Markov Chains and Decision Processes for Engineers and Managers

Regular price €82.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Theodore J. Sheskin
absorbing
Absorbing Markov Chain
Absorbing State
Author_Theodore J. Sheskin
Cash Fl Ow Diagram
Category=PBT
decision analysis
Discounted Rewards
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Expected Shortage Cost
Fi Nite Planning Horizon
Fi Rst Passage
Fi Rst Passage Time
Fundamental Matrix
Hidden Markov Chain
Infi Nite Horizon
Initial State Probability Vector
inventory control methods
Markov Chain
Markov decision process modeling for engineering
matrix
Matrix Reduction
Observation Symbol
operational research
Planning Horizon
probability
queueing theory applications
recurrent
Recurrent Chain
Recurrent States
regular
Regular Markov Chain
Reward Vector
state
states
steady
Steady State Probabilities
Steady State Probability Vector
stochastic modeling
system optimization techniques
Transient States
transition
Transition Matrix
Transition Probability Matrix
vector

Product details

  • ISBN 9780367383435
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 19 Sep 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
Secure checkout Fast Shipping Easy returns

Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and service systems. However, most books on Markov chains or decision processes are often either highly theoretical, with few examples, or highly prescriptive, with little justification for the steps of the algorithms used to solve Markov models. Providing a unified treatment of Markov chains and Markov decision processes in a single volume, Markov Chains and Decision Processes for Engineers and Managers supplies a highly detailed description of the construction and solution of Markov models that facilitates their application to diverse processes.

Organized around Markov chain structure, the book begins with descriptions of Markov chain states, transitions, structure, and models, and then discusses steady state distributions and passage to a target state in a regular Markov chain. The author treats canonical forms and passage to target states or to classes of target states for reducible Markov chains. He adds an economic dimension by associating rewards with states, thereby linking a Markov chain to a Markov decision process, and then adds decisions to create a Markov decision process, enabling an analyst to choose among alternative Markov chains with rewards so as to maximize expected rewards. An introduction to state reduction and hidden Markov chains rounds out the coverage.

In a presentation that balances algorithms and applications, the author provides explanations of the logical relationships that underpin the formulas or algorithms through informal derivations, and devotes considerable attention to the construction of Markov models. He constructs simplified Markov models for a wide assortment of processes such as the weather, gambling, diffusion of gases, a waiting line, inventory, component replacement, machine maintenance, selling a stock, a charge account, a career path, patient flow

Sheskin, Theodore J.

More from this author