AbstractA statistical model for global optimization is constructed generalizing some properties of the Wiener process to the multidimensional case. An approach to the construction of global optimization algorithms is developed using the proposed statistical model. The convergence of an algorithm based on the constructed statistical model and simplicial partitioning is proved. Several versions of the algorithm are implemented and investigated
DoctorNested partitions (NP) method is a new type of random search method for global optimization pr...
We study a class of random sampling-based algorithms for solving general non-convex, nondifferentiab...
Simulated annealing is a global optimization method that distinguishes between different local optim...
AbstractA statistical model for global optimization is constructed generalizing some properties of t...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
Stochastic global optimization methods are methods for solving a global optimization prob-lem incorp...
This paper will discuss the randomness and normality tests of the data collected by splitting the in...
In this paper we are concerned with global optimization, which can be defined as the problem of find...
Algorithms based on statistical models compete favorably with other global optimization algorithms a...
This thesis looks at some theoretical and practical aspects of global optimization - as we shall see...
On t.p. "d̳" is superscript. Cover title.Includes bibliographical references (p. 28-29).Research su...
In this paper several probabilistic search techniques are developed for global optimization under th...
Stochastic methods for global optimization problems with continuous variables have been studied. Mod...
On cover "d̳" indicates superscript. Cover title.Includes bibliographical references (leaf 35).Rese...
Model-based optimization methods are a class of random search methods that are useful for solving gl...
DoctorNested partitions (NP) method is a new type of random search method for global optimization pr...
We study a class of random sampling-based algorithms for solving general non-convex, nondifferentiab...
Simulated annealing is a global optimization method that distinguishes between different local optim...
AbstractA statistical model for global optimization is constructed generalizing some properties of t...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
Stochastic global optimization methods are methods for solving a global optimization prob-lem incorp...
This paper will discuss the randomness and normality tests of the data collected by splitting the in...
In this paper we are concerned with global optimization, which can be defined as the problem of find...
Algorithms based on statistical models compete favorably with other global optimization algorithms a...
This thesis looks at some theoretical and practical aspects of global optimization - as we shall see...
On t.p. "d̳" is superscript. Cover title.Includes bibliographical references (p. 28-29).Research su...
In this paper several probabilistic search techniques are developed for global optimization under th...
Stochastic methods for global optimization problems with continuous variables have been studied. Mod...
On cover "d̳" indicates superscript. Cover title.Includes bibliographical references (leaf 35).Rese...
Model-based optimization methods are a class of random search methods that are useful for solving gl...
DoctorNested partitions (NP) method is a new type of random search method for global optimization pr...
We study a class of random sampling-based algorithms for solving general non-convex, nondifferentiab...
Simulated annealing is a global optimization method that distinguishes between different local optim...