Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Managing Waiting Lines.

Slides:

Advertisements

Similar presentations

Managing Waiting Lines

Advertisements

LESSONs NINE and TEN QUEUING MODELS.

McGraw-Hill/Irwin © The McGraw-Hill Companies, Inc., Where is There Waiting? Service Facility –Fast-food restaurants –Post office –Grocery store.

© The McGraw-Hill Companies, Inc., 1998 Irwin/McGraw-Hill 2 Chapter 7 TN Waiting Line Management u Waiting line characteristics u Some waiting line management.

QMD: Waiting-line analysis

Chapter 12 Managing Waiting Lines

ISM 270 Service Engineering and Management Lecture 5: Facility Location, Project Management.

Model Antrian By : Render, ect. Outline  Characteristics of a Waiting-Line System.  Arrival characteristics.  Waiting-Line characteristics.  Service.

© The McGraw-Hill Companies, Inc., Technical Note 6 Waiting Line Management.

Managing Waiting Lines

Managing Waiting Lines chapter - 13

To accompany Quantitative Analysis for Management, 8e by Render/Stair/Hanna 14-1 © 2003 by Prentice Hall, Inc. Upper Saddle River, NJ Chapter 14.

Management of Waiting Lines

1 Service A Queuing System Arrival Rate (  Average Number in Queue ( L q ) Avg Time in System ( W ) Avg Number in System ( L ) Average Wait in Queue.

Queuing. Elements of Waiting Lines  Population –Source of customers Infinite or finite.

Queueing Theory Professor Stephen Lawrence Leeds School of Business University of Colorado Boulder, CO

ISM 270 Service Engineering and Management Lecture 7: Forecasting and Managing Service Capacity.

Operations Management Waiting-Line Models Module D

Managing Waiting Lines McGraw-Hill/Irwin Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.

Model Antrian By : Render, ect. M/M/1 Example 2 Five copy machines break down at UM St. Louis per eight hour day on average. The average service time.

Group members  Hamid Ullah Mian  Mirajuddin  Safi Ullah.

Capacity and Demand Management

___________________________________________________________________________ Operations Research  Jan Fábry Waiting Line Models.

A Somewhat Odd Service Process (Chapters 1-6)

Introduction to Management Science

McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc., All Rights Reserved. Waiting Line Models.

Service Systems & Queuing Chapter 12S OPS 370. Nature of Services –A

Queueing Theory Models Training Presentation By: Seth Randall.

Waiting Line Models ___________________________________________________________________________ Quantitative Methods of Management  Jan Fábry.

ISM 270 Service Engineering and Management Lecture 7: Forecasting and Managing Service Capacity.

McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Service Processes CHAPTER 5.

Introduction to Queueing Theory

Management of Waiting Lines McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

Supplement D Waiting Line Models Operations Management by R. Dan Reid & Nada R. Sanders 3rd Edition © Wiley 2005 PowerPoint Presentation by Roger B. Grinde,

Chapter 12 Managing Waiting Lines McGraw-Hill/Irwin Service Management: Operations, Strategy, and Information Technology, 6e Copyright © 2008 by The McGraw-Hill.

McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved. 1.

OPSM 405 Service Management Class 18: Managing capacity Koç University Zeynep Aksin

McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 18 Management of Management of Waiting Lines.

1-1 McGraw-Hill/Irwin ©2009 The McGraw-Hill Companies, All Rights Reserved 1 Chapter 8A Waiting Line Management.

1 Queuing Models Dr. Mahmoud Alrefaei 2 Introduction Each one of us has spent a great deal of time waiting in lines. One example in the Cafeteria. Other.

1 Elements of Queuing Theory The queuing model –Core components; –Notation; –Parameters and performance measures –Characteristics; Markov Process –Discrete-time.

Waiting Lines and Queuing Models. Queuing Theory  The study of the behavior of waiting lines Importance to business There is a tradeoff between faster.

Spreadsheet Models for Managers: Session 12 12/1 Copyright © Richard Brenner Spreadsheet Models for Managers Session 12 Service Systems Single-Server.

Queuing Theory. Introduction Queuing is the study of waiting lines, or queues. The objective of queuing analysis is to design systems that enable organizations.

Chapter 16 Capacity Planning and Queuing Models

1 Queuing Systems (2). Queueing Models (Henry C. Co)2 Queuing Analysis Cost of service capacity Cost of customers waiting Cost Service capacity Total.

Supplement D Waiting Line Models

OPSM 301: Operations Management Session 19: Flow variability Koç University Zeynep Aksin

Reid & Sanders, Operations Management © Wiley 2002 Waiting Line Models A SUPPLEMENT.

