Numerical Methods for Simulation and Optimization of Piecewise Deterministic Markov Processes

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A01=Benoite de Saporta
A01=Francois Dufour
A01=Huilong Zhang
assumptions
Author_Benoite de Saporta
Author_Francois Dufour
Author_Huilong Zhang
boundary
Category=PBKS
Category=PBU
characteristics
definition
deterministic
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
introduction
ix
lipschitregularity
local
markovchain
part
pdmp
processes
quantization
random
reliability
subject
time
variable

Product details

  • ISBN 9781848218390
  • Weight: 590g
  • Dimensions: 163 x 241mm
  • Publication Date: 15 Dec 2015
  • Publisher: ISTE Ltd and John Wiley & Sons Inc
  • Publication City/Country: GB
  • Product Form: Hardback
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Mark H.A. Davis introduced the Piecewise-Deterministic Markov Process (PDMP) class of stochastic hybrid models in an article in 1984. Today it is used to model a variety of complex systems in the fields of engineering, economics, management sciences, biology, Internet traffic, networks and many more. Yet, despite this, there is very little in the way of literature devoted to the development of numerical methods for PDMDs to solve problems of practical importance, or the computational control of PDMPs.

This book therefore presents a collection of mathematical tools that have been recently developed to tackle such problems. It begins by doing so through examples in several application domains such as reliability. The second part is devoted to the study and simulation of expectations of functionals of PDMPs. Finally, the third part introduces the development of numerical techniques for optimal control problems such as stopping and impulse control problems.

Benoîte de Saporta is Professor in Applied Probabilities at the University of Montpellier 2 in France.

François Dufour is Professor at the University of Bordeaux in France.

Huilong Zhang is a lecturer at INRIA in Bordeaux, France.

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