BU.520.601(K1, K2)- Decision Models – Dr. Hossein Arsham - Page 2 of 4
/Decision Models
2 CreditsBU.520.601 (K1, K2)
10-22-2013 to 12-10-2013
T 09:00 AM - 12:00 PM
T 01:30 PM - 04:30 PM
Fall 2013
Downtown Baltimore, Harbor East 206
Instructor: Dr. Hossein Arsham
Contact Information
Phone Number: (443) 721 – 4125
E-mail Address:
Office Hours: By appointment
T 12:00 PM - 01:30 PM
Required Text and Learning Materials
Stephen G. Powell and Kenneth R. Baker, Management Science: The Art of Modeling with Spreadsheets, 3rd edition, John Wiley & Sons Inc. ISBN 978-0-470-53067-2
Additional learning material in the form of notes, copies of power point slides and / or Excel spreadsheets may be posted from time to time; these can vary from instructor to instructor
For learning EXCEL there are several resources available.
· A number of books on Microsoft Excel are available; you may find some inexpensive paperback quite useful.
· Answers to most questions on use of EXCEL can be found by searching the Internet.
Blackboard Site
A Blackboard course site is set up for this course. Each student is expected to check the site throughout the semester, as Blackboard will be the primary venue for outside classroom communications between the instructors and the students. Students can access the course site at https://blackboard.jhu.edu. Support for Blackboard is available at 1-866-669-6138.
Course Evaluation
As a research and learning community, the Carey Business School is committed to continuous improvement. Therefore each student must complete the course evaluation as part of the continuous improvement process. Information on how to complete the evaluation will be provided near the end of the course.
Disability Services
Johns Hopkins University and the Carey Business School are committed to making all academic programs, support services, and facilities accessible. To determine eligibility for accommodations, please contact the Carey Disability Services Office at time of admission and allow at least four weeks prior to the beginning of the first class meeting. Students should contact Rachel Hall in the Disability Services office by phone at 410-234-9243, by fax at 443-529-1552, or email: .
Important Academic Policies and Services
· Honor Code
· Statement of Diversity and Inclusion
· Tutoring
· Carey Writing Center
· Inclement Weather Policy
Students are strongly encouraged to consult the Johns Hopkins Carey Business School Student Handbook and Academic Catalog and the School website http://carey.jhu.edu/syllabus_policies for detailed information regarding the above items.
Course Description:
This course discusses quantitative methods that have proven to be particularly useful for decision making in business settings. The course covers a variety of models and methodologies. While a number of software programs are available the course will leverages the capabilities of Excel for a large number of topics. However, an emphasis will be placed on formulating problems, translating those formulations into useful models, optimizing and/or displaying the models, and interpreting results. The lessons of this course prepare students to perform the analysis required in subsequent courses and in practice. Topics such as Linear and Integer Linear Programming, Network Flow, Decision Analysis, and Monte Carlo Simulation will be discussed to demonstrate applications in planning and control for different types of business decisions.
Course Overview:
This course will not produce experts at modeling the most complex decisions. Its goal is to produce managers who are comfortable with formulating models of important and realistic decisions, solving them using a spreadsheet (typically Microsoft Excel), and making sense of the results. Some of the models discussed in the course are well documented in the academic literature while others are quietly being used in practice. The primary emphasis of this course is on formulation and interpretation, but you will pick up quite a few spreadsheet skills along the way. We will engage in systematic approaches to a wide array of problems. The style of analysis, model development, optimization, and interpretation lends itself to a plethora of problem settings, and develops a set of fundamental skills that are essential for survival when dealing with difficult decisions in an uncertain world.
Student Learning Objectives for This Course
All Carey graduates are expected to demonstrate competence on four Learning Goals, operationalized in eight Learning Objectives. These learning goals and objectives are supported by the courses Carey offers. For a complete list of Carey learning goals and objectives, please refer to the website http://carey.jhu.edu/LearningAtCarey/LGO/index.html.
The learning objectives for this course are:
1. Identify and describe the trade-offs that define a problem setting.
2. Translate this understanding into a problem formulation.
3. Create a spreadsheet-based model that embodies this formulation.
4. Utilize the capabilities of Excel to develop insights about what should be done in the setting of interest.
5. Interpret the output of a decision model and use it as a guide to improve performance.
Attendance Policy
Attendance and class participation is expected from everyone; students are expected to inform in advance if they have to miss a class due to business travel or other important matters. They are however responsible for submission of assignments on time as well as keeping up with the material covered in the missed lecture. Failure to inform will be treated as absence without excuse.
Absence due to illness or family emergency will be handled on individual basis.
Assignments and Tests:
There will be 4 to 5 assignments; larger assignments can be submitted in groups of 2 or 3. In addition, there will be a group exercise (in class, in lecture 7). This exercise also requires a submission of report. The last lecture will be devoted to the final exam; open-book, open-notes. The exam will be mostly on modeling aspects rather than questions involving expertise in spreadsheets. Exam duration: 2 ½ hours.
Evaluation and Grading:
Assignment / Learning Outcome / WeightHomework assignments / 1 – 5 / 40%
In class exercise and report / 1 – 5 / 20%
Final Exam / 1 – 5 / 40%
Important notes about grading policy:
The grade for good performance in a course will be a B+/B. The grade of A- will only be awarded for excellent performance. The grade of A will be reserved for those who demonstrate extraordinarily excellent performance. The grades of D+, D, and D- are not awarded at the graduate level. Grade appeals will ONLY be considered in the case of a documented clerical error.
Tentative Course Calendar*
*The instructor reserves the right to alter course content or adjust the pace to accommodate class progress.
Class / Content / Selected topics from textbook chapters¶1 / Introduction, Hand on exercise, Using Excel / 1, 2, 3
2 / Linear Programming (LP) - also called linear optimization: History, two-variable LP with the graph of the feasible region. / 10.1, 11.1 to 11.4
3 / LP: Understanding solver answer report. LP Sensitivity Analysis: effect of changes in the objective function and RHS coefficients. / 11.5
4 / Network based Decision Models and Integer Programming: Transportation / transshipment models, Assignment, Capital budgeting, Knapsack Set covering, Dynamic lot sizing Multi-variable formulation.
Allocation, blending and production planning, aggregate planning,models. / 12.1 to 12.5, 13
5 / Decision Analysis (DA): Terminology, DA without probabilities (Maximax, Maximin, Minimax Regret), DA with probabilities: (Decision point / branch, chance event / branch, .., Decision tree with examples including sensitivity analysis, Earned value of information),
Brief discussion of utility theory. / 15
6 / Simulation / 16, some discussion from 17
7 / In class exercise:
Semester Review
8 / Final Exam (Open book, open notes)
¶ Some topics included in the course may not be covered in the textbook.
¶ Some topics from other chapters not listed may be covered or pointed out for additional reading.
Copyright Statement
Unless explicitly allowed by the instructor, course materials, class discussions, and examinations are to be used by class participants only. The recording and rebroadcasting of such material, by any means, is forbidden. Violations are subject to sanctions under the Honor Code.