SlideShare ist ein Scribd-Unternehmen logo
1 von 8
Downloaden Sie, um offline zu lesen
Chapter 14R (14.1 -
14.5) Waiting Line Models
     Matt Levy ISDS 2001
Introduction
Models to help managers understand and make decisions on the
operation of waiting lines.

Also known as a queue -- waiting line models are based on queueing
theory.

We are interested in the operating characteristics (a.k.a performance
characteristics) of waiting lines, which include the following:
 1. The probability that no units are in the system.
 2. The average number of units in the waiting line.
 3. The average number of units in the system (number of units in
    the waiting line + number being served)
 4. The average time a unit spends in the waiting line.
 5. The average time a unit spends in the system (waiting time +
    service time)
 6. The probability that an arriving unit has to wait for service.
General Waiting Line System Characteristics
Single Channel Waiting Line - Each customer entering an establishment passes through
one channel -- for example, one line and one order taking and filling station.

For most waiting line situations customer arrivals occur randomly and independently.

Quantitative analysts have found the Poisson distribution provides a good distribution
of the arrival pattern.

The probability function is as follows:


x = the number of arrivals in the time period
λ = the mean number of arrivals per time period (arrival rate)
e = 2.71828

While we can use this, in practice data should be recorded over a period of several days
or weeks and compared to the Poisson distribution.
General Waiting Line System Characteristics
Distribution of Service Times - the time a customer spends at a
service facility once a service has started.

Service time has been found to have an exponential probability
distribution.


µ = the mean number of units that can be served per time period (service rate)
e = 2.71828

Again, while we can use this, in practice data should be recorded over a period of
several days or weeks and compared to the Exponential distribution.

Additional Terms:
FCFS - First come first served -- this is the model we use in this section.
Transient Period - the beginning or start up period.
Steady-State Operation - normal state of operations.
Operating Characteristics - Single Channel Waiting Line Model with
Poisson Arrivals and Exponential Service Times
Operating Characteristics - Multiple Channel Waiting Line Model
with Poisson Arrivals and Exponential Service Times
These formulas are only applicable if:
  1. The arrivals follow a Poisson
     probability distribution
  2. The service time for each channel
     follows an exponential probability
     distribution.

λ = the arrival rate
µ = service rate
k = number of channels
General Relationships for Waiting Line
Models (this means shortcuts!)
The End

Problems: 1, 2-15 evens, but try the odds as well

See you Wednesday!

Weitere ähnliche Inhalte

Was ist angesagt? (20)

Operational research queuing theory
Operational research queuing theoryOperational research queuing theory
Operational research queuing theory
 
Queueing Theory and its BusinessS Applications
Queueing Theory and its BusinessS ApplicationsQueueing Theory and its BusinessS Applications
Queueing Theory and its BusinessS Applications
 
Waiting lines
Waiting linesWaiting lines
Waiting lines
 
Queuing theory .
Queuing theory .Queuing theory .
Queuing theory .
 
Queuing Theory
Queuing TheoryQueuing Theory
Queuing Theory
 
Queuing unit v ppt
Queuing unit v pptQueuing unit v ppt
Queuing unit v ppt
 
Waiting Line Management Problem Solution, Writer Jacobs (1-15)
Waiting Line Management Problem Solution, Writer Jacobs (1-15)Waiting Line Management Problem Solution, Writer Jacobs (1-15)
Waiting Line Management Problem Solution, Writer Jacobs (1-15)
 
Q theory
Q theoryQ theory
Q theory
 
Queue
QueueQueue
Queue
 
Queueing theory
Queueing theoryQueueing theory
Queueing theory
 
Queing theory and delay analysis
Queing theory and delay analysisQueing theory and delay analysis
Queing theory and delay analysis
 
Queuing theory
Queuing theoryQueuing theory
Queuing theory
 
Unit 4 queuing models
Unit 4 queuing modelsUnit 4 queuing models
Unit 4 queuing models
 
Queuing theory and simulation (MSOR)
Queuing theory and simulation (MSOR)Queuing theory and simulation (MSOR)
Queuing theory and simulation (MSOR)
 
Ramniwas final
Ramniwas finalRamniwas final
Ramniwas final
 
Queuing theory
Queuing theoryQueuing theory
Queuing theory
 
Queuing theory
Queuing theoryQueuing theory
Queuing theory
 
queueing problems in banking
queueing problems in bankingqueueing problems in banking
queueing problems in banking
 
Queuing Theory
Queuing TheoryQueuing Theory
Queuing Theory
 
Queuing Theory
Queuing TheoryQueuing Theory
Queuing Theory
 

Andere mochten auch

Andere mochten auch (6)

