swMATH ID: 19036
Software Authors: León, C., Miranda, G., Segura, C.
Description: 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.
Homepage: http://www.worldscientific.com/doi/abs/10.1142/S0218213009000275
Related Software: Hyperheuristics; JADE; TOMS659; MersenneTwister; SPEA2; MPI; CALMA
Referenced in: 4 Publications

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1 Publication describing the Software Year
Metco: a parallel plugin-based framework for multi-objective optimization
León, Coromoto; Miranda, Gara; Segura, Carlos

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