'Service time distribution' diaporamas de présentation

Facilities Design

Facilities Design. S.S. Heragu Industrial Engineering Department University of Louisville. Appendix: Introduction to Queuing, Queuing Network, and Simulation Modeling. A queuing system. Queuing Models are descriptive models. What is the expected number of parts waiting in a queue?

838 views • 66 slides

Queuing Theory

Queuing Theory. A brief review of probability. Continuous Random Variables. Random Variable X F(x)=Pr(X ?x) is distribution function f(x)=d/dx F(x) is density function E(X)=? =is mean or average E(X 2 ) second moment Var(X)=E(X 2 )- ? 2. Probability. X is the max of two dice

682 views • 54 slides

Queueing Theory

1.28k views • 50 slides

Operations Management

608 views • 49 slides

Operations Management

641 views • 49 slides

Simulation

555 views • 42 slides

Chapter 5 Statistical Models in Simulation

Chapter 5 Statistical Models in Simulation. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation. Purpose & Overview. The world the model-builder sees is probabilistic rather than deterministic. Some statistical model might well describe the variations.

668 views • 37 slides

Chapter 5 Statistical Models in Simulation

Chapter 5 Statistical Models in Simulation. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation. Purpose & Overview. The world the model-builder sees is probabilistic rather than deterministic. Some statistical model might well describe the variations.

777 views • 37 slides

Simulation

Simulation. 1. Overview of Simulation. When do we prefer to develop simulation model over an analytic model? When not all the underlying assumptions set for analytic model are valid. When mathematical complexity makes it hard to provide useful results.

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On the Gittins index in the M/G/1 queue

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On the Gittins index in the M/G/1 queue

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Analysis of M/M/1, M/M/c, and M/M/c/c

Analysis of M/M/1, M/M/c, and M/M/c/c. AGENDA. Markov Chain Basic Queueing Analysis of M/M/1 Analysis of M/M/c Analysis of M/M/c/c. Markov Chain. Markov Chain is a random process with the property that the next state depends only on the current state Transition probabilities P ij

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Flows and Networks Plan for today (lecture 4):

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OPSM 301: Operations Management

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OPSM 301: Operations Management

359 views • 24 slides

Queueing Theory II

Queueing Theory II. Summary. M/M/1 Output process Networks of Queue Method of Stages Erlang Distribution Hyperexponential Distribution General Distributions Embedded Markov Chains. M/M/1 Output Process. A k. I k. Z k. Z k. Y k. Y k. Interdeparture Time. D k- 1. D k- 1. D k. D k.

446 views • 23 slides

CS SOR: Polling models

CS SOR: Polling models. Vacation models Multi type branching processes Polling systems (cycle times, queue lengths, waiting times, conservation laws, service policies, visit orders). Richard J. Boucherie department of Applied Mathematics University of Twente. Polling models.

370 views • 23 slides

Queueing Theory II

Queueing Theory II. Summary. M/M/1 Output process Networks of Queue Method of Stages Erlang Distribution Hyperexponential Distribution General Distributions Embedded Markov Chains. M/M/1 Output Process. A k. I k. Z k. Z k. Y k. Y k. Interdeparture Time. D k- 1. D k- 1. D k. D k.

421 views • 23 slides

Queue theory

Queue theory. 1.1.????? ??? ?? ?? ????? ? ????? ? ??????? ????? ?? ( Queue ) ?? ?? ?????? ( Waiting Line ) ?? ??????? ? ?? ???? ????? ??? ????? ?? ?????? ???. ?? ????? ??? ???? ?? ?? ???? ?? ????:. 1.1 Examples. Example 1.1.1 Supermarket .

367 views • 21 slides

Probabilistic Models

Probabilistic Models. University of Palestine. Operations Research. Queuing Theory. Prepared By :. Sheren Mohammed abo mousa 120060147. Supervisor. Dr . Sana'a. Waiting Line Models. The Structure of a Waiting Line System. Queuing Systems. Queuing System Input Characteristics .

383 views • 19 slides