BA 409

Operations Research

Mark Parker

MWF, 1:00 - 1:50

SH 212 or SH 146 (Computer Lab)


Other Resources

Introduction

Operations Research is the study of quantitative techniques to help management make informed decisions about the daily operations of their organization. To maintain a competitive edge in a global economy, companies in diverse industries are investing in Operations Research, Management Science, and Decision Analysis. The goal of the course is to provide an introduction to the quantitative methods available for performing analyses and providing input to business decisions. Specifically, my goals are for you to learn to:

  1. recognize specific types of decision problems and modeling approaches to aid in their resolution,
  2. objectively evaluate quantitative models that you will be expected to interpret in the future,
  3. be able to construct and use basic models, and
  4. understand the strengths and weaknesses of these modeling approaches.

We'll attain these goals with a "hands-on" approach via Excel spreadsheet modeling, which is the tool of choice in the modern work environment. No prior knowledge of Excel is required; you will be taught the skills from class and the text, and gain proficiency by doing the homework problems.

Text

textbook Spreadsheet Modeling and Applications,
First Edition
Albright and Winston Thomson Publishing

Schedule

This schedule is tentative and may change as required.

Week Date Topic Text Chapters Suggested Homework Handouts
Week 1 Jan 8 Course Introduction Chapter 1   Syllabus
  Jan 10 Lab 1: Excel Tutorial Sections 2.1 - 2.2   Lab 1 Handout
  Jan 12 Lab 2 : Bus Fuel Costs Section 2.3   Lab 2 Handout
Week 2 Jan 15 No Class - MLK Day      
  Jan 17 Lab 3 : School Busses II Sections 2.4 - 2.5   Lab 3 Handout
Lab 3 Excel Template
  Jan 19 No Class - Sick Day      
Week 3 Jan 22 Modeling and NPV Section 2.6    
  Jan 24 Lab 4: Research and Development Analysis Section 2.6   Lab 4 Handout
Lab 4 Excel Template
  Jan 26 Project 1: Contract Analysis Chapter 2   Project 1 Handout
Sample Reports (PDF)
Week 4 Jan 29

Introduction to Linear Programming

Sections 3.1 - 3.3 Block 2 Homework Textbook errata
  Jan 31 Lab 5: Linear Programming in Excel Sections 3.3 - 3.4 Ch 3 Solutions (Excel) Lab 5 Handout
  Feb 2 Sensitivity Analysis Sections 3.4 - 3.6   Sensitivity Analysis Handout
Week 5 Feb 5 Lab: Work on Project 1      
  Feb 7 Lab 6: More LP in Excel Section 3.7   Lab 6 Handout
  Feb 9 Lab 7: Multiperiod Production Model Section 3.8   Lab 7 Handout
Lab 7 Excel Template
Week 6 Feb 12 Static Workforce Scheduling Models Section 4.3    
  Feb 14 Lab 8: Production Process Models Section 4.5   Lab 8 Handout
Lab 8 Excel Template
  Feb 16 Financial Models Section 4.7   Financial Models Handout
Week 7 Feb 19 Presidents' Day      
  Feb 21 Lab 9: Capital Budgeting Models Sections 6.1 - 6.3   Lab 9 Handout
Lab 9 Excel Template
  Feb 23 Modeling with Binary Variables Section 6.4    
Week 8 Feb 26 Lab 10: Models for Rating Sports Teams Sections 7.1 - 7.2 7.6

 

Lab 10 Handout
Lab 10 Excel Template
  Feb 28 Lab 11: Portfolio Optimization Models Section 7.7   Lab 11 Handout
Lab 11 Excel Template
  Mar 2 Exam 1   Chapters 3, 4, 6, 7  
Week 9 Mar 12 Decision Analysis Introduction Sections 8.1 - 8.2   Decision Analysis Handout
  Mar 14 Lab 12: Multicriteria Decision models     Lab 12 Handout
Lab 12 Excel Template
  Mar 16 Decision Analysis Wrap-up Section 8.3    
Week 10 Mar 19 Dr. Parker sick, no class      
  Mar 21 Lab 13: Simulation in Excel Sections 9.1 - 9.4   Lab 13 Handout
  Mar 23 Lab: Project 2  


Project 2 Handout
Week 11 Mar 26 Lab 14: Exponential and Poisson Distributions
Section 11.3   Lab 14 Handout
Lab 14 Excel Template
  Mar 28 Queuing Models Sections 11.1 - 11.2   Queuing Introduction
  Mar 30 Lab 15: Queuing Models in Excel Section 11.5   Lab 15 Handout
Q.xls
Week 12 Apr 2 Queueing Models Analysis Section 11.5   Queuing Analysis Handout
  Apr 4 Lab 16: M/G/1 and M/D/1 Queues Section 11.5 Sample Exam II
(you might also be asked to use Q.x ls to find some of these values...)
Lab 16 Handout
  Apr 6 Good Friday      
Week 13 Apr 9 Easter Monday      
  Apr 11 Lab 17: Queuing Analysis     Lab 17 Handout
  Apr 13 Exam 2   Chapters 8, 9, and 11 Project 3 Handout
Week 14 Apr 16 Introduction to Time Series Models Sections 12.5 - 12.6   Time Series Handout
  Apr 18 Lab 18: Time Series Models: Exponential Smoothing Section 12.7   Lab 18 Handout
Lab 18 Excel Template
  Apr 20 Regression Models Sections 12.1 - 12.3   Regression Handout
Week 15 Apr 23 Lab 19: Multiple Regression and Seasonal Regression Section 12.4   Lab 19 Handout
Multiple Regression.xls
Regression Seasonal.xls
  Apr 25 Lab: Catch up Day      
  Apr 27 Lab: Catch up Day      
Finals Week April 30 Exam 3 - Monday: 1:00 - 2:45
     

Grading

Assignment Percentage
Labs 15%
Projects 40%
Examinations 45%

Your grade will translate to a letter grade as follows :


mark parker
Last modified: 4 April 2007