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2015/2016  KAN-CMATV1063U  Mathematical Optimization: Models, Methods and Applications

English Title
Mathematical Optimization: Models, Methods and Applications

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc/MSc in Business Administration and Management Science, MSc
Course coordinator
  • Dolores Romero Morales - Department of Economics (ECON)
Main academic disciplines
  • Finance
  • Economics
Last updated on 18-02-2016
Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors: During the course, and through a hands-on approach supported by optimization theory, students will develop quantitative skills needed for Decision Making, as well as learn to appreciate the implications of multiple objectives and uncertainty in Decision Making and the need for flexible and robust solutions.
Examination
Mathematical Optimization: Models, Methods and Applications:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual
Size of written product Max. 10 pages
Assignment type Written assignment
Duration Written product to be submitted on specified date and time.
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period Autumn
Make-up exam/re-exam
Same examination form as the ordinary exam
Course content and structure

This course aims to enhance your theoretical knowledge of and practical skills in Optimization tools. The course uses computer software to illustrate how to apply the methodologies we introduce. The course is multidisciplinary in nature with links to areas such as economics, finance, marketing, and operations management. The structure of the course is as follows:

 

          Mixed Integer Linear Programming

  • Modelling
  • Methods
  • Applications

          Nonlinear Programming

  • Modelling
  • Methods
  • Applications

          Multiobjective Optimization

  • The Pareto Frontier
  • Methods
  • Applications

          Stochastic and Robust Optimization

  • Modelling
  • Methods
  • Applications

          Heuristics

  • Constructive
  • Matheuristics
  • Metaheuristics

 

The course’s development of personal competences:

 
Teaching methods
Lectures, Exercises, Demos, Computer Workshops
Further Information

Main academic disciplines: Optimization, Economics, Finance
Expected literature

Expected literature

 

Model Building in Mathematical Programming, H.P. Williams (Wiley)



Model Solving in Mathematical Programming, H.P. Williams (Wiley)



Operations Research: Applications and Algorithms, W.L. Winston (Duxbury)


Optimization in Operations Research, R.L. Rardin (Prentice Hall)
Last updated on 18-02-2016