BAN402 Decision Modelling in Business (E)

• Topics

  This course is about formulating, analyzing and solving models for making optimal decisions in business, using data and computer-based decision support. The formulation of the models is based on mathematical optimization. To process data and solve the models, we use up-to-date computational tools specially designed to find the best decisions to a mathematical optimization model.

  The course focuses on problems that capture strategic, tactical, operational and economic aspects involved in the decision making of organizations. These include, for example, applications of decision modelling in business related to logistics, energy, natural resources and the environment. 

  The methods studied in the course come mainly from fields labeled as Operations Research, Management Science, and Prescriptive Analytics. Specific topics include linear programming, integer programming, nonlinear programming, economic interpretation, computational optimization.

• Learning outcome

  By the end of this course the students

  Knowledge

  • are familiar with the application and impact of decision models in real-world problems
  • are able to explain and discuss key concepts in decision making and optimization
  • are able to understand decision modelling works published in major scientific journals and formulate relevant research questions

  Skills

  • are able to formulate decision-making problems into an optimization model
  • can implement and solve the optimization model as well as interpret the results
  • have developed good analytical skills for decision making in business
  • are able to identify, analyze and process the data needed as input for a decision model
  • have developed good skills to write codes and to cope with errors in a computational software

  General competences

  • are able to use computational tools for implementing and solving a decision model
  • are able to analyze performance of decision making and solution quality by support of computational tools

• Teaching

  Lectures, projects, lab sessions, software coding.

• Credit reduction due to overlap

  Course identical to BUS461 (former ENE420)

• Compulsory Activity

  Approval of 2 case assignments.

  Compulsory activities from previous semesters are not valid. Students who completed the assessment before these requirements were introduced must obtain course approval.

• Assessment

  4 hour written school exam (pen and paper).

  This course is a continuation of BUS461 and the total number of attempts applies to the course (not the course code).

• Grading Scale

  A - F

• Computer tools

  Python with commercial solver Gurobi (see www.gurobi.com for academic licenses)

• Literature

  Recommended literature will be provided on Canvas at the beginning of the semester.

• Permitted Support Material

  Calculator

  One bilingual dictionary (Category I)

  All in accordance with Supplementary provisions to the Regulations for Full-time Study Programmes at the Norwegian School of Economics Ch.4 Permitted support materialhttps://www.nhh.no/en/for-students/regulations/https://www.nhh.no/en/for-students/regulations/and https://www.nhh.no/en/for-students/examinations/examination-support-materials/https://www.nhh.no/en/for-students/examinations/examination-support-materials/