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QMD: Waiting-line analysis

QMD Waiting Lines

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QMD: Waiting-line

analysis

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Overview

Terminology

Characteristics of Waiting-lines

Operating characteristics

M/M/1 model – single channel•Example: video store

M/M/S model – multi-channel

•Example: Multiplex theater

Psychology of waiting

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 ‘The other linealways moves faster.’  

 ‘If you change lines,the one you left willstart to move faster

than the one you’rein.’  

© 1995 Corel Corp.

Thank you for holding.

Hello...are you there?

You’ve Been There Before! 

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Service

FacilityWaiting Line

Waiting Line System

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Situation Arrivals Servers Service Process

Waiting Line Examples

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Queue: Waiting line Arrival: 1 person, machine, part,

etc. that arrives and demands

service

Queue discipline: Rules for

determining the order that arrivals

receive service

Channel: Number of servers

Phase: Number of steps in service

Waiting Line Terminology

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Behavior of the arrivals•  join the queue, and wait 

until served 

• No balking; refuse to jointhe line

• No reneging; leave theline

Service

FacilityWaiting Line

Pattern of arrivalsrandom

scheduled

Arrival Characteristics of aWaiting Line System

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Input

source Service

facility

Waiting

line

Service system

© 1995 Corel Corp.

Line was

too long!

Balking

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Reneging

Input

source Service

facility

Waiting

line

Service system

 © 1995 Corel Corp.

I give up!

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Line Characteristics of aWaiting Line System - continued

Length of the

queue limited unlimited  

Service priority

 FIFO other  

Service

FacilityWaiting Line

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Waiting Line Arrangements 

Service facilities

(a) Single line

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Waiting Line Arrangements 

Service facilities

(a) Single line Service facilities

(b) Multiple lines

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Waiting Line Arrangements 

Service facilities

(a) Single line Service facilities

(b) Multiple lines

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 Number of channels single multiple

Number of phases in service system single

multiple

Service Facility Characteristics of aWaiting Line System - continued

Service

FacilityWaiting Line

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Service Facility Arrangements 

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Service Facility Arrangements 

Servicefacility

(a) Single channel, single phase

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 Arrivals

Served

unitsService

facility

Queue

Service system

DockWaiting ship line

Ships at

sea

Ship unloading system Empty

ships

Single-Channel, Single-Phase System

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Service Facility Arrangements 

(b) Single channel, multiple phase

Servicefacility 1

Servicefacility 2

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Cars

& food

Single-Channel, Multi-Phase System

 Arrivals

Served

unitsService

facility

Queue

Service system

Pick-upWaiting cars

Cars

in area

McDonald’s drive-through

Pay

Service

facility

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Service Facility Arrangements 

(c) Multiple channel, single phase

Servicefacility 1

Servicefacility 2

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 Arrivals

Served

unitsService

facilityQueue

Service system

Service

facility

Example: Bank customers wait in single line for one of 

several tellers.

Multi-Channel, Single Phase System

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Decision Areas 

Arrival rates 

Number of service 

channels  Number of phases 

Service time 

Priority rule 

Line arrangement 

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Average queue length, Lq 

Average number in system, Ls 

Average queue time, W q 

Average time in system, W s 

System utilization,  

Performance Measuresor

Operating Characteristics

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Simple (M/M/1) •Example: Information booth atmall

Multi-channel (M/M/S) 

•Example: Airline ticket counter

Types of Queuing Models

Constant Service (M/D/1) 

Example: Automated car wash

Limited Population Example: Department with only 7 drills 

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Type: Single-channel, single-phase system

Queue: Unlimited; single line

Queue discipline: FIFO (FCFS)

Service rate > arrival rate 

Simple (M/M/1) ModelCharacteristics

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Queuing Models

- ‘lambda’  

•arrival rate of the customers

- ‘mu’  

•servicerate

for a single server• If the service time is 15 minutes

per customer, what is the service

rate??

