LGO

The program system LGO serves to solve global optimization problems under very mild -- continuity or Lipschitz-continuity -- structural assumptions. LGO is embedded into a menu-driven user interface which effectively assists the application development process. Implementation details, and several application areas are also highlighted.


References in zbMATH (referenced in 63 articles , 1 standard article )

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  1. Kampas, Frank J.; Pintér, János D.; Castillo, Ignacio: Optimal packing of general ellipses in a circle (2017)
  2. Scitovski, Rudolf: A new global optimization method for a symmetric Lipschitz continuous function and the application to searching for a globally optimal partition of a one-dimensional set (2017)
  3. Al-Dujaili, Abdullah; Suresh, S.; Sundararajan, N.: MSO: a framework for bound-constrained black-box global optimization algorithms (2016)
  4. Balsa-Canto, Eva; Alonso, Antonio A.; Arias-Méndez, Ana; García, Miriam R.; López-Núñez, A.; Mosquera-Fernández, Maruxa; Vázquez, C.; Vilas, Carlos: Modeling and optimization techniques with applications in food processes, bio-processes and bio-systems (2016)
  5. Evtushenko, Yu.G.; Lurie, S.A.; Posypkin, M.A.; Solyaev, Yu.O.: Application of optimization methods for finding equilibrium states of two-dimensional crystals (2016)
  6. Gergel, Victor; Grishagin, Vladimir; Gergel, Alexander: Adaptive nested optimization scheme for multidimensional global search (2016)
  7. Grimstad, Bjarne; Sandnes, Anders: Global optimization with spline constraints: a new branch-and-bound method based on B-splines (2016)
  8. Khong, Sei Zhen; Nešić, Dragan; Krstić, Miroslav: Iterative learning control based on extremum seeking (2016)
  9. Paulavičius, Remigijus; Žilinskas, Julius: Advantages of simplicial partitioning for Lipschitz optimization problems with linear constraints (2016)
  10. Pintér, János D.; Castellazzo, Alessandro; Vola, Mariachiara; Fasano, Giorgio: Nonlinear regression analysis by global optimization: a case study in space engineering (2016)
  11. Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.: On the least-squares fitting of data by sinusoids (2016)
  12. Sergeyev, Yaroslav D.; Mukhametzhanov, Marat S.; Kvasov, Dmitri E.; Lera, Daniela: Derivative-free local tuning and local improvement techniques embedded in the univariate global optimization (2016)
  13. Censor, Yair; Reem, Daniel: Zero-convex functions, perturbation resilience, and subgradient projections for feasibility-seeking methods (2015)
  14. Lampariello, F.; Liuzzi, G.: A filling function method for unconstrained global optimization (2015)
  15. Lampariello, Francesco; Liuzzi, Giampaolo: Global optimization of protein-peptide docking by a filling function method (2015)
  16. Liu, Haitao; Xu, Shengli; Ma, Ying; Wang, Xiaofang: Global optimization of expensive black box functions using potential Lipschitz constants and response surfaces (2015)
  17. Sergeyev, Yaroslav D.; Kvasov, Dmitri E.: A deterministic global optimization using smooth diagonal auxiliary functions (2015)
  18. Chu, Moody T.; Lin, Matthew M.; Wang, Liqi: A study of singular spectrum analysis with global optimization techniques (2014)
  19. Paulavičius, Remigijus; Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Žilinskas, Julius: Globally-biased disimpl algorithm for expensive global optimization (2014)
  20. Paulavičius, Remigijus; Žilinskas, Julius: Simplicial Lipschitz optimization without the Lipschitz constant (2014)

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