Computationally Expensive Optimization

I gave a presentation at Symposium on Fuzzy, Artificial Intelligence, Neural Networks and Computational Intelligence (FAN2021, 21-23, Sep.), and we won the Excellent Paper Award. Thank you to all those who helped make this event possible.

2021 Symposium on Fuzzy, Artificial Intelligence, Neural Networks and Computational Intelligence

This paper proposes a new ensemble adaptive DE with a prior validation that estimates a suitable adaptive DE every generation without additional FEs before solution generation. Experimental results show that our proposal outperforms existing methods and has a better convergence speed.

This paper presents a generalized prior-validation framework for algorithmic configurations, which can be applicable to major variants of self-adaptive DEs that adapt the scaling factor, the crossover rate, and/or the mutation/crossover strategies for each individual.

自己適応型差分進化法は，アルゴリズム構成を試行錯誤的に調整するため，少ない解評価回数では性能が十分に改善しない．本論文は，調整されたアルゴリズム構成の事前検証によって，試行錯誤的な調整を削減し，少ない解評価回数で高い性能を実現することを目的とする．また，提案する事前検証 …