Co-Listed Course: EM 540 Operations Research for Managers

Course Director: Dr. James R. Holt
429 SE 13 th Court
Gresham, OR 97080
(jholt@wsu.edu)

 Faculty Support: Patti Elshafei (pelshafei@wsu.edu)
Office at Pullman: (509) 335-0125

Home Office: (503) 669-6676

After 7:00 AM and before 9:30 PM

Office Fax: (509) 335-4725

James R. Holt, Ph.D., PE. is an Associate Professor of Engineering Management at Washington State University - Vancouver. He teaches Organizational Behavior, Operations Research, Statistics, Engineering Economics, Simulation, Information Systems, Constraints Management and other special topics. He was a Principal Consultant with Management Advisory Group, Inc. and a Certified Associate of the Avraham Y. Goldratt Institute. Prior to his consulting work, he was Department Head, Engineering and Environmental Management at the Air Force Institute of Technology, Wright-Patterson AFB, Ohio. Dr. Holt retired from the Air Force with 20 years experience in engineering, computer and technology management. He has published many articles on supply chain management, project management, maintenance and artificial intelligence. He holds a BS in Mechanical Engineering from Utah State University, an MS in Facilities Engineering from the Air Force Institute of Technology and a Ph.D. specializing in Industrial Engineering / Business Administration from Texas A&M University. Dr Holt has taught at the graduate level 18 years and has advised 88 engineering student theses and dissertations on a wide variety of topics. He has lived in the Portland area for 13 years and is active with professional and community organizations.

 Required Text: Quantitative Analysis for Management and Student CD-ROM, 10th Edition

Barry Render, Ralph M. Stair, Jr., and Michael E. Hanna.

Prentice-Hall, 2009

ISBN -10: 0136036252

Includes: Weiss QM for Windows, Excel QM, Setup for Chapter Assignments and other Computer Software

 Other Suggested Texts for Insightful Operations Research Topics:

1. The Goal, 2nd Revised Edition [Physical Process Management]

Eliyahu M. Goldratt

North River Press, Inc. 1992

2. The Haystack Syndrome:

Sifting Information out of the Data Ocean [Data Manipulation/Management]

Eliyahu M. Goldratt

North River Press, Inc. 1990

3. The Machine that Changed the World [Optimizing Every Process]

James P. Womack, Daniel T. Jones and Daniel Roos

Macmillan 1990

4. It's Not Luck [Logically Changing the System-Thinking Process]

Eliyahu M. Goldratt

North River Press, Inc. 1994

5. Critical Chain [Breakthrough Project Management]

Eliyahu M. Goldratt

North River Press, Inc. 1994

 Background: Operation Research is both a thought process and a mathematical representation of decision making. Mathematical models have been part of the decision making process since people learned to represent physical entities and relationships with an abstract system of numbers. Engineers traditionally represent physical reality in deterministic models seeking a single solution. Operations Research extends math modeling to managerial decisions, organizational problems and business systems which have many solutions. Operations Research uses these models to better understanding the options available to the manager. Traditional operations research techniques include a collection of mathematical models to help rationalize and quantify the role of the decision maker. These tools guide the manager towards the 'best solution' among the many possible satisfying solutions.

 Course Description: This course introduces the student to a number of models which have proven effective in solving certain classes of managerial problems. The student will see the rational behind the technique and understand how to apply the tools. The student will apply these tools to various representative sample problems in class, in homework and in a course project. The tools to be surveyed include linear programming, network models, scheduling models, integer and goal programming, dynamic programming, stochastic processes, decision theory, queuing theory, digital simulation, inventory systems, decision support systems, artificial intelligence and constraint theory. Students learn the strengths and weaknesses, the applications and limitations of the models presented. More importantly, good students begin to master the systematic and logical approach to problem solving which extends beyond the collection of tools presented into everyday application.

 Prerequisites: Students should have a solid understanding of algebra, basic calculus, probability concepts and statistical methods. An awareness of matrix algebra is desirable.

Classroom Approach: This course uses a hands on approach to learning and incorporates an upward spiraling technique. Students examine the formal approach to solving a problem and then formulate a simple problem using the mathematical model. Then, the student solves that problem. Then, a slightly harder problem is posed and the student formulates and solves that problem and so on. In this way, the student learns why the basic assumptions of the tool are important and what can happen when they are violated. Simple to complex problems will be discussed in class. The focus of the course is on concepts and applications and not on mathematical theory. As much as possible, examples from the student's environment will be used as case studies to apply these tools to current reality.

