Class: DSES Simulation Modeling And Analysis

Slides:

Advertisements

Similar presentations

Waiting Line Management

Advertisements

Class: DSES Simulation Modeling And Analysis

Q vs Await Node Q is a simplified Await node Q activity is the resource ie server, inspection Await Node can specify resource that is needed by activity.

Review of Probability Distributions

Waiting Lines Example Students arrive at the Administrative Services Office at an average of one every 15 minutes, and their request take on average 10.

Queuing Theory Worthmore Department Store

QUEUING MODELS Based on slides for Hilier, Hiller, and Lieberman, Introduction to Management Science, Irwin McGraw-Hill.

Simulation Study of a Call Center Gaurav Chhabra & Sachin Jayaswal.

1 Ardavan Asef-Vaziri Jan-2011Operations Management: Waiting Lines 2 The arrival rate to a GAP store is 6 customers per hour and has Poisson distribution.

Waiting Lines Example-1

Simulation of multiple server queuing systems

Chapter 22 Simulation with Process Model to accompany Operations Research: Applications and Algorithms 4th edition by Wayne L. Winston Copyright (c) 2004.

Probability Distributions

1 Ardavan Asef-Vaziri Jan-2011Operations Management: Waiting Lines 2 Example: The arrival rate to a GAP store is 6 customers per hour and has Poisson distribution.

Waiting Line Management

MGTSC 352 Lecture 23: Congestion Management Introduction: Asgard Bank example Simulating a queue Types of congested systems, queueing template Ride’n’Collide.

Simulating Single server queuing models. Consider the following sequence of activities that each customer undergoes: 1.Customer arrives 2.Customer waits.

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

Waiting line Models.

Lecture 4 Mathematical and Statistical Models in Simulation.

EASTERN MEDITERRANEAN UNIVERSITY FACULTY OF ENGINEERNG Department of Industrial Engineering IENG461 System Modeling and Simulation Course Fall

A Somewhat Odd Service Process (Chapters 1-6)

Chapter 8 – Further Applications of Integration 8.5 Probability 1Erickson.

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

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

Notes Over 12.7 Using a Normal Distribution Area Under a Curve.

Section 9.3 Distribution of Sample Means AP Statistics February 5, 2010 Berkley High School.

1 Systems Analysis Methods Dr. Jerrell T. Stracener, SAE Fellow SMU EMIS 5300/7300 NTU SY-521-N NTU SY-521-N SMU EMIS 5300/7300 Queuing Modeling and Analysis.

SIMULATION EXAMPLES QUEUEING SYSTEMS.

Simulation vs. Queuing Theory

Think about a normal (school) day. How do you spend your time?

Post-after.  What is the word that describes what you do when have the change the date of the picnic until after the planned date because it will be.

1 1 Slide © 2011 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole.

1 Ardavan Asef-Vaziri Sep-09Operations Management: Waiting Lines3 Example: The arrival rate to a GAP store is 6 customers per hour and has Poisson distribution.

Unit 6 Section 6-4 – Day 1.

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.

CS 450 – Modeling and Simulation Dr. X. Topics System Analysis Arrival process The Queue The Server The simulation.

1 1 Slide Continuous Probability Distributions n The Uniform Distribution  a b   n The Normal Distribution n The Exponential Distribution.

Uniform Problem A subway train on the Red Line arrives every 8 minutes during rush hour. We are interested in the length of time a commuter must wait.

Simulation of single server queuing systems

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,

Managerial Decision Making Chapter 13 Queuing Models.

Section 7.6 Solving Multi-Step Inequalities Solve and Graph.

12.7 Normal Distributions Idleness is not doing nothing. Idleness is being free to do anything.

Queuing Models Part 1: Basics

DISPLAYING AND ANALYZING DATA

18 Management of Waiting Lines

Post Office Basic Content (Low Graders) Vocabulary

“QUEUING THEORY”.

Getting Started .Cont The Basic Process Panel

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

SIMULATION EXAMPLES QUEUEING SYSTEMS.

Logarithmic Functions and Their Graphs

LESSON 12: EXPONENTIAL DISTRIBUTION

SIMULATION EXAMPLES QUEUEING SYSTEMS.

Determine whether each situation calls for a survey, an experiment, or an observational study. Explain your reasoning. You want to find opinions on the.

Process Improvement Labs

Mitchell Jareo MAT4340 – Operations Research Dr. Bauldry

LESSON 8: RANDOM VARIABLES EXPECTED VALUE AND VARIANCE

Topic IV. Single Channel Systems (Limited queue length system)

Section 9.3 Distribution of Sample Means

QUEUING THEORY Made by Abdulsalam shek salim

Section 9.5 The Bell Curve.

6.3 Logarithmic Functions

Homework: pg. 500 #41, 42, 47, )a. Mean is 31 seconds.

Continuous distribution curve.

UNITS OF TIME QUESTIONS.

SIMULATION EXAMPLES QUEUEING SYSTEMS.

Presentation transcript:

Class: DSES - 6620 Simulation Modeling And Analysis Homework: L4.5 Exercises Name: Kevin Lewelling Date: February 13, 2002 1. Customers arrive at the Lake Gardens post ofice for buying stamps, mailing letters and packages, and so forth. The interarrival time is exponentially distributed with a mean of 2 minutes. The time to process each customer is normally distributed with a mean of 10 minutes and a standard deviation of 2 minutes. How many postal clerks are needed at the counter so that there are no more than 15 customers waiting in the post office at any time? Make a time series plot of the number of customers in the post office in a typical eight-hour day. Change the number of postal clerks until you find the optimum number. Five postal clerks are required so that there are no more than 15 customers waiting in the post office at a time. 2. The Lake Gardens postmaster in Exercise 1 wants to serve his customers well. He wold like to see that no postal customer has to wait more than 15 minutes a the post office. Make a graph for the content histogram for the cycle time in the system. 3. For the example in Lab 3, Section L3.3, find out the percentage of time the splitter and the lathe are idle. Make a state graph and a pie graph for these locations. Splitter - 5.33% Lathe - 16.76% 4. For the example in Lab3, Section L3.2, plot the time painted logs spend in the manufacturing facility. Also, plot the number of painted logs produced.