Parallel Characteristical Algorithms for Solving Problems of Global Optimization. - Vladimir A. Grishagin; Yaroslav D. Sergeyev; Roman G. Strongin (J. Glob. Optim., 1997)

Firms' R&D decisions under incomplete information. - Vladimir A. Grishagin; Yaroslav D. Sergeyev; D. B. Silipo (Eur. J. Oper. Res., 2001)

Local Tuning in Nested Scheme of Global Optimization. - Victor Gergel; Vladimir A. Grishagin; Ruslan Israfilov (ICCS, 2015)

Adaptive nested optimization scheme for multidimensional global search. - Victor Gergel; Vladimir A. Grishagin; Alexander Gergel (J. Glob. Optim., 2016)

Adaptive Dimensionality Reduction in Multiobjective Optimization with Multiextremal Criteria. - Victor Gergel; Vladimir A. Grishagin; Ruslan Israfilov (LOD, 2018)

Convergence conditions and numerical comparison of global optimization methods based on dimensionality reduction schemes. - Vladimir A. Grishagin; Ruslan Israfilov; Yaroslav D. Sergeyev (Appl. Math. Comput., 2018)

Multiextremal Optimization in Feasible Regions with Computable Boundaries on the Base of the Adaptive Nested Scheme. - Victor Gergel; Vladimir A. Grishagin; Ruslan Israfilov (NUMTA (2), 2019)

Parallel Dimensionality Reduction for Multiextremal Optimization Problems. - Victor Gergel; Vladimir A. Grishagin; Ruslan Israfilov (PaCT, 2019)

An Approach for Simultaneous Finding of Multiple Efficient Decisions in Multi-objective Optimization Problems. - Konstantin Barkalov; Victor Gergel; Vladimir A. Grishagin; Evgeniy Kozinov (MOTOR, 2021)

Parallel Computations in Integrated Environment of Engineering Modeling and Global Optimization. - Victor Gergel; Vladimir A. Grishagin; Alexei Liniov; Sergey Shumikhin (PaCT, 2021)

ML-Based Approach for Accelerating Global Search Algorithm for Solving Multicriteria Problems. - Konstantin Barkalov; Vladimir A. Grishagin; Evgeny Kozinov (LION, 2022)

An Accelerated Algorithm for Finding Efficient Solutions in Multiobjective Problems with Black-Box Multiextremal Criteria. - Konstantin Barkalov; Vladimir A. Grishagin; Evgeny Kozinov (OPTIMA, 2022)

Application of Machine Learning to Increase the Efficiency of the Global Search Algorithm for Solving Multicriterial Problems. - Konstantin Barkalov; Vladimir A. Grishagin; Evgeny Kozinov (NUMTA (1), 2023)

Local Information in Global Optimization with Dimensionality Reduction Schemes. - Dmitri E. Kvasov; Vladimir A. Grishagin (NUMTA (1), 2023)

Comparative Efficiency of Machine Learning Models for Enhancing Algorithms in Solving Multiextremal Multicriteria Problems. - Sergey Konnov; Evgeny Kozinov; Konstantin Barkalov; Vladimir A. Grishagin (OPTIMA, 2024)