BUS336 Optimization Methods in Business Analytics
Credits (ECTS):5
Course responsible:Marie Gotteberg Steen
Campus / Online:Taught campus Ås
Teaching language:Norsk
Course frequency:Annually
Nominal workload: Nominal workload: 125 hours. Exercises: Appox. 18 hours + own work through problem solving and self-study
Teaching and exam period:This course starts in Spring parallel. This course has teaching/evaluation in Spring parallel.
About this course
Management Science is an approach to management decision-making that makes extensive use of quantitative methods. This course aims to introduce students to the application of quantitative techniques to problems where models capture problem structure and use it to help optimise the decision outcome. The most central methods are linear programming including graphical representations, sensitivity analysis, different classes of network models, integer/binary programming, non-linear programming and goal programming. A combination of computer sessions and example classes demonstrate how advances in computing power have made these techniques more accessible to managers and how the techniques can be applied to a range of different situations. These broad aims map to a number of explicit learning outcomes presented below.
Learning outcome
Knowledge
On completion of the course students should be able to:
- discuss the practical use of the techniques covered
- use the modelling techniques covered to help structure management problems
- solve models built using the techniques covered
- demonstrate that they can identify which of the techniques covered is most suitable for a management problem
- demonstrate that they can interpret the results of their analysis of a management problem
Skills
On completion of the course students should:
- be able to demonstrate that they can build and analyse a model of a management problem
- be able to demonstrate their ability to apply their computer skills to support the analysis of a management problem
- have developed their quantitative and modelling skills.
Learning activities
Teaching support
Prerequisites
Recommended prerequisites
Assessment method
Examiner scheme
Mandatory activity
Teaching hours
Reduction of credits
Admission requirements