PhD course: Fundamentals of Optimization - An Interdisciplinary and Applied Approach
Many real-world challenges are optimization problems—situations where the goal is to make the best possible decision while managing trade-offs and constraints. Optimization is in fact a structured, mathematical approach to decision-making based on defined goals and specific limitations.
Start date: 28 January 2026 00:00
End date: 27 March 2026 00:00
Organiser: Department of Forest Biomaterials and Technology
Location: Umeå
Last day of registration: 4 January 2026
How can a forestry manager allocate resources in the best possible way to sustain forest health and yield? How can an economist determine the most effective way to distribute limited resources to meet market demand? How can an engineer develop a system that achieves the best trade-off between cost, efficiency, and safety? How can a biologist structure an experiment to get the most valuable results while considering time and budget constraints?
All of these are optimization problems—challenges where the goal is to make the best possible decision while balancing trade-offs and limitations.
This course demystifies optimization, making it accessible to Ph.D. students across multiple disciplines, including forestry, agriculture, economics, engineering, biology and beyond. Students will learn how to correctly define and approach optimization problems, even without a strong mathematical background.
Through practical examples and hands-on techniques, students will explore key concepts such as linear and nonlinear programming, classical optimization algorithms, multi-objective optimization and metaheuristic approaches. These methods can enhance efficiency, resource allocation, and support better decision-making across various fields.
By the end of the course, students will have a solid understanding of the fundamentals of optimization and gain basic tools to approach and apply key techniques in their research and professional work.
Read more on the course on the LADOK page.
Programs
The course introduces the fundamental concepts of optimization, focusing on real-world applications in various disciplines such as forestry, economics, engineering, biology and beyond. Students will learn how to formulate, analyse, and solve basic optimization problems while considering constraints, trade-offs, and decision-making processes.
The course covers:
• Fundamental principles of optimization modelling.
• Types of optimization problems: linear vs. nonlinear, single vs. multi-objective.
• Introduction to common solution methods, including classical algorithms and meta-heuristic approaches.
• Hands-on implementation using computational tools and coding.
• Interpretation of optimization results and limitations.
The course includes a mix of lectures, practical coding sessions with real-world examples from different disciplines, fostering a broader interdisciplinary perspective on optimization. Alongside lectures, students will complete a series of assignments that gradually build their skills, from connecting optimization to their own field, to solving practical problems, and exploring trade-offs in decision making. The course concludes with a final project in which each student formulates and analyses an optimization problem relevant to their research.