Hemos publicado recientemente un nuevo artículo, en el que describimos una herramienta para el manejo de preferencias en optimización evolutiva multiobjetivo:
G. Reynoso-Meza, J. Sanchis, X. Blasco, S. García-Nieto. Physical programming for preference driven evolutionary multi-objective optimization. Applied Soft Computing. Volume 24, November 2014, Pages 341–362
Por tiempo limitado, el artículo se encuentra libre de descarga.
Preference articulation in multi-objective optimization could be used to improve the pertinency of solutions in an approximated Pareto front. That is, computing the most interesting solutions from the designer's point of view in order to facilitate the Pareto front analysis and the selection of a design alternative. This articulation can be achieved in an a priori, progressive, or a posteriori manner. If it is used within an a priori frame, it could focus the optimization process toward the most promising areas of the Pareto front, saving computational resources and assuring a useful Pareto front approximation for the designer. In this work, a physical programming approach embedded in an evolutionary multi-objective optimization is presented as a tool for preference inclusion. The results presented and the algorithm developed validate the proposal as a potential tool for engineering design by means of evolutionary multi-objective optimization.