File storageandbackupsystems
File storageandbackupsystemsFile storageandbackupsystems
File storageandbackupsystems
 
London School of English Google Drive
London School of English Google DriveLondon School of English Google Drive
London School of English Google Drive
 
Share point 2010
Share point 2010Share point 2010
Share point 2010
 
FM3 - Lesson 4 - One Drive
FM3 - Lesson 4 - One DriveFM3 - Lesson 4 - One Drive
FM3 - Lesson 4 - One Drive
 
drive, one drive, dropbox
drive, one drive, dropboxdrive, one drive, dropbox
drive, one drive, dropbox
 
Slideshare ppt
Slideshare pptSlideshare ppt
Slideshare ppt
 

Ähnlich wie Chapter 14R

chapter11 liner model programing.pptx
chapter11 liner model programing.pptxchapter11 liner model programing.pptx
chapter11 liner model programing.pptxJAMESFRANCISGOSE
 
solving restaurent model problem by using queueing theory
solving restaurent model problem by using queueing theorysolving restaurent model problem by using queueing theory
solving restaurent model problem by using queueing theorySubham kumar
 
Queuing theory and its applications
Queuing theory and its applicationsQueuing theory and its applications
Queuing theory and its applicationsDebasisMohanty37
 
Management Queuing theory Lec 2
Management Queuing theory Lec 2Management Queuing theory Lec 2
Management Queuing theory Lec 2cairo university
 
Queuing Theory
Queuing TheoryQueuing Theory
Queuing TheoryDallina1
 
Opersea report waiting lines and queuing theory
Opersea report waiting lines and queuing theoryOpersea report waiting lines and queuing theory
Opersea report waiting lines and queuing theoryIsaac Andaya
 
Decision Sciences_SBS_9.pdf
Decision Sciences_SBS_9.pdfDecision Sciences_SBS_9.pdf
Decision Sciences_SBS_9.pdfKhushbooJoshiSBS
 
Operations Research_18ME735_module 4 - queuing systems.pdf
Operations Research_18ME735_module 4 - queuing systems.pdfOperations Research_18ME735_module 4 - queuing systems.pdf
Operations Research_18ME735_module 4 - queuing systems.pdfRoopaDNDandally
 
International Journal of Mathematics and Statistics Invention (IJMSI)
International Journal of Mathematics and Statistics Invention (IJMSI) International Journal of Mathematics and Statistics Invention (IJMSI)
International Journal of Mathematics and Statistics Invention (IJMSI) inventionjournals
 
Queuing theory network
Queuing theory networkQueuing theory network
Queuing theory networkAmit Dahal
 
4-Queuing-System-ioenotes.pdf
4-Queuing-System-ioenotes.pdf4-Queuing-System-ioenotes.pdf
4-Queuing-System-ioenotes.pdfubaidullah75790
 
ch06-Queuing & Simulation.ppt
ch06-Queuing & Simulation.pptch06-Queuing & Simulation.ppt
ch06-Queuing & Simulation.pptLuckySaigon1
 

Ähnlich wie Chapter 14R (20)

chapter11 liner model programing.pptx
chapter11 liner model programing.pptxchapter11 liner model programing.pptx
chapter11 liner model programing.pptx
 
Queuing Theory by Dr. B. J. Mohite
Queuing Theory by Dr. B. J. MohiteQueuing Theory by Dr. B. J. Mohite
Queuing Theory by Dr. B. J. Mohite
 
Queueing Theory.pptx
Queueing Theory.pptxQueueing Theory.pptx
Queueing Theory.pptx
 
QUEUING THEORY
QUEUING THEORY QUEUING THEORY
QUEUING THEORY
 
solving restaurent model problem by using queueing theory
solving restaurent model problem by using queueing theorysolving restaurent model problem by using queueing theory
solving restaurent model problem by using queueing theory
 
Queuing theory and its applications
Queuing theory and its applicationsQueuing theory and its applications
Queuing theory and its applications
 
Management Queuing theory Lec 2
Management Queuing theory Lec 2Management Queuing theory Lec 2
Management Queuing theory Lec 2
 
Queuing Theory
Queuing TheoryQueuing Theory
Queuing Theory
 
Opersea report waiting lines and queuing theory
Opersea report waiting lines and queuing theoryOpersea report waiting lines and queuing theory
Opersea report waiting lines and queuing theory
 
Operation Research
Operation ResearchOperation Research
Operation Research
 
Decision Sciences_SBS_9.pdf
Decision Sciences_SBS_9.pdfDecision Sciences_SBS_9.pdf
Decision Sciences_SBS_9.pdf
 
