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3.1.4 Steady State Probability

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Vishal Tidake
Vishal Tidake

Steady State Probability

Data & Analytics
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www.sanjivanimba.org.in Unit No.3. DECISION SCIENCE Presented By: Dr. V. M. Tidake Ph. D (Financial Management), MBA(FM), MBA(HRM) BE(Chem) Dean, EDP & Associate Professor MBA 1 Sanjivani College of Engineering, Kopargaon Department of MBA www.sanjivanimba.org.in
www.sanjivanimba.org.in 302-DECISION SCIENCE Unit No.3 Marko Chain & Simulation 3.1.3 Steady State Probability in Markov Chain Presented By: Dr. V. M. Tidake Ph. D (Financial Management), MBA(FM), MBA(HRM) BE(Chem) Dean EDP & Associate Professor MBA 2 Sanjivani College of Engineering, Kopargaon Department of MBA www.sanjivanimba.org.in
www.sanjivanimba.org.in MARKOV CHAIN & SIMULATION  At the End of the Session Student will be able to understand- A. Steady State Probability in Markov Chain
www.sanjivanimba.org.in MARKOV CHAIN If the transitions from one state to the others continue indefinitely, we reach a stage where the system becomes stable and the state probabilities tend to remain constant. This is the steady state equilibrium in Markov Chain. This is symbolically given by- RK = Rk-1 And as we have- RK = Rk-1 * P RK = Rk * P - (As Rk=Rk-1) Thus, if SA, SB & SC are the steady state probabilities then- . SA SB SC = SA SB SC * P Also we always have SA + SB + SC = 1 Solving these two equations simultaneously, we get the values of steady state probabilities SA, SB & SC.
www.sanjivanimba.org.in EXERCISE  What do you mean by Steady State Probability in Markov Chain. How to proceed in case of Steady State in Markov Chain.
www.sanjivanimba.org.in For More Details Contact Dr. V M Tidake tidkevishal@gmail.com tidkevishalmba@sanjivani.org.in
www.sanjivanimba.org.in Thank You

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3.1.4 Steady State Probability

  • 1. www.sanjivanimba.org.in Unit No.3. DECISION SCIENCE Presented By: Dr. V. M. Tidake Ph. D (Financial Management), MBA(FM), MBA(HRM) BE(Chem) Dean, EDP & Associate Professor MBA 1 Sanjivani College of Engineering, Kopargaon Department of MBA www.sanjivanimba.org.in
  • 2. www.sanjivanimba.org.in 302-DECISION SCIENCE Unit No.3 Marko Chain & Simulation 3.1.3 Steady State Probability in Markov Chain Presented By: Dr. V. M. Tidake Ph. D (Financial Management), MBA(FM), MBA(HRM) BE(Chem) Dean EDP & Associate Professor MBA 2 Sanjivani College of Engineering, Kopargaon Department of MBA www.sanjivanimba.org.in
  • 3. www.sanjivanimba.org.in MARKOV CHAIN & SIMULATION  At the End of the Session Student will be able to understand- A. Steady State Probability in Markov Chain
  • 4. www.sanjivanimba.org.in MARKOV CHAIN If the transitions from one state to the others continue indefinitely, we reach a stage where the system becomes stable and the state probabilities tend to remain constant. This is the steady state equilibrium in Markov Chain. This is symbolically given by- RK = Rk-1 And as we have- RK = Rk-1 * P RK = Rk * P - (As Rk=Rk-1) Thus, if SA, SB & SC are the steady state probabilities then- . SA SB SC = SA SB SC * P Also we always have SA + SB + SC = 1 Solving these two equations simultaneously, we get the values of steady state probabilities SA, SB & SC.
  • 5. www.sanjivanimba.org.in EXERCISE  What do you mean by Steady State Probability in Markov Chain. How to proceed in case of Steady State in Markov Chain.
  • 6. www.sanjivanimba.org.in For More Details Contact Dr. V M Tidake tidkevishal@gmail.com tidkevishalmba@sanjivani.org.in