Mathematics for Decisions

TECH4 Mathematics for Decisions

Spring 2025

Autumn 2025
  • Topics

    Firms seek to allocate resources and plan activities in order to create value for stakeholders, given an increasingly complex and uncertain environment. Mathematics and information technology are becoming more important as tools to support decisions.

    Mathematics for decisions will address the following questions:

    • How can we build mathematical models for decision making in a given practical setting?
    • How can we use computer tools to solve and analyze the models numerically?
    • How can we use the model results for improved decision making?

    The course will use methods from mathematics and statistics, and they will be applied to a wide range of decision situations that are related to courses in economics and business administration.

    Mathematical theory/methods and numerical implementation via Python-based tools, such as Pyomo or GurobiPy, will be taught in parallel.

    The teaching will be problem-based, where models are developed from practical situations, and theory/methods are covered when suitable.

  • Learning outcome

    Upon course completion, the candidate will be able to:

    Knowledge

    • Describe and explain various optimization techniques.
    • Demonstrate proficiency in mathematical formulations and modeling techniques for real-world decision-making problems.
    • Elaborate on the basics of decision analysis and risk management to make informed decisions in deterministic and uncertain settings.

    Skills

    • Build practical mathematical models for decision-making.
    • Use relevant software tools and programming languages for solving optimization problems.
    • Evaluate and interpret model results for improved decision-making.

    General competences

    • Independently apply mathematical methods in various decision situations, especially related to economics and business administration.
    • Effectively convey research findings to both experts and non-experts in a clear, concise, and rigorous manner, aiming to offer valuable business insights to a diverse audience

  • Teaching

    Lectures and programming sessions.

  • Compulsory Activity

    There will be one assignment given during the semester that must be completed and approved for course approval.

  • Assessment

    The assessment in TECH4 consists of two parts:

    • 4-hour digital school exam (60%), individual.
    • 1-week homework (assignment - 40%), individual or in groups of two students freely chosen.

    Both parts must be answered in English.

  • Grading Scale

    A - F

  • Computer tools

    Python with optimization packages and solvers, open-source repositories and cloud services.

  • Literature

    • F. Hillier, G. Lieberman. Introduction to Operations Research. McGrawHill, International Student Edition (Evergreen Release or 11th Ed).
    • T. Roughgarden. Algorithms Illuminated Omnibus Edition (September 2022).
    • Link to Articles/Reports/Chapters and to software coding materials will be posted in Canvas and handed out in Lectures

  • Permitted Support Material

    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/

  • Retake

    Retake is offered early in the non-teaching semester for students who were registered for the exam at the time of the assessment in the teaching semester, and did not achieve a passing grade. Other students may retake the exam the next time the course is offered.

    The assignment cannot be retaken in the non-teaching semester, and may be retaken the next time the course is offered.

    For detailed information regarding the retake policy, please visit our website: https://www.nhh.no/en/for-students/examinations/retake-of-exams/https://www.nhh.no/en/for-students/examinations/retake-of-exams/ (copy url).

Overview

ECTS Credits
10.0
Teaching language
English
Teaching Semester

Autumn. Will be offered autumn 2025.

Course responsible

Professor Mario Guajardo, Department of Business and Management Science (main course responsible)

Assistant Professor Lars Jaffke, Department of Business and Management Science