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KRANNERT SCHOOL OF MANAGEMENT PURDUE UNIVERSITY

Fall 2011 MGMT 30600 – Management Science Instructor:

Prof. Patrick Johanns Office: Krannert Center 232 Phone: 494-4431 Office Hours: MW: 12:00 – 1:00pm, T: 3:00 – 5:00pm or by

appointment E-mail: [email protected]

Course Coordinator: Prof. Patrick Johanns

Admin. Assistant:

Julie Gable Office: Krannert KRAN 519 Phone: 494-4371 Office Hours: Daily 7:30 am to 2:30 pm E-mail: [email protected]

Class Hours: Division 01: Johanns MW 9:00am - 10:15am Division 02: KRAN G18

Johanns

KRAN G18

MW 10:30am - 11:45am

Division 03:

Johanns

MW 1:30pm - 2:45pm

KRAN G18

Division 04:

Johanns

MW 3:00pm – 4:15pm

KRAN G18

Division 05:

Li

MW 4:30pm - 5:45pm

KRAN G18

Course web page:

http://katalyst.mgmt.purdue.edu/

COURSE COREQUISITE: MGMT 30500:

Business Statistics

TEXTBOOK Management Science with Spreadsheet Modeling 2nd Edition, by Patrick Johanns, Kendall/Hunt Publishing Company, ISBN 978-0-7575-7172-5, 2010.

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COURSE OBJECTIVES Objective 1:

To acquaint you with mathematical spreadsheet modeling techniques and solution methods which often serve as an aid to managerial decision making.

Objective 2:

To develop your expertise in using and solving management science problems with the help of personal computer and decision tool software.

Objective 3:

To give you experience in analyzing results and making decisions through assigned homework exercises and performing case analysis in class.

COURSE OVERVIEW The field of management science focuses on quantitative methods that aid in making effective decisions in a business environment.  You will formulate, solve, and interpret optimization models from various applications areas in management including marketing, accounting and finance.  Insights gained from the mathematical modeling and solution process will be discussed and analyzed. Results will be examined in the context of the decision problem and revision of the model will be proposed and analyzed. Primary emphasis will be placed on formulating decision problems as optimization models and solving them by the Excel tools and other decision analysis software. This course will require the use of personal computers and spreadsheet-based decision tool software. 

YOUR ROLE IN THE COURSE Class Participation. Class participation is crucial for learning the course content and for keeping in pace with the class progress. 1) You should be prepared for each class and should try to contribute to class discussions. Active and cooperative learning will be encouraged. During the lecture, you are expected to answer/raise questions, and participate in small-group activities such as modeling and solving problems, and interpreting solutions. 2) You should read the assigned sections from the textbook and any other course material that is posted on Katalyst. 3) Attendance will be taken on the class dates and will constitute part of your participation grade.

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Computer Lab Sessions. A major intent of this course is to give you the skills to create spreadsheet models of business problems and use software to find good solutions to those problems. To help achieve this end, we will have four computer lab sessions this term where we will guide you through hands-on sessions. The skills developed during these sessions will be valuable when doing the homework, during the exams, and in jobs after you graduate. We will break the class down into two groups on lab days in order to give you more individualized attention. Before each lab, we will let you know which lab room you have been assigned. Homework Assignments. You will apply the concepts, theory and methods learnt in class to a variety of problems. You will formulate, solve and analyze models with the help of the Excel tools and other Software. Most of the assignments will be taken from the textbook. Homework assignments must be prepared individually or in a group of two students from the same section. Only one report must be submitted for the group. 1) All assignments should be prepared professionally. Every assignment must include your and your partner’s names and section time. The pages in your book are designed so you can remove problems from them and hand them in. Computer results should be neatly displayed. Unorganized, illegible, or incomplete assignments will not be graded. 2) Due Dates for homework are specified on the course. Homework assignments should be turned in by 2:20 pm on the due date to Julie in 519 Krannert. They will be posted one week prior to their due date on Katalyst. Late assignments will not be accepted. 3) Homework solutions will be posted on the course web page by the following day that they are collected. It will be helpful to read through the solutions before the upcoming quiz. 4) The lowest homework grade will be dropped.

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Quizzes. Short, 15-minute quizzes will be given periodically throughout the semester typically in the class following the homework and as designated in the outline 1) The quiz will be based on the material covered in the previous homework and will mostly emphasize recently discussed material. 2) Quizzes will be closed book and notes. Each student will be allowed a single sheet (8.5” x 11”, double sided) of notes for each quiz. Auxiliary tables and formulas will only be included if required. 3) No make-up quizzes will be given unless deemed necessary and must be agreed by instructor in advance. 4) Quiz solution will be posted on the course calendar by the following day. 5) The lowest quiz grade will be dropped. This policy is adopted in case you have a job interview, illness, or other situation that might prevent you from attending class. Examinations. Two evening exams and a final exam will be administered as scheduled in the course outline. Examinations will be closed book and notes. 1) Each student will be allowed a single 8.5” x 11” sheet of “crib” notes for the evening examination. Three such sheets of crib notes will be allowed for the final exam. No photocopies will be allowed. 2) No make-up exams will be given unless required by Purdue University policies. Students who are eligible for a make-up exam or need extra time must contact the instructor at least one week prior to the exam date.

