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Nikolai Krivulin

Publications and source records attributed to Nikolai Krivulin.

44 records · Page 3Linked to original sources
arXiv2012

Evaluation of the mean cycle time in stochastic discrete event dynamic systems

We consider stochastic discrete event dynamic systems that have time evolution represented with two-dimensional state vectors through a vector equation that is linear in terms of an idempotent semiring. The state transitions are governed by second-order random matrices that are assumed to be independent and identically distributed. The problem of interest is to evaluate the mean growth rate of state vector, which is also referred to as the mean cycle time of the system, under various assumptions on the matrix entries. We give an overview of early results including a solution for systems determined by matrices with independent entries having a common exponential distribution. It is shown how to extend the result to the cases when the entries have different exponential distributions and when some of the entries are replaced by zero. Finally, the mean cycle time is calculated for systems with matrices that have one random entry, whereas the other entries in the matrices can be arbitrary nonnegative and zero constants. The random entry is always assumed to have exponential distribution except for one case of a matrix with zero row when the particular form of the matrix makes it possible to obtain a solution that does not rely on exponential distribution assumptions.

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arXiv2012

An algebraic approach to multidimensional minimax location problems with Chebyshev distance

Minimax single facility location problems in multidimensional space with Chebyshev distance are examined within the framework of idempotent algebra. The aim of the study is twofold: first, to give a new algebraic solution to the location problems, and second, to extend the area of application of idempotent algebra. A new algebraic approach based on investigation of extremal properties of eigenvalues for irreducible matrices is developed to solve multidimensional problems that involve minimization of functionals defined on idempotent vector semimodules. Furthermore, an unconstrained location problem is considered and then represented in the idempotent algebra settings. A new algebraic solution is given that reduces the problem to evaluation of the eigenvalue and eigenvectors of an appropriate matrix. Finally, the solution is extended to solve a constrained location problem.

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arXiv2012

An algebraic approach to project schedule development under precedence constraints

An approach to schedule development in project management is developed within the framework of idempotent algebra. The approach offers a way to represent precedence relationships among activities in projects as linear vector equations in terms of an idempotent semiring. As a result, many issues in project scheduling reduce to solving computational problems in the idempotent algebra setting, including linear equations and eigenvalue-eigenvector problems. The solutions to the problems are given in a compact vector form that provides the basis for the development of efficient computation procedures and related software applications.

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arXiv2012

Unbiased estimates for gradients of stochastic network performance measures

Three classes of stochastic networks and their performance measures are considered. These performance measures are defined as the expected value of some random variables and cannot normally be obtained analytically as functions of network parameters in a closed form. We give similar representations for the random variables to provide a useful way of analytical study of these functions and their gradients. The representations are used to obtain sufficient conditions for the gradient estimates to be unbiased. The conditions are rather general and usually met in simulation study of the stochastic networks. Applications of the results are discussed and some practical algorithms of calculating unbiased estimates of the gradients are also presented.

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arXiv2012

A new algebraic solution to multidimensional minimax location problems with Chebyshev distance

Both unconstrained and constrained minimax single facility location problems are considered in multidimensional space with Chebyshev distance. A new solution approach is proposed within the framework of idempotent algebra to reduce the problems to solving linear vector equations and minimizing functionals defined on some idempotent semimodule. The approach offers a solution in a closed form that actually involves performing matrix-vector multiplications in terms of idempotent algebra for appropriate matrices and vectors. To illustrate the solution procedures, numerical and graphical examples of two-dimensional problems are given.

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arXiv2012

An analysis of the least median of squares regression problem

The optimization problem that arises out of the least median of squared residuals method in linear regression is analyzed. To simplify the analysis, the problem is replaced by an equivalent one of minimizing the median of absolute residuals. A useful representation of the last problem is given to examine properties of the objective function and estimate the number of its local minima. It is shown that the exact number of local minima is equal to $ {p+\lfloor (n-1)/2 \rfloor \choose{p}} $, where $ p $ is the dimension of the regression model and $ n $ is the number of observations. As applications of the results, three algorithms are also outlined.

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arXiv2012

A complete closed-form solution to a tropical extremal problem

A multidimensional extremal problem in the idempotent algebra setting is considered which consists in minimizing a nonlinear functional defined on a finite-dimensional semimodule over an idempotent semifield. The problem integrates two other known problems by combining their objective functions into one general function and includes these problems as particular cases. A new solution approach is proposed based on the analysis of linear inequalities and spectral properties of matrices. The approach offers a comprehensive solution to the problem in a closed form that involves performing simple matrix and vector operations in terms of idempotent algebra and provides a basis for the development of efficient computational algorithms and their software implementation.

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