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PFS0175
Operations Research and Analytics in forestry
Purpose: The aim of the