76 citations · 306 across the 7 of their papers we have counts for
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Safe global optimization of expensive noisy black-box functions in the -Lipschitz framework
Yaroslav D. Sergeyev, Antonio Candelieri, Dmitri E. Kvasov +1
In this paper, the problem of safe global maximization (it should not be confused with robust optimization) of expensive noisy black-box functions satisfying the Lipschitz conditio…
On strong homogeneity of a class of global optimization algorithms working with infinite and infinitesimal scales
Yaroslav D. Sergeyev, Dmitri E. Kvasov, Marat S. Mukhametzhanov
The necessity to find the global optimum of multiextremal functions arises in many applied problems where finding local solutions is insufficient. One of the desirable properties o…
Deterministic approaches for solving practical black-box global optimization problems
Dmitri E. Kvasov, Yaroslav D. Sergeyev
In many important design problems, some decisions should be made by finding the global optimum of a multiextremal objective function subject to a set of constrains. Frequently, esp…
A deterministic global optimization using smooth diagonal auxiliary functions
Yaroslav D. Sergeyev, Dmitri E. Kvasov
In many practical decision-making problems it happens that functions involved in optimization process are black-box with unknown analytical representations and hard to evaluate. In…
Lipschitz gradients for global optimization in a one-point-based partitioning scheme
Dmitri E. Kvasov, Yaroslav D. Sergeyev
A global optimization problem is studied where the objective function is a multidimensional black-box function and its gradient satisfies the Lipschitz condition ove…
A One-Dimensional Local Tuning Algorithm for Solving GO Problems with Partially Defined Constraints
Yaroslav D. Sergeyev, Dmitri E. Kvasov, Falah M. H. Khalaf
Lipschitz one-dimensional constrained global optimization (GO) problems where both the objective function and constraints can be multiextremal and non-differentiable are considered…