Components of the Queuing System

Stevenson and Ozgur First Edition Introduction to Management Science with Spreadsheets McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies,

Structure of a Waiting Line System Queuing theory is the study of waiting lines Four characteristics of a queuing system: –The manner in which customers.

1 1 Slide Chapter 12 Waiting Line Models n The Structure of a Waiting Line System n Queuing Systems n Queuing System Input Characteristics n Queuing System.

Waiting Line Theroy BY, PRAYASH NEUPANE, KARAN CHAND & SANTOSH SHERESTHA.

Queueing Theory. The study of queues – why they form, how they can be evaluated, and how they can be optimized. Building blocks – arrival process and.

OPERATIONS MANAGEMENT INTEGRATING MANUFACTURING AND SERVICES FIFTH EDITION Mark M. Davis Janelle Heineke Copyright ©2005, The McGraw-Hill Companies, Inc.

Simple Queueing Theory: Page 5.1 CPE Systems Modelling & Simulation Techniques Topic 5: Simple Queueing Theory  Queueing Models  Kendall notation.

QUEUING THOERY. To describe a queuing system, an input process and an output process must be specified. Examples of input and output processes are: SituationInput.

Queueing Theory/Waiting Line: Models and Analysis Navneet Vidyarthi

Abu Bashar Queuing Theory. What is queuing ?? Queues or waiting lines arise when the demand for a service facility exceeds the capacity of that facility,

Chapter 2 Simulation Examples. Simulation steps using Simulation Table 1.Determine the characteristics of each of the inputs to the simulation (probability.

McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 18 Management of Waiting Lines.

© 2006 Prentice Hall, Inc.D – 1 Operations Management Module D – Waiting-Line Models © 2006 Prentice Hall, Inc. PowerPoint presentation to accompany Heizer/Render.

McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.

“QUEUING THEORY”.

Managing Waiting Lines

McGraw-Hill/Irwin ©2009 The McGraw-Hill Companies, All Rights Reserved

Management of Waiting Lines

Supplement D Waiting Line Models

Waiting Line Models Waiting takes place in virtually every productive process or service. Since the time spent by people and things waiting in line is.

Presentation transcript:

Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Managing Waiting Lines

Where the Time Goes In a life time, the average American will spend-- SIX MONTHS Waiting at stop lights EIGHT MONTHS Opening junk mail ONE YEAR Looking for misplaced objects TWO YEARS Unsuccessfully returning phone calls FOUR YEARS Doing housework FIVE YEARS Waiting in line SIX YEARS Eating

Waiting Realities  Inevitability of Waiting: Waiting results from variations in arrival rates and service rates  Economics of Waiting: High utilization purchased at the price of customer waiting. Make waiting productive (salad bar) or profitable (drinking bar).

Laws of Service  Maister’s First Law: Customers compare expectations with perceptions.  Maister’s Second Law: Is hard to play catch-up ball.  Skinner’s Law: The other line always moves faster.  Jenkin’s Corollary: However, when you switch to another other line, the line you left moves faster.

Psychology of Waiting  That Old Empty Feeling: Unoccupied time goes slowly  A Foot in the Door: Pre-service waits seem longer that in-service waits  The Light at the End of the Tunnel: Reduce anxiety with attention  Excuse Me, But I Was First: Social justice with FCFS queue discipline  They Also Serve, Who Sit and Wait: Avoids idle service capacity

Approaches to Controlling Customer Waiting  Animate: Disneyland distractions, elevator mirror, recorded music  Discriminate: Avis frequent renter treatment (out of sight)  Automate: Use computer scripts to address 75% of questions  Obfuscate: Disneyland staged waits (e.g. House of Horrors)

Essential Features of Queuing Systems Departure Queue discipline Arrival process Queue configuration Service process Renege Balk Calling population No future need for service

Arrival Process StaticDynamic AppointmentsPrice Accept/Reject BalkingReneging Random arrivals with constant rate Random arrival rate varying with time Facility- controlled Customer- exercised control Arrival process

Distribution of Patient Interarrival Times

Temporal Variation in Arrival Rates

Poisson and Exponential Equivalence Poisson distribution for number of arrivals per hour (top view) One-hour interval Arrival Arrivals Arrivals Arrival 62 min. 40 min. 123 min. Exponential distribution of time between arrivals in minutes (bottom view)

Queue Configurations Multiple Queue Single queue Take a Number Enter

Queue Discipline Queue discipline Static (FCFS rule) Dynamic selection based on status of queue Selection based on individual customer attributes Number of customers waiting Round robinPriorityPreemptive Processing time of customers (SPT rule)

Outpatient Service Process Distributions

Service Facility Arrangements Service facility Server arrangement Parking lot Self-serve Cafeteria Servers in series Toll booths Servers in parallel Supermarket Self-serve, first stage; parallel servers, second stage Hospital Many service centers in parallel and series, not all used by each patient