Modeling Business Decisions

General characterization

Prerequisites

This course involves a hands-on, in-class learning experience, so attending each class and bringing a laptop computer to class are absolutely essential. Course requirements also consist of creating and analyzing models of assigned problems and cases on spreadsheets.

Everyone is expected to know the basics of working with Excel spreadsheets, multivariable calculus, statistics and microeconomics. Basic knowledge of Excel include developing and copying formulas with relative and absolute cell addresses, and using the function and chart wizards. Students should also be familiar with equilibrium comparative statics with unconstrained and constrained optimization, the Lagrange multiplier and shadow prices, local and global optima and the envelope theorem. Everyone is also expected to have some familiarity with microeconomics and functional areas of management such as operations, and finance, marketing. Finally, one should not be averse to analytical thinking and quantitative analysis in general.

Bibliography

There is only one required textbook for this course: Albright, S.C. and Winston, W.L., Management Science Modeling, 3rd or 4th edition are OK, Cengage Learning. Chapters: 1, 3-7, 11 and 12.

Students should not expect the instructor to write down lecture notes on each topic and post them in moodle or to email them. However, in each class, the instructor will highlight the material she feels most important or that is conceptually difficult, where she can provide an alternate explanation or modeling to complement the textbook´s presentation. This is a very practical/interactive course and students should attend lectures and take their own notes. Whenever appropriate the instructor will provide some additional readings. Students should always read the textbook chapters on the topics discussed in class.

Teaching method

The course has a highly interactive format with in-class exercises and assignments designed to engage students in problem-based learning in order to help them understand complex concepts quickly. Each student should bring his or her own laptop, or else can use the facilities in the PC pool. Because of its practical nature, students should be aware that the course is quite time consuming as learning goals can only be achieve with a learning by doing experience.

Evaluation method

• 1st Group assignment: 40% of your grade.
• 2nd Group assignment (sent out to students on the last lecture day of the
course): 30% of your grade. Due on the exa• 1st Group assignment: 40% of your grade. • 2nd Group assignment (sent out to students on the last lecture day of the course): 30% of your grade. Due on the exam date (this is just a reference date!) established by NovaSBE. No exam takes places for this course. • Individual assignment (taken in class, open book), last lecture day of the course: 30% of your grade with minimum passing grade of 10/20 points.

Attendance is mandatory. More than two (2) un-excused absences will result in failure for the course. You are NOT excused to miss any of the lectures during the last week of classes. m date (this is just a reference date!)
established by NovaSBE. No exam takes places for this course.
• Individual assignment (taken in class, open book), last lecture day of the
course: 30% of your grade with minimum passing grade of 10/20 points.

Attendance is mandatory. More than two (2) un-excused absences will result in
failure for the course. You are NOT excused to miss any of the lectures during
the last week of classes.

Subject matter

The Course Outline is:
1. Introduction
2. Introduction to Optimization Modeling
3. Linear Programming Models
4. Sensitivity Analysis
5. Network Models
6. Optimization Models with Integer Variables
7. Nonlinear Optimization Models
8. Forecasting Models
9. Introduction to Simulation Modeling
10. Monte Carlo Simulation Models

Programs

Programs where the course is taught: