A surrogate-assisted a priori multiobjective evolutionary algorithm for constrained multiobjective optimization problems
Aghaei pour, P., Hakanen, J., & Miettinen, K. (2024). A surrogate-assisted a priori multiobjective evolutionary algorithm for constrained multiobjective optimization problems. Journal of Global Optimization, Early online. https://doi.org/10.1007/s10898-024-01387-z
Julkaistu sarjassa
Journal of Global OptimizationPäivämäärä
2024Tekijänoikeudet
© The Author(s) 2024
We consider multiobjective optimization problems with at least one computationally expensive constraint function and propose a novel surrogate-assisted evolutionary algorithm that can incorporate preference information given a priori. We employ Kriging models to approximate expensive objective and constraint functions, enabling us to introduce a new selection strategy that emphasizes the generation of feasible solutions throughout the optimization process. In our innovative model management, we perform expensive function evaluations to identify feasible solutions that best reflect the decision maker’s preferences provided before the process. To assess the performance of our proposed algorithm, we utilize two distinct parameterless performance indicators and compare them against existing algorithms from the literature using various real-world engineering and benchmark problems. Furthermore, we assemble new algorithms to analyze the effects of the selection strategy and the model management on the performance of the proposed algorithm. The results show that in most cases, our algorithm has a better performance than the assembled algorithms, especially when there is a restricted budget for expensive function evaluations.
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SpringerISSN Hae Julkaisufoorumista
0925-5001Asiasanat
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https://converis.jyu.fi/converis/portal/detail/Publication/216026073
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This research was partly supported by the Academy of Finland (grant no 311877) and is related to the thematic research area DEMO (Decision Analytics utilizing Causal Models and Multiobjective Optimization, jyu.fi/demo) of the University of Jyväskylä. KAEA-C will be implemented in the open-source software DESDEO (https://desdeo.it.jyu.fi/) funded by the Academy of Finland. Open Access funding provided by University of Jyväskylä (JYU). ...Lisenssi
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