000			01921cam a2200253 i 4500
001			23581039
005			20250630102705.0
008			240227s2024 nju b 000 0 eng
020			_a9789811286155
040			_aCSL _cCSL
041			_2eng _aeng
084			_aB281N07 R4 _qCSL
100	1		_aAndronov, Alexander _eauthor. _9810070
245	1	0	_aContinuous-time Markov-modulated chains in operations research
260			_aNew Jersey : _bWorld Scientific, _c2024.
300			_axvi, 210p. _b: ill. _c; 24 cm.
504			_aIncludes bibliographical references.
520			_a"Probabilistic models are widely used for description and an analysis of various processes in system reliability, risk, queuing, data communication, logistic and storage systems. The book contains various applications of the theory of continuous-time Markov-modulated processes in operation research. All analytical results are illustrated by numerical computations. Used algorithms allow overcoming computation difficulties successfully. For example, a calculation of transient probabilities of states for a continuous-time finite Markov chain is used eigenvalues and eigenvectors of the corresponding matrix (generator). In a more complex case of differential or integral equations, such a simple explicit form of a solution is missing. The explicit form of solution is presented by means of infinity sums of functions. For example, often we have to deal with the so-called renewal equation. Its solution is presented as an infinite sum of the renewal function. In this case, an approximation of functions of interest and iterative computation procedures are used"--
650		0	_aMarkov processes. _9449609
650		0	_aPoisson processes. _9716530
650		0	_aOperations research.
700	1		_aMahareva, Kristina _eco-author. _9810071
942			_2CC _cTEXL _hB281N07 R4 _n0
999			_c1433095 _d1433095