo; León, Coromoto: Scalability and robustness of parallel hyperheuristics applied to a multiobjectivised frequency assignment problem (2013) ioport
- León, Coromoto; Miranda, Gara; Segura, Carlos: Metco: a parallel plugin-based framework for multi-objective optimization (2009) ioport