In this course, students will learn how to use mathematical modelling to support practical business management decisions. The course will give an introduction to the use of the most common modelling techniques for deterministic optimisation, such as linear programming (LP), integer programming (IP), mixed-integer programming (MIP) and nonlinear programming (NLP). Applications of these methods in logistics/operations, strategy, marketing, and finance will be demonstrated through exercises, using state-of-the-art software.
- The concept of a mathematical programming model
- Linear programming models and the importance of linearity
- How to interpret model output
- Sensitivity and scenario analysis
- Network models
- Multi-period planning models
- Integer and mixed-integer models
- Special ordered sets of variables
- Good and bad formulations
- Non-linear models
- Multi-objective models
- Various applications
Learning outcome knowledge
Students should develop skills in quantitative modelling of business problems and opportunities, and they should understand how such modeling techniques can be used to assist the decision-maker, when they are applicable, and what the main challenges in practical applications are.
Students should also get an understanding of why some problems are hard to solve while other problems can be easily solved using standard software.
- Written assignment: 30%
- Written exam: 70%