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A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization.

, , , , and . GECCO, page 656-663. ACM, (2019)

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A parallel technique for multi-objective Bayesian global optimization: Using a batch selection of probability of improvement., , and . Swarm Evol. Comput., (2022)Faster Exact Algorithms for Computing Expected Hypervolume Improvement., , , and . EMO (2), volume 9019 of Lecture Notes in Computer Science, page 65-79. Springer, (2015)Expected hypervolume improvement algorithm for PID controller tuning and the multiobjective dynamical control of a biogas plant., , , and . CEC, page 1934-1942. IEEE, (2015)Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement., , , , and . GECCO, page 1333-1340. ACM, (2018)Challenges of ELA-Guided Function Evolution Using Genetic Programming., , , , , , and . IJCCI, page 119-130. SCITEPRESS, (2023)Efficient Computation of Expected Hypervolume Improvement Using Box Decomposition Algorithms., , , and . CoRR, (2019)Surrogate-assisted Multi-objective Optimization via Genetic Programming Based Symbolic Regression., and . EMO, volume 13970 of Lecture Notes in Computer Science, page 176-190. Springer, (2023)Preference-based multiobjective optimization using truncated expected hypervolume improvement., , , , and . ICNC-FSKD, page 276-281. IEEE, (2016)SMS-EMOA with multiple dynamic reference points., , , , and . ICNC-FSKD, page 282-288. IEEE, (2016)Population diversity and inheritance in genetic programming for symbolic regression., , and . Nat. Comput., 23 (3): 531-566 (September 2024)