Business Optimization

Introduksjon

Please note that this is a preliminary course description. The final version will be published in June 2026.

In an increasingly complex and uncertain business environment, where resources are limited and competition is intense, relying on intuition alone is no longer sufficient. Effective decision-making must be grounded in data, supported by analytical tools, and capable of addressing both deterministic and uncertain factors.

This course equips students with the fundamental skills and tools of business optimization, focusing on how mathematical modelling can be used to support and improve managerial decision-making. Students will learn how to formulate and solve optimization problems using widely applied techniques such as linear programming (LP) and mixed-integer programming (MIP). For complex or large-scale problems where exact solutions are difficult to obtain, the course introduces heuristic methods. Additionally, students will gain an introduction to optimization approaches that incorporate uncertainty, preparing them to tackle more realistic and dynamic business challenges.

Through practical exercises and case-based learning, students will explore a range of applications, such as strategic planning, supply chain, marketing, and finance. The course also emphasizes hands-on experience with modern optimization software and programming tools to develop real-world decision-support models.

Kursets innhold

• The concept of a mathematical programming model
• Linear programming models
• Multi-period planning models
• Integer and mixed-integer models
• Good and bad formulations
• Multi-objective optimization
• Accounting for uncertainty
• Heuristics
• Practical aspects of optimization