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
A stochastic method for global optimization is described and evaluated. The method involves a combin...
AbstractRationalization processes are proposed to improve uniformity in small samples for pseudorand...
DoctorNested partitions (NP) method is a new type of random search method for global optimization pr...
AbstractA statistical model for global optimization is constructed generalizing some properties of t...
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...
Stochastic global optimization methods are methods for solving a global optimization prob-lem incorp...
Algorithms based on statistical models compete favorably with other global optimization algorithms a...
The global optimization of a mathematical model determines the best parameters such that a target or...
The global optimization of a mathematical model determines the best parameters such that a target or...
This thesis looks at some theoretical and practical aspects of global optimization - as we shall see...
The purpose of the paper is to develop and study new techniques for global optimization based on dyn...
Current research results in stochastic and deterministic global optimization including single and mu...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
Simulated annealing is a global optimization method that distinguishes between different local optim...
A stochastic method for global optimization is described and evaluated. The method involves a combin...
AbstractRationalization processes are proposed to improve uniformity in small samples for pseudorand...
DoctorNested partitions (NP) method is a new type of random search method for global optimization pr...
AbstractA statistical model for global optimization is constructed generalizing some properties of t...
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...
Stochastic global optimization methods are methods for solving a global optimization prob-lem incorp...
Algorithms based on statistical models compete favorably with other global optimization algorithms a...
The global optimization of a mathematical model determines the best parameters such that a target or...
The global optimization of a mathematical model determines the best parameters such that a target or...
This thesis looks at some theoretical and practical aspects of global optimization - as we shall see...
The purpose of the paper is to develop and study new techniques for global optimization based on dyn...
Current research results in stochastic and deterministic global optimization including single and mu...
Many problems in economy may be formulated as global optimization problems. Most numerically promisi...
Simulated annealing is a global optimization method that distinguishes between different local optim...
A stochastic method for global optimization is described and evaluated. The method involves a combin...
AbstractRationalization processes are proposed to improve uniformity in small samples for pseudorand...
DoctorNested partitions (NP) method is a new type of random search method for global optimization pr...