The book presents new methods of asymptotic analysis for nonlinearly perturbed semi-
Markov processes with finite phase spaces. These methods are based on special time …

In time series analysis, when fitting an autoregressive model, one must solve a Toeplitz
ordinary least squares problem numerous times to find an appropriate model, which can …

In Chapter 4, new algorithms for construction of asymptotic expansions for stationary
distributions of nonlinearly perturbed semi-Markov processes with finite phase spaces are …

We study a certain polytope arising from embedding the Hamiltonian cycle problem in a
discounted Markov decision process. The Hamiltonian cycle problem can be reduced to …

In Chapter 3, we introduce a model of perturbed semi-Markov processes, formulate basic
perturbation conditions, describe a one-step time-space screening procedure of phase …

We study the embedding of the Hamiltonian Cycle problem, on a symmetric graph, in a
discounted Markov decision process. The embedding allows us to explore the space of …

Markov decision processes continue to gain in popularity for modeling a wide range of
applications ranging from analysis of supply chains and queuing networks to cognitive …

Characterising the smallest dimension polytope containing all integer solutions of an integer
programming problem can be a very challenging task. Frequently, this task is facilitated by …

We analyse a polyhedron which contains the convex hull of all Hamiltonian cycles of a given
undirected connected cubic graph. Our constructed polyhedron is defined by polynomially …

We study a certain polytope depending on a graph G and a parameter β∈(0, 1) that arises
from embedding the Hamiltonian cycle problem in a discounted Markov decision process …