Grunderna i Optimering: Ett Tvärvetenskapligt och Tillämpat Tillvägagångssätt
Kursbeskrivning
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.
Optimization is often misunderstood—many think it simply means improving something, but in reality, it follows a structured approach to decision-making based on goals and specifications. At its core, optimization is a mathematical process that involves maximizing or minimizing a function while considering constraints to find the best possible outcome.
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.