[{"Course code":"P000148","Version":1,"English name":"Fundamentals of Optimization: An Interdisciplinary and Applied Approach","Higher education credits":4.5,"Syllabus":"FUN S","Valid from":"VT2025","Syllabus approved":"2025-04-11","Level within study regulation":"Third cycle","Grading scale":"Pass \/ Failed","Language":"Swedish","Entry requirements":"Doctoral students that are admitted to SLU or to another University.","Objectives":"On completion of the course, the student will be able to:
\n1\\.- Describe what an optimization problem is and identify its key components (objective function, decision variables, and constraints).
\n2\\.- Classify different types of optimization problems, such as linear vs. nonlinear and single vs. multi-objective.
\n3\\.- Formulate simple optimization problems from real-world scenarios and from their own research projects.
\n4\\.- Use computational tools to apply basic optimization techniques and solve simple problems.
\n5\\.- Interpret the results of optimization models, understanding trade-offs and constraints.","Content":"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.
\nThe course covers:
\n• Fundamental principles of optimization modelling.
\n• Types of optimization problems: linear vs. nonlinear, single vs. multi-objective.
\n• Introduction to common solution methods, including classical algorithms and meta-heuristic approaches.
\n• Hands-on implementation using computational tools and coding.
\n• Interpretation of optimization results and limitations.
\nThe 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.","Examination formats":"1\\.- Approved assignments.\n\n2.- Approved final project. \r\n- If a student has failed an examination, the examiner has the right to issue supplementary assignments. This applies if it is possible and there are grounds to do so.\r\n\r\n- The examiner can provide an adapted assessment to students entitled to study support for students with disabilities following a decision by the university. Examiners may also issue an adapted examination or provide an alternative way for the students to take the exam.\r\n\r\n- If this syllabus is withdrawn, SLU may introduce transitional provisions for examining students admitted based on this syllabus and who have not yet passed the course.\r\n\r\n- For the assessment of an independent project (degree project), the examiner may also allow a student to add supplemental information after the deadline for submission. Read more in the Education Planning and Administration Handbook.\r\n","Organisation":[{"code":"545","Organisation":"Department of Forest Biomaterials and Technology"}],"Other information":"\r\n- The right to participate in teaching and\/or supervision only applies for the course instance the student was admitted to and registered on.\r\n\r\n- If there are special reasons, students are entitled to participate in components with compulsory attendance when the course is given again. Read more in the Education Planning and Administration Handbook.\r\n"}]