This is a template for course syllabus.

Learning Objectives

This course will form a foundation for your future coursework at Simon and you should expect to apply what you learn here in later courses as well as the workplace. The course has two major objectives:

to develop your ability to frame business decision problems in a way that makes them amenable to quantitative analysis and
to train you in fundamental quantitative analysis techniques useful for business problems.

Course Description

The course is structured in three parts.

Model business decision problems in a structured way using spreadsheets
Use the computer to solve complex decision problems involving many variables and constraints.
Use Monte Carlo simulation so that you will have a framework for understanding and analyzing uncertainty in business.

All three parts are strongly interrelated. We will draw upon examples from different functional areas so that you will see how the techniques taught can be applied in a practical way to a variety of settings. All assignments and exams will be computer-based.

TextBook

The recommended textbook for this course is Management Science: The Art of Modeling with Spreadsheets, by Stephen G. Powell and Kenneth R. Baker, 3rd edition or above. It is an excellent reference for most of the topics covered in the course.

Software

The course software is RiskSolver, which is available here. Please make sure you have it installed before our second class.

Grading

Homework assignments	40%
Professionalism and Class Participation	10%
Final Exam	50%

Schedule

Week	Date	Session	Module	Topic	Reading (3rd version)
1	1/10	1	Building Models	Influence Diagram	Chapter 2 pp. 26-34
1	1/10	2	Building Models	Spreadsheet Engineering	Chapter 5 pp. 95-111
2	1/17	3	Building Models	Sensitivity Analysis	Chapter 6 pp. 119-132
2	1/17	4	Optimization	Introduction to Optimization	Chapter 10 pp. 206-231
3	1/24	5	Optimization	Linear Optimization	Chapter 10 pp. 206-231 Chapter 12 pp. 281-305
3	1/24	6	Optimization	Case 1: Bloomex.ca
4	1/31	7	Optimization	Binary Variables	Chapter 13 pp. 314-323
4	1/31	8	Optimization	Case 2: DHL Supply Chain
5	2/7	9	Simulation	Randomness and Probability	Chapter 16 pp. 392-412
5	2/7	10	Simulation	Building Simulation Models
6	2/14	11	Simulation	Sensitivity Analysis	Chapter 16 pp. 412-424
6	2/14	12	Simulation	Case 3: Printicomm
7	2/21	13	Simulation	Optimization under Uncertainty	Chapter 17 pp. 448-466
7	2/21	14	Simulation	Course Review and Homework Discussions

Need help?

Office Hours: Tuesday, 1-2 am

Email: huaxia.rui@simon.rochester.edu

Phone: 585-275-4278

TA Office Hours: Thursday 6 - 7:30 pm & Sunday: 1 - 2:30 pm, at Zoom

TA Email: cli83@simon.rochester.edu