Ch. 6 Queuing Flashcards

(42 cards)

1
Q

Purpose of Queuing Models

A

mgt has some control
-More employees - shorter lines, more exp
-Less employees- long lines, unhappy cust.

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2
Q

Trade-off in Queuing Models (service level increase)

A

-Cost of providing the service increases.
-cost of cust. dissatisfaction decreases

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3
Q

As service lvl decreases

A

cost of providing serv. decreases
cost of cust. dissatisfaction increases

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4
Q

Main goal for queuing costs and service levels

A

The goal is to find the optimal service level that
achieves a balance between the cost of providing service and the customer satisfaction level.

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5
Q

Queuing theory helps us predict what happens if?

A

-we increase / decrease the number of
servers?
* customer arrival rates increase / decrease?
* we reduce the average service time?

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6
Q

Queuing theory

A

help us to understand, design, operate, and improve these systems and help Managers make decisions.

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7
Q

Queuing Behaviour

A

Line up actions (things people do/don’t do)
-Wait, not join, jockey (change line), join then leave line, meld (2 lines in one)

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8
Q

Lines are just for people

A

No can be for printers, subassemblies in mfg, electronic messages

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9
Q

History of Queuing Theory

A

It is the body of knowledge dealing with waiting lines.
Early 1900s by Danish telephone engineer A.K Erlang (studying the congestion and waiting times occurring on phone lines)

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10
Q

Queue Mgt Suggestions

A

-Perception of Wait
-Acceptable waiting time
-Distractions
-Avoid lineups where possible
-Awareness of waiting time- provide
-Modify arrival behavior
-Idle resources out of sight
-Segment customers
-Think long term
-A friendly server (alter impression of wait)

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11
Q

Perception of Wait

A

People tend to overestimate their wait time

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12
Q

Acceptable Waiting Time

A

→ Type of service (ex. Bank vs. Emergency room)
→ Type of waiting (ex. in person vs. phone)
→ Type of customer (ex. parent with small children)

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13
Q

Distractions

A

Provide something to do / watch / read, etc

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14
Q

Avoid Line-ups where possible

A

→ Reservations, appointments, automation, etc.

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15
Q

Awareness of Waiting Time – Provide?

A

→ Only if…
Customer is unable to estimate the
wait time themselves such as phone
support or a plane waiting to take off

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16
Q

Modify Arrival Behaviour

A

→ Incentives for arriving outside of peak hours

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17
Q

Idle Resources out of Sight

A

→ Frustrating when staff seem available, but don’t help

18
Q

Segment Customers

A

→ Identify who is willing to wait versus who would pay
more for faster service (provide that option)
→ Volume of purchases (express lane)

19
Q

Think Long-Term

A

→ Opinions of long line-ups / delays kept for a long time
→ Word-of-mouth can multiply this impact

20
Q

What card was given to Janice and why

A

This card is used to help us provide
you with the most accurate wait
time. Please hand the card to a cast
member at the end of the ride.”
(Orlando jan 2011) a card on a lanyard

21
Q

How did they manage queues at disney with virtual queues

A

-Use park pass to line up for a pop attraction with the FastPass system. (know when to ret)
-Now updated electronically

22
Q

Managing Queue Expectations at
Breakfast in Disney

A

-Inform cust. about queues
-message was in the elevator - to avoid dissatisfaction

23
Q

virtual Queues

A

In San Francisco, you can shop
at Macy’s while waiting for a table
at the Cheesecake Factory.
 Restaurants in Calgary also use
this.

24
Q

Configurations

A

-many use FCFS 1st come 1st serve
- arrivals are from a calling pop.

25
Characteristics of calling pop
-Size -Arrival pattern -Attitude
26
Size
-Finite = pre set max -Infinite = most common, # in line up small compare to # that could come
27
Arrival Pattern
-Random- poisson, others (indep. arrivals) -Pre det. (appointment/reservation)
28
Attitude
-Patient -(wait for service) -Impatient-balking(unwilling- not joining the line), reneging(abandon) (leave w/o service)
29
Configuration is defined by
A queuing system configuration is defined by the # of channels (servers) and # of phases -1 server, 1 phase / 1 server, 2 phase - 2 server, 1 phase (not the same as lining up behind each server i.e grocery store)/ 2 server , 2 phase
30
It takes the server to process the cust. who leaves the system when finished
No, It takes the service time to process the customer who leaves the system when finished
31
Charact. of Queuing Systems
-Arrival rates - avg arrival rate lambda -Service time - avg service rate mu
32
Arrival rate & Inter arrival time
-Avg # of cust. arriving in a time period -Avg time betw. 2 cust. arrivals = 1/^
33
Interarrival Time Variation
The customer arrival process is modeled with the Poisson Distribution.  The time between arrivals is independent.(arrival of cust. 1 doesn't influence the timing of cust. 2)
34
Relat. Betw. the Poisson Arrival Rate & Inter-Arrival Time Distribution
Arrival rate - poisson dist. actual val=integer Inter arrival - expon. dist. actual val= not necessarily integer
35
Service rate & service time
-the no.of cust. 1 server manage in a time -avg service time- avg time req. to provide serv1/u
36
Service time includes queue time
No, the amount of time to perform a service
37
Inter arrival & service time variation
-Variation in the inter-arrival times causes a queue to form.  Queuing theory can tell us the average length of the queue
38
Kendall notation
To describe and calculate a queuing system and its performance using queuing theory, we need to know: → the prob. distr. of the inter-arrival times → the prob. distr. of the service times → the number of servers s
39
the notation
M/ / most common is M/M/1
40
Queuing models
Queuing Theory is the Study of Lines (Queues). Some elements of line-ups in queuing theory: → Not enough servers * s = # of servers → Servers are too slow * (mu), average service rate → Too many customers * (lambda), average arrival rate → Too many customers arrived before you, and you can’t cut in line * First-in First-Out
41
queuing performance measures
that could be used to evaluate the efficiency and effectiveness of these systems? → Avg. number of customers waiting in the queue → Avg. number of customers in the system → Average waiting time in the queue → Average time in system
42
Steady State
 At the beginning of each day, most queuing systems start in an “empty and idle” condition → business activity gradually builds up to reach the normal, or steady-state, level of operation.  A queuing system can have different levels of steady-state operations at different times through the day. → A restaurant can be busy at lunch and dinner. → Rush hour traffic happens in the morning and evening.