ARGONAUT: algorithms for global optimization of constrained grey-box computational problems. The algorithmic framework ARGONAUT is presented for the global optimization of general constrained grey-box problems. ARGONAUT incorporates variable selection, bounds tightening and constrained sampling techniques, in order to develop accurate surrogate representations of unknown equations, which are globally optimized. ARGONAUT is tested on a large set of test problems for constrained global optimization with a large number of input variables and constraints. The performance of the presented framework is compared to that of existing techniques for constrained derivative-free optimization.
Keywords for this software
References in zbMATH (referenced in 9 articles , 1 standard article )
Showing results 1 to 9 of 9.
- Zhai, Jianyuan; Boukouvala, Fani: Data-driven spatial branch-and-bound algorithms for box-constrained simulation-based optimization (2022)
- Eason, John P.; Biegler, Lorenz T.: Model reduction in chemical process optimization (2021)
- Pappas, Iosif; Diangelakis, Nikolaos A.; Pistikopoulos, Efstratios N.: The exact solution of multiparametric quadratically constrained quadratic programming problems (2021)
- Schweidtmann, Artur M.; Bongartz, Dominik; Grothe, Daniel; Kerkenhoff, Tim; Lin, Xiaopeng; Najman, Jaromił; Mitsos, Alexander: Deterministic global optimization with Gaussian processes embedded (2021)
- Audet, Charles; Côté, Pascal; Poissant, Catherine; Tribes, Christophe: Monotonic grey box direct search optimization (2020)
- Bajaj, Ishan; Hasan, M. M. Faruque: Global dynamic optimization using edge-concave underestimator (2020)
- Kim, Sun Hye; Boukouvala, Fani: Machine learning-based surrogate modeling for data-driven optimization: a comparison of subset selection for regression techniques (2020)
- Kieslich, Chris A.; Boukouvala, Fani; Floudas, Christodoulos A.: Optimization of black-box problems using Smolyak grids and polynomial approximations (2018)
- Boukouvala, Fani; Floudas, Christodoulos A.: ARGONAUT: algorithms for global optimization of constrained grey-box computational problems (2017)