COURSE HONOR PRINCIPLE We expect and encourage students to discuss readings, computer exercises, homework exercises, and other course content with their classmates. Such discussions constitute a valuable aspect of the student's own learning experience. However, all work counted towards the students’ grade must be prepared/answered solely by the individual student or the group members submitting it. Photocopied homework solutions will not be accepted. In addition, students are expected to prepare homework and other instructional materials without using materials or advice from students who have taken the course previously. Examinations and quizzes will be closed book and notes. Auxiliary tables and formulas will be included if deemed necessary by the course coordinator. However, each student will be allowed a single 8.5” x 11” sheet (both sides) for each quiz and evening examination and three such sheets of "crib" notes for the final exam (no photocopies). Cheating in any form will not be tolerated. Any student caught cheating will be censured in full accordance with Purdue University policies. Students are strongly recommended to read the academic integrity guide published by the Office of the Dean of Students at http://www.purdue.edu/ODOS/osrr/integrity.htm . 4

GRADING SYSTEM This course follows Krannert’s guidelines for upper-.level undergraduate core classes and uses plus/minus grades. At the end of the term your weighted points will be totaled and your class percentile calculated. Grades will be allocated as follows: Grade A AB+ B BC+ C C- and below

Percentile needed 75th 70th 65th 40th 35th 30th 10th Instructor’s judgment will be used for the cut offs for grades below a C-.

Elements of your coursework will be weighted as follows to evaluate your performance in MGMT 30600: Class attendance and participation Homework assignments In-class quizzes Evening examinations Final examination

8% 15% 12% 40% 25%

Major Campus Emergencies In the event of a major campus emergency, course requirements, deadlines and grading percentages are subject to changes that may be necessitated by a revised semester calendar or other circumstances. Information will be provided through Katalyst and emails, or you may contact your instructor by email or phone.

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MGMT 306 Fall 2011 Tentative Class Calendar Week

Date

Class

1

22-Aug 24-Aug

2

2

29-Aug

3

31-Aug

4

1

3

5-Sep

4

7-Sep 12-Sep

5 6

14-Sep

7

19-Sep

8

21-Sep

9

26-Sep

10

28-Sep

11

3-Oct

12

5-Oct

13

5

6

7

9

10

11

12-Oct

14

17-Oct

15

19-Oct

16

24-Oct

17

26-Oct

18

31-Oct 3-Nov

Course Introduction, Linear Programming Models Graphical Solution Methods

Chpt. 1

Lab Session I: Computer Solution of LPs Sections 1 & 2 will be in ENAD 135 or KRAN Lab 2, Sections 3, 4, and 5 will be in KRAN Labs 1&2 Linear Programming Sensitivity Analysis

Due

Chpt. 3 Chpt. 2 & 3

Chpt. 3

Sensitivity Analysis with Computer Output Linear Programming Applications: Product-Mix, Marketing Research Linear Programming Applications: Multi-period Production-and-Inventory Management Nonlinear Optimization Models, Solution and Applications; Pricing Models, Portfolio Optimization Model Optimization Models with Integer Variables: Capital Budgeting, Fixed-cost Models Lab Session II: Computer Modeling of NLPs Sections 1 & 2 will be in ENAD 135 or KRAN Lab 2, Sections 3, 4, and 5 will be in KRAN Labs 1&2 Optimization Models with Integer Variables: Vehicle Routing, Workforce Scheduling Integer Programming Application: Airline Hub Location-Service Model, Personnel Assignment Model Review for Exam 1

Chpt. 4 Chpt. 4

19

Monte Carlo Simulation; Simulation Modeling with Excel Tools and @RISK Simulation Modeling and Applications: Bidding for Contract, Investing for Retirement Simulation and Analysis Applications Lab Session III: Simulation Modeling - Sections 1 & 2 will be in ENAD 135 or KRAN Lab 2, Sections 3, 4, and 5 will be in KRAN Labs 1 & 2 Project Management: Critical Path Method, Application in Software Development Project No Class in lieu of Evening Exam Review for Exam 2 Evening Exam 6:30 - 7:30 pm CL50 224 or WTHR 104

HW 1 Quiz 1

Chpt. 4 Chpt. 5

Chpt. 6

HW2 Quiz 2

Chpt. 5

Chpt. 6 Chpt. 6

HW 3

Quiz 3 Exam 1

Evening Exam 8:00-9:00 pm PHYS 112 or PHYS 114 Fall Break - No Class

10-Oct

2-Nov

Reading

Labor Day - no class

6-Oct 8

Topic/Activity

Chpt. 7 Chpt. 7 Chpt. 7 Chpt. 7

Chpt. 8 HW 4 Quiz 4 Exam 2

6

12

13

14 15

16

Finals Week

7-Nov

20

21-Nov

Project Management: Project Evaluation and Review Technique (PERT) Project Management: Applications of PERT, Time-cost Trade-offs Decision Analysis: Pay-off Table, Decision Tree, Optimistic and Pessimistic Approaches Decision Analysis: Min-max Regret Approaches, Expected Value Approach, Expected Value of Perfect Information No Class in lieu of Evening Exam

9-Nov

21

14-Nov

22

16-Nov

23

23-Nov

Thanksgiving Break - No Class

28-Nov

24

30-Nov

25

5-Dec

26

7-Dec

27

12 Dec 17 Dec

Lab Session IV: Decision Analysis using PrecisionTree - Sections 1 & 2 will be in ENAD 135 or KRAN Lab 2, Sections 3, 4, and 5 will be in KRAN Labs 1 & 2 Multi-criteria Decision Models: Efficient Frontier, Efficient Solutions for Investment Multi-criteria Decision Models and Solution: Goal Programming, Computer Production Planning Review for Final Exam

Chpt. 8 Chpt. 8 Chpt. 9 Chpt. 9

HW 5

Chpt. 9

HW 6 (Due Dec. 1)

Chpt. 10

Quiz 5

Chpt. 10

Final Exam Time and Location to be announced

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