Homework Approach: Homework is for you own use and benefit. Representative homework is assigned and should be worked an d kept by the student in a notebook. Students are also asked to demonstrate their understanding of the assigned homework by generating a new problem and solving it using that week's specific technique.

Student Notebook - Representative homework is assigned to develop the student as the class progresses. Homework will not be turned-in in a traditional sense. Students are encouraged to work the assigned homework in their own way keeping notes on what to watch-out for or what special thing was learned. Maintain this work in a notebook which will be of value to you. (Note: Students should make every effort to say current with the homework. This class moves quickly and it is easy to fall behind.) The notebook will be turned in with the mid-term exam and with the final exam. The only requirement will be for the notebook to be legible enough to see which problem is which. An excellent notebook would show evidence of having worked most of the problems and contain personal notes about the techniques used, their application and difficulties. Attached, annotated computer sheets are acceptable. Group work on homework and classroom projects is allowed and encouraged. When you work as a group, give credit to the other group members (note: just copying someone else's work is not working together and destroys your own learning experience which will show on the exam).

Student Generated Problems - Each class period will discuss new techniques or amplify learned techniques. Each week, the student is assigned to create a typical homework problem that uses the new technique or amplification and hand-in that homework at the next class period. The student generated problem helps will encourage the student to stay current and to understand the elements involved in the particular techniques. Students will formulate the problem and include the solution with the problem. Student generated problems will not be returned, only acknowledged (or help provided if the student is too far off the mark).  A maximum of ten student generated problems will be counted. So, if you choose not to do a problem each week, you can still get full points if you submit work for ten or more weeks.

Testing Approach: A take home mid-term and final exam will be given. These exams will test the students ability to formulate and solve problems based on the tools presented in class. In general, the final exam in not comprehensive, however, it will test the students ability to decide which tool to apply to which problem and why. The exams are INDIVIDUAL EFFORT and represent private work. Do not work with other students or outside parties in completing the exam. Computers software, class notes and the Student Notebook may be used to solve problems on the exam. 

Computer Use: Most algorithms used in operations research tools have been computerized. Use of these automated tools is encouraged. When using these tools, the student takes responsibility for selecting the right automated tool, correctly formulating the problem and in accurately interpreting the output. Computers are allowed for homework and for exams. Portable computers may be used in class once students have mastered the basic techniques.

Project Requirements: Students will complete two projects during the course. The projects are to help the student learn one technique in detail and to learn where other sources of valuable information can be found. Both projects may be completed at anytime during the course. Both projects must be turned in before receiving the final exam.

Application Project: Each student will select one of the major topics in the course and apply the technique to an appropriate problem in his or her own work environment (or personal situation). Think of this as a large Student Generated Problem. The student will define the problem in ‘story problem form’ (similar to Case Studies shown at the end of the chapters in the text) including relevant data. And, the student then solves the problem in correct form.

Research Project: Each student will find one article supporting or attacking one of the techniques taught in the course and write a short report (around 2 pages double spaced) about the article. Such sources could be Management Science, Industrial Management, IIE Magazine, SEMS Journal, IEEE Transactions or other professional sources.

Evaluation: The various evaluation measures will be weighted as follows:

Mid-term exam	25%
Final exam	30%
Student Generated Problems	15%
Homework Notebook	10%
Application Project	10%
Research Project	10%

In graduate courses, participation is critical to the success of the class. Each student is expected to contribute thoughtful comment and question. Although participation is not a direct contributing factor in the course evaluation equation, it will be used against students who are not involved in the group learning process. The maximum adjustment for non-participation will be -5%.

Treatment of Sensitive Material: The students of this class come from many companies. While you will be amazed how often different companies suffer from the same types of problems, some companies are reluctant to make public their concerns and breakthrough solutions. In addition, some students may be dealing with sensitive or propietary materials within their company. We have academic freedom within the classroom, we do not mean to embarass any student. And academic freedom does not mean we have a secure environment even with password protection. If you have sensitive material that should not be shared publicly, please do not discuss it in class or other class communications channels.

If you indicate you have sensitive material in your homework submissions, I will not share that information with any other people. Some firms desire a non-disclosure agreement in this cases. Such agreements are easily possible for sensitive work. However, most of the time, a simple "sensitve material" statement is all you need.

Incomplete Policy:Occationally, events beyond the students control prevent the student from completing all the required work for the Major Application Project. This project is represents the meat of the course and demonstrates the student has adequately learned the course material. If a student has completed at least through the FRT (representing more than 50% of the course material) but has not completed the full project by the time grades are do, the student will be awarded an 'I' - Incomplete grade. Students recieving an Incomplete should try to complete their project within the following semester.

Disability: Reasonable accommodations are available for students with a disability. DDP and the Disability Resource Center (DRC) work together to provide reasonable accommodations for students who have documented disabilities and who are registered both with DDP and the DRC. DDP's liaison to the DRC will assist you in getting started. To begin this process, contact DDP (800-222-4978 or distance@wsu.edu). We strongly recommend that you notify us as soon as possible. All accommodations must be approved through Disability Resource Center (DRC).

Plagerism: Cases of academic dishonesty shall be processed in accordance with the Academic Integrity Policy, as printed in the Student Handbook and the Faculty Manual and as available from the Office of Student Affairs: http://www.wsulibs.wsu.edu/plagiarism/main.html.

Date	Week	Render, Stair, Hanna	Subject	In-Class Slide Presentation	Homework
24 Aug	1	Chap. 1,2	Introduction to Quantitative Analysis Probability Concepts and Applications	Wk1.ppt	1-3, 1-14, 2-8, 2-9, 2-20, 2-27
31 Aug No class Sep 7)	2	Chap. 3	Decision Analysis	Wk2.ppt	3-9, 3-19, 3-21, 3-23, M3-14 (on CD-ROM)
14 Sep	3	Chap. 4	Regression Models	Wk3.ppt	4-22, 4-19
21 Sep	4	Chap. 5, 6	Forecasting Inventory Control Models Correct Inventory Management	Wk4.ppt	5-1, 5-3, 5-8, 5-18. 1-19, 5-37. 6-5, 6-35, 6-36
28 Sep	5	Chap. 7	Linear Programming Models: Graphical and Computer	Wk5.ppt	7-5, 7-14, 7-19, 7-26, 7-29, 7-30, 7-33, 7-37
5 Oct	6	Chap. 8	Linear Programming by Computer Analysis (Excel & QM) Hand-Out Mid Term Exam	Wk6.ppt	8-4, 8-9, 8-11, 8-14
12 Oct	7 Exam Due	Chap. 9	Linear Programming: The Simplex Method (Also Analysis on the back of an envelope) Mid Term Exam Due Homework Notebook Due	Wk7.ppt	9-6, 9-17, PQ, PQ Plus  (PQ problesm are on PowerPoint Handouts)
19 Oct	8	Chap. 10	Transportation/Assignment Models	Wk8.ppt	10-11, 10-12, 10-38
26 Oct	9	Chap. 11	Integer / Goal Programming and Branch and Bound	Wk9.ppt	11-13, 11,24  Case-Puyallup Mall (Optional M1-4 & M6-5 on CD-ROM)
2 Nov	10	Chap. 12	Network Models	Wk10.ppt	12-7, 12-19, 12-20, 12-21, Case - Southwestern U Traffic (Optional M2-12 on CD-ROM)
9 Nov (No class 16 or 23 Nov )	11	Chap 13	Project Scheduling Project Management	Wk11.ppt Wk12.ppt	13-12, 13-19, 13-27
30 Nov	12	Chap 14 Chap 15	Waiting Line, Queuing Theory and Simulation Models	Wk13. Wk14.ppt Harry's Tire Shop Simkin Inventory Port of New Orleans Three Hills Power	14-11, 14-17, 14-30 15-7, 15-15, 15-25
7 Dec	13	Chap. 16, 17	Markov Processes Statistical Process Control Hand out Final Exam	Wk15.ppt	16-8 16-14, 16-18, 16-19 Case - Rentall Trucks 17-11, 17-16
14 Dec		Finals Week	Final Exam and Homework Notebook Due		Research Project and Application Project can be turned in at any time prior to the last class.