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13-1 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Queuing Analysis Chapter 13.

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Presentation on theme: "13-1 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Queuing Analysis Chapter 13."— Presentation transcript:

1 13-1 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Queuing Analysis Chapter 13

2 13-2 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall ■Elements of Waiting Line Analysis ■The Single-Server Waiting Line System ■Undefined and Constant Service Times ■Finite Queue Length ■Finite Calling Population ■The Multiple-Server Waiting Line ■Additional Types of Queuing Systems Chapter Topics

3 13-3 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall A significant amount of time is spent in waiting lines by people, products, etc. Providing quick service is an important aspect of quality customer service. The basis of waiting line analysis is the trade-off between the cost of improving service and the costs associated with making customers wait. Queuing analysis is a probabilistic form of analysis. The results are referred to as operating characteristics. Results are used by managers of queuing operations to make decisions. Overview

4 13-4 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Waiting lines form because people or things arrive at a service faster than they can be served. Most operations have sufficient server capacity to handle customers in the long run. Customers however, do not arrive at a constant rate nor are they served in an equal amount of time. Elements of Waiting Line Analysis (1 of 2)

5 13-5 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Waiting lines are continually increasing and decreasing in length and approach an average rate of customer arrivals and an average service time in the long run. Decisions concerning the management of waiting lines are based on these averages for customer arrivals and service times. Averages are used in formulas to compute operating characteristics of the system which in turn form the basis of decision making. Elements of Waiting Line Analysis (2 of 2)

6 13-6 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Components of a waiting line system include arrivals (customers), servers, (cash register/operator), customers in line form a waiting line. Factors to consider in analysis:  The queue discipline.  The nature of the calling population  The arrival rate  The service rate. The Single-Server Waiting Line System (1 of 2)

7 13-7 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall The Single-Server Waiting Line System (2 of 2) Figure 13.1 The Fast Shop Market waiting line system

8 13-8 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Queue Discipline: The order in which waiting customers are served. Calling Population: The source of customers (infinite or finite). Arrival Rate: The frequency at which customers arrive at a waiting line according to a probability distribution (frequently described by a Poisson distribution). Service Rate: The average number of customers that can be served during a time period (often described by the negative exponential distribution). Single-Server Waiting Line System Component Definitions

9 13-9 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Assumptions of the basic single-server model:  An infinite calling population  A first-come, first-served queue discipline  Poisson arrival rate  Exponential service times Symbols: = the arrival rate (average number of arrivals/time period)  = the service rate (average number served/time period) Customers must be served faster than they arrive ( <  ) or an infinitely large queue will build up. Single-Server Waiting Line System Single-Server Model

10 13-10 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Probability that no customers are in the queuing system: Probability that n customers are in the system: Average number of customers in system: Average number of customer in the waiting line: Single-Server Waiting Line System Basic Single-Server Queuing Formulas (1 of 2)

11 13-11 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Average time customer spends waiting and being served: Average time customer spends waiting in the queue: Probability that server is busy (utilization factor): Probability that server is idle: Single-Server Waiting Line System Basic Single-Server Queuing Formulas (2 of 2)

12 13-12 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall = 24 customers per hour arrive at checkout counter  = 30 customers per hour can be checked out Single-Server Waiting Line System Operating Characteristics: Fast Shop Market (1 of 2)

13 13-13 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Single-Server Waiting Line System Operating Characteristics for Fast Shop Market (2 of 2)

14 13-14 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Single-Server Waiting Line System Steady-State Operating Characteristics Because of the steady-state nature of operating characteristics:  Utilization factor, U, must be less than one: U < 1, or /  < 1 and < .  The ratio of the arrival rate to the service rate must be less than one. In other words, the service rate must be greater than the arrival rate.  The server must be able to serve customers faster than the arrival rate in the long run, or waiting line will grow to infinite size.

15 13-15 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall A manager wishes to test several alternatives for reducing customer waiting time: 1. Addition of another employee to pack up purchases 2. Addition of another checkout counter. Alternative 1: Addition of an employee (raises service rate from  = 30 to  = 40 customers per hour).  Cost $150 per week, avoids loss of $75 per week for each minute of reduced customer waiting time.  System operating characteristics with new parameters: P o =.40 probability of no customers in the system L = 1.5 customers on average in the queuing system Single-Server Waiting Line System Effect of Operating Characteristics (1 of 6)

16 13-16 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall System operating characteristics with new parameters (continued): L q = 0.90 customer on the average in the waiting line W = hour average time in the system per customer W q = hour average time in the waiting line per customer U =.60 probability that server is busy and customer must wait I =.40 probability that server is available Average customer waiting time reduced from 8 to 2.25 minutes worth $ per week. Single-Server Waiting Line System Effect of Operating Characteristics (2 of 6)

