In this course, we will learn how to:
- Develop mathematical models to analyse complex business situations.
- Implement mathematical models in appropriate software, e.g., Excel, GAMS, or MATLAB, to solve business cases.
- Test the validity of the model’s assumptions by performing sensitivity analysis and interpreting the findings.
Application areas include defense, energy, environment, finance, human resource management, IT planning, logistics, manufacturing, marketing, and transportation. Quantitative methods such as linear programming (LP), integer programming, network flows, multi-criteria analysis, and simulation will be applied as appropriate with an emphasis on problem formulation and computational implementation with realistic data. This course is designed to develop students’ problem-solving skills and expertise in state-of-the-art decision tools. The emphasis will be on understanding the models thoroughly so that they may be applied to analyse real-world business decisions. As always, while a mathematical approach is encouraged throughout, the main concepts will be illustrated through extensive case studies. Furthermore, emphasis is placed on the intuition behind the concepts to enable more profound understanding. Students registering for this course would benefit from a solid grounding in mathematics, statistics, or programming.
The course is given in period I such that the first four (recorded) lectures are given in 21-24 September and the second four in 5-8 October (9:00-12:00). The course is assessed through a group assignment and a final examination (both graded on an 1-5 scale). The assignment will consist of case studies that groups of students will solve together. It will cover topics from the first four sessions and will be available on 24 September with a deadline of 4 October. The final exam will be a take-home assessment during 19-23 October. Grading is based 25% on the assignment and 75% on the exam.
Both the lecturer and the teaching assistant will have remote drop-in help sessions for the group assignment, more information on these later.
Lecturer: Afzal Siddiqui
Course Assistant: Olli Herrala
E-mail addresses: firstname.surname (at) aalto.fi
Ragsdale, Cliff T. (2015), Spreadsheet Modeling & Decision Analysis: a Practical Introduction to Business Analytics, Cengage Learning, Stamford, CT, USA (ISBN: 9781285418681)
||Content||Recommended reading (Ragsdale, 2015)|
||Lecture 1: Linear Programming (LP)
|Chapter 2, Sections 3.0 to 3.8, Sections 4.0 to 4.6|
|22.9.||Lecture 2: LP Applications in Business
|Sections 3.9, 3.10, and 3.12|
|23.9.||Lecture 3: Network Models
|24.9.||Lecture 4: Integer Programming (IP) and Its Business Applications
|4.10.||Group assignment deadline|
|5.10.||Lecture 5: Multi-Period Planning
|6.10.||Lecture 6: Multi-Criteria Decision Making
|7.10.||Lecture 7: Simulation
|8.10.||Lecture 8: Project Management