Operations Research_18ME735_module 4 - queuing systems.pdf
Operations Research_18ME735_module 4 - queuing systems.pdfOperations Research_18ME735_module 4 - queuing systems.pdf
Operations Research_18ME735_module 4 - queuing systems.pdf
 
Unit 3 des
Unit 3 desUnit 3 des
Unit 3 des
 
International Journal of Mathematics and Statistics Invention (IJMSI)
International Journal of Mathematics and Statistics Invention (IJMSI) International Journal of Mathematics and Statistics Invention (IJMSI)
International Journal of Mathematics and Statistics Invention (IJMSI)
 
QUEUEING THEORY
QUEUEING THEORYQUEUEING THEORY
QUEUEING THEORY
 
Waiting Lines.pptx
Waiting Lines.pptxWaiting Lines.pptx
Waiting Lines.pptx
 
Queuing theory network
Queuing theory networkQueuing theory network
Queuing theory network
 
Queuing theory
Queuing theoryQueuing theory
Queuing theory
 
4-Queuing-System-ioenotes.pdf
4-Queuing-System-ioenotes.pdf4-Queuing-System-ioenotes.pdf
4-Queuing-System-ioenotes.pdf
 
ch06-Queuing & Simulation.ppt
ch06-Queuing & Simulation.pptch06-Queuing & Simulation.ppt
ch06-Queuing & Simulation.ppt
 

Mehr von Matthew L Levy

Mehr von Matthew L Levy (10)

Chapter 15R Lecture
Chapter 15R LectureChapter 15R Lecture
Chapter 15R Lecture
 
Chapter 5R
Chapter 5RChapter 5R
Chapter 5R
 
Chapter 4R Part II
Chapter 4R Part IIChapter 4R Part II
Chapter 4R Part II
 
Chapter 4 R Part I
Chapter 4 R Part IChapter 4 R Part I
Chapter 4 R Part I
 
Chapter 20 Lecture Notes
Chapter 20 Lecture NotesChapter 20 Lecture Notes
Chapter 20 Lecture Notes
 
Chapter 18 Part I
Chapter 18 Part IChapter 18 Part I
Chapter 18 Part I
 
Chapter 16
Chapter 16Chapter 16
Chapter 16
 
Chapter 15
Chapter 15Chapter 15
Chapter 15
 
Chapter 14 Part Ii
Chapter 14 Part IiChapter 14 Part Ii
Chapter 14 Part Ii
 
Chapter 14 Part I
Chapter 14 Part IChapter 14 Part I
Chapter 14 Part I
 

Chapter 14R

  • 1. Chapter 14R (14.1 - 14.5) Waiting Line Models Matt Levy ISDS 2001
  • 2. Introduction Models to help managers understand and make decisions on the operation of waiting lines. Also known as a queue -- waiting line models are based on queueing theory. We are interested in the operating characteristics (a.k.a performance characteristics) of waiting lines, which include the following: 1. The probability that no units are in the system. 2. The average number of units in the waiting line. 3. The average number of units in the system (number of units in the waiting line + number being served) 4. The average time a unit spends in the waiting line. 5. The average time a unit spends in the system (waiting time + service time) 6. The probability that an arriving unit has to wait for service.
  • 3. General Waiting Line System Characteristics Single Channel Waiting Line - Each customer entering an establishment passes through one channel -- for example, one line and one order taking and filling station. For most waiting line situations customer arrivals occur randomly and independently. Quantitative analysts have found the Poisson distribution provides a good distribution of the arrival pattern. The probability function is as follows: x = the number of arrivals in the time period λ = the mean number of arrivals per time period (arrival rate) e = 2.71828 While we can use this, in practice data should be recorded over a period of several days or weeks and compared to the Poisson distribution.
  • 4. General Waiting Line System Characteristics Distribution of Service Times - the time a customer spends at a service facility once a service has started. Service time has been found to have an exponential probability distribution. µ = the mean number of units that can be served per time period (service rate) e = 2.71828 Again, while we can use this, in practice data should be recorded over a period of several days or weeks and compared to the Exponential distribution. Additional Terms: FCFS - First come first served -- this is the model we use in this section. Transient Period - the beginning or start up period. Steady-State Operation - normal state of operations.
  • 5. Operating Characteristics - Single Channel Waiting Line Model with Poisson Arrivals and Exponential Service Times
  • 6. Operating Characteristics - Multiple Channel Waiting Line Model with Poisson Arrivals and Exponential Service Times These formulas are only applicable if: 1. The arrivals follow a Poisson probability distribution 2. The service time for each channel follows an exponential probability distribution. λ = the arrival rate µ = service rate k = number of channels
  • 7. General Relationships for Waiting Line Models (this means shortcuts!)
  • 8. The End Problems: 1, 2-15 evens, but try the odds as well See you Wednesday!