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Simple (M/M/1) Model Equations

  

 

s LAverage number of 

customers in the

system

    

2

q LAverage numberof customers in the

queue

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Simple (M/M/1) Model Equations

   1

sW 

   

 

qW 

Average time

customers are in

the system

Average time

customers are in

the queue

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Simple (M/M/1) Model Equations

    

Utilization factor –  

percent of time

that the single

server is busy; also

the probability that

a customer will

wait

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Example: Video Store

The manager of a video store isinterested in providing good service.On a Friday or Saturday night, on

average 30 customers per hourarrive at the counter to check out avideo. The customers are served at

an average rate of 35 customers perhour from a single cash register.

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Example: Video Store

Determine the operatingcharacteristics for the video store.

• Average number of customers in line

• Average number of customers in thesystem

• Average wait time in line

• Average time in the system• Server utilization

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Average number of customers in line

   

 

2

q L

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Average number of customers in the system

   s L

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Average wait time in line

   

 

qW 

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Average time in the system

  

1

sW 

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Server utilization

 

   

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Example: Video Store

•What service rate would berequired to have customers

average only 5 minutes in thesystem?

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What service rate would be required to havecustomers average only 5 minutes in the

system?

  

1

sW 

GO TO EXCEL OM

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Type: Multichannel system

Queue discipline: FIFO(FCFS)

Service rates > arrivalrate 

Multichannel (M/M/S) ModelCharacteristics

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Multichannel M/M/S Equations

Probability of zero

customers in the

system:

Average number of 

customers in the

system:

  

 

 

 

 

 

 

  

 

 

  

 

S

S

Sn

PSn

S

n !

1

!

1

1

1

0

0

 

 

  

 

  

 

  

 

02

!1

PSS

 L

S

s

Average number of 

customers waiting for 

service:  

  sq L L

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Multichannel M/M/S Equations

Average time a person or 

unit spends in the queue

Average time a unit

spends in the system:     

 

  

s

S

s

 LP

SSW 

 

  

 

1

!102

  

q

sq

 LW W 

1

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Example: Movie Theater

A multiplex movie theater has 3concession clerks serving customers on afirst come, first served basis. The servicetime per customer is exponentially

distributed with an average of 2 minutesper customer. Concession customersarrive at a rate of 81 customers per hour.10 minutes of previews run in the lobby.

If the average time in the concession areaexceed 10 minutes, customers becomedissatisfied.

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Example: Movie theater

What is the average number of customers in the concession area?

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What is the average number of customers in theconcession area?

GO TO EXCEL OM

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Multiplex Movie Theater

The distribution is reducing thelength of the previews to 8 minutes.How many servers will be required to

so that the average wait is no longerthan 8 minutes?

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Total Cost per Hours

Total cost per Hour= waiting cost +service cost

TC = CwL

s+ KC

s

• Cw – cost of waiting per hour per

customer

• Ls – number of customers in the system

• K – number of servers

• Cs- service cost per hour per server

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Total Cost: Video Store

Considering adding another cashierfor Friday and Saturday nights.

Part-time cashier will cost $6.00 per

hour

Customers waiting time (cost of 

goodwill, etc) is $10.00 per hour.

Is it cost effective to hire the

cashier?

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Total Cost: Video Store M/M/1

TC = CwLs + KC 

Cw = $10/hour

Ls = 6

K = 1

CS = $6.00/hr

TC = 10(6) +1(6)

= $66/hour

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Total Cost: Video Store M/M/2

TC = CwL + KC 

Cw = $10/hour

Ls = 1.05

K = 2

Cs = $6.00/hr

TC = 10(1.05)+ 2(6)

= $22.50/hr

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 = Mean number of arrivals per timeperiod

• e.g., 3 units/hour

 = Mean number of people or items

served per timeperiod

• e.g., 4 units/hour

1/ = 15

minutes/unit

Remember: &  Are Rates

© 1984-1994 T/Maker Co.

If average service time is 15

minutes, then μ is 4

customers/hour 

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The Psychology of Waiting

Maister’s (1985) Propositions of 

customer satisfaction in queues

•Unoccupied time feels longer thanoccupied time

•Pre-process wait feels longer than

in-process waits.•Anxiety makes waits feel longer

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The Psychology of Waiting

•Uncertain waits seem longer than

certain waits

•Unexplained waits seem longer

than explained waits

•Unfair waits seem longer thanequitable waits

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Psychology of Waiting

•More valuable the service, the

longer people will wait.

•Solo waiting feels longer than

group waiting.