17 13-17 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Alternative 2: Addition of a new checkout counter ($6,000 plus $200 per week for additional cashier).  = 24/2 = 12 customers per hour per checkout counter   = 30 customers per hour at each counter  System operating characteristics with new parameters: P o =.60 probability of no customers in the system L = 0.67 customer in the queuing system L q = 0.27 customer in the waiting line W = hour per customer in the system W q = hour per customer in the waiting line U =.40 probability that a customer must wait I =.60 probability that server is idle Single-Server Waiting Line System Effect of Operating Characteristics (3 of 6)

18 13-18 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Savings from the reduced waiting time worth: $500 per week - $200 = $300 net savings per week. After $6,000 is recovered, alternative 2 would provide: $ = $18.75 more savings per week. Single-Server Waiting Line System Effect of Operating Characteristics (4 of 6)

19 13-19 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Table 13.1 Operating characteristics for each alternative system Single-Server Waiting Line System Effect of Operating Characteristics (5 of 6)

20 13-20 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Figure 13.2 Cost trade-off for service levels Single-Server Waiting Line System Effect of Operating Characteristics (6 of 6)

21 13-21 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.1 Single-Server Waiting Line System Solution with Excel and Excel QM (1 of 2) Formula for L q, average number in queue =(1/(D4-D3))*60 =(D3/(D4*(D4-D3)))*60

22 13-22 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.2 Single-Server Waiting Line System Solution with Excel and Excel QM (2 of 2) Click on “Add-Ins” to access the “Excel QM” menu

23 13-23 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.3 Single-Server Waiting Line System Solution with QM for Windows

24 13-24 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Constant, rather than exponentially distributed service times, occur with machinery and automated equipment. Constant service times are a special case of the single-server model with undefined service times. Queuing formulas for the undefined service time model: Single-Server Waiting Line System Undefined and Constant Service Times

25 13-25 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Data: Single fax machine; arrival rate of 20 users per hour, Poisson distributed; undefined service time with mean of 2 minutes, standard deviation of 4 minutes. Operating characteristics: Single-Server Waiting Line System Undefined Service Times Example (1 of 2)

26 13-26 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Operating characteristics (continued): Single-Server Waiting Line System Undefined Service Times Example (2 of 2)

27 13-27 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall In the constant service time model there is no variability in service times;  = 0. Substituting  = 0 into equations: All of the remaining formulas are the same as the single- server formulas. Single-Server Waiting Line System Constant Service Times Formulas

28 13-28 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Car wash servicing one car at a time; constant service time of 4.5 minutes; arrival rate of customers of 10 per hour (Poisson distributed). Determine average length of waiting line and average waiting time. = 10 cars per hour,  = 60/4.5 = 13.3 cars per hour Single-Server Waiting Line System Constant Service Times Example

29 13-29 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.4 Undefined and Constant Service Times Solution with Excel Average number in the queue, L q =D8+(1/D4)*60 =(D6/D3)*60

30 13-30 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.5 Undefined and Constant Service Times Solution with QM for Windows

31 13-31 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall In a finite queue, the length of the queue is limited. Operating characteristics, where M is the maximum number in the system: Finite Queue Length

32 13-32 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Metro Quick Lube single bay service; space for one vehicle in service and three waiting for service; mean time between arrivals of customers is 3 minutes; mean service time is 2 minutes; both inter- arrival times and service times are exponentially distributed; maximum number of vehicles in the system equals 4. Operating characteristics for = 20,  = 30, M = 4: Finite Queue Length Example (1 of 2)

33 13-33 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Average queue lengths and waiting times: Finite Queue Length Example (2 of 2)

34 13-34 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.6 Finite Queue Model Example Solution with Excel Formula for P 0 in cell D7 +((D3/D4)/(1-(D3/D4))) - ((D5+1)*(D3/D4) ^(D5+1))/(1-(D3/D4)^(D5+1))

35 13-35 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.7 Finite Queue Model Example Solution with QM for Windows

36 13-36 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall In a finite calling population there is a limited number of potential customers that can call on the system. Operating characteristics for a system with Poisson arrival and exponential service times: Finite Calling Population

37 13-37 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Wheelco Manufacturing Company; 20 machines; each machine operates an average of 200 hours before breaking down; average time to repair is 3.6 hours; breakdown rate is Poisson distributed, service time is exponentially distributed. Is repair staff sufficient? = 1/200 hour =.005 per hour  = 1/3.6 hour =.2778 per hour N = 20 machines Finite Calling Population Example (1 of 2)

38 13-38 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall …The system seems woefully inadequate. Finite Calling Population Example (2 of 2)

39 13-39 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.8 Finite Calling Population Example Solution with Excel and Excel QM (1 of 2) P 0 = 1/G26 Summation component for n=1 in cell G6 Array with summation components for P 0 formula

40 13-40 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit 13.9 Finite Calling Population Example Solution with Excel and Excel QM (2 of 2) Click on “Add-Ins” to access the macro for the finite population model Enter problem data in cells B7:B9

41 13-41 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit Finite Calling Population Example Solution with QM for Windows

42 13-42 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Multiple-Server Waiting Line (1 of 3) Figure 13.3 A multiple-server waiting line

43 13-43 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall In multiple-server models, two or more independent servers in parallel serve a single waiting line. Biggs Department Store service department; first-come, first-served basis. Multiple-Server Waiting Line (2 of 3)

44 13-44 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Customer Service System at Biggs Department Store Multiple-Server Waiting Line (3 of 3)

45 13-45 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Multiple-Server Waiting Line Queuing Formulas (1 of 3) Assumptions:  First-come first-served queue discipline  Poisson arrivals, exponential service times  Infinite calling population. Parameter definitions:  = arrival rate (average number of arrivals per time period)   = the service rate (average number served per time period) per server (channel)  c = number of servers  c  = mean effective service rate for the system (must exceed arrival rate)

46 13-46 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Multiple-Server Waiting Line Queuing Formulas (2 of 3)

47 13-47 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Multiple-Server Waiting Line Queuing Formulas (3 of 3)

48 13-48 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Multiple-Server Waiting Line Biggs Department Store Example (1 of 2) = 10,  = 4, c = 3

49 13-49 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Multiple-Server Waiting Line Biggs Department Store Example (2 of 2)

50 13-50 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit Multiple-Server Waiting Line Solution with Excel Formula for P 0 =((((D3)*(D4)*((D3/D4)^D5)*(D7))/(FACT (D5-1)*(((D5*D4)-D3)^2))))+(D3/D4) =(1/FACT(D5))*((D3/D4)^D5)*((D5*D4*D7)/((D5)*(D4)-(D3)))

51 13-51 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit Multiple-Server Waiting Line Solution with Excel QM

52 13-52 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Exhibit Multiple-Server Waiting Line Solution with QM for Windows

53 13-53 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Figure 13.4 Single queues with single & multiple servers in sequence Additional Types of Queuing Systems (1 of 2)

54 13-54 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Other items contributing to queuing systems:  Systems in which customers balk from entering system, or leave the line (renege).  Servers who provide service in other than a first-come, first-served manner  Service times that are not exponentially distributed or are undefined or constant  Arrival rates that are not Poisson distributed  Jockeying (i.e., moving between queues) Additional Types of Queuing Systems (2 of 2)

55 13-55 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Problem Statement: Citizens Northern Savings Bank loan officer customer interviews. Customer arrival rate of four per hour, Poisson distributed; officer interview service time of 12 minutes per customer. 1. Determine operating characteristics for this system. 2. Add an additional officer creating a multiple-server queuing system with two channels. Determine operating characteristics for this system. Example Problem Solution (1 of 7)

56 13-56 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Solution: Step 1: Determine Operating Characteristics for the Single- Server System = 4 customers per hour arrive,  = 5 customers per hour are served P o = (1 - /  ) = ( 1 – 4 / 5) =.20 probability of no customers in the system L = / (  - ) = 4 / (5 - 4) = 4 customers on average in the queuing system L q = 2 /  (  - ) = 4 2 / 5(5 - 4) = 3.2 customers on average in the waiting line Example Problem Solution (2 of 7)

57 13-57 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Step 1 (continued): W = 1 / (  - ) = 1 / (5 - 4) = 1 hour on average in the system W q = /  (u - ) = 4 / 5(5 - 4) = 0.80 hour (48 minutes) average time in the waiting line P w = /  = 4 / 5 =.80 probability the new accounts officer is busy and a customer must wait Example Problem Solution (3 of 7)

58 13-58 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Step 2: Determine the Operating Characteristics for the Multiple-Server System. = 4 customers per hour arrive;  = 5 customers per hour served; c = 2 servers Example Problem Solution (4 of 7)

59 13-59 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Step 2: Determine the Operating Characteristics for the Multiple-Server System. = 4 customers per hour arrive;  = 5 customers per hour served; c = 2 servers Example Problem Solution (5 of 7)

60 13-60 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Step 2 (continued): Example Problem Solution (6 of 7)

61 13-61 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Step 2 (continued): Example Problem Solution (7 of 7)

62 13-62 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.


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