Evolutionary Optimization of Expensive Multiobjective Problems With Co-Sub-Pareto Front Gaussian Process Surrogates
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2018.2811761
Abstract: This paper proposes a Gaussian process (GP) based co-sub-Pareto front surrogate augmentation strategy for evolutionary optimization of computationally expensive multiobjective problems. In the proposed algorithm, a multiobjective problem is decomposed into a number of subproblems,… read more here.
Keywords: pareto; expensive multiobjective; evolutionary optimization; sub pareto ... See more keywords
Multilayer Perceptron Grouping and Sparse Gaussian Process-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Multiobjective Optimization.
Sign Up to like & getrecommendations! Published in 2025 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2025.3634364
Abstract: Gaussian processes (GPs) have attracted considerable attention in assisting evolutionary algorithms (EAs) to solve computationally expensive optimization problems (EOPs) because they can directly provide information about the uncertainty of their predictions. However, the computational complexity… read more here.
Keywords: assisted evolutionary; evolutionary algorithm; expensive multiobjective; optimization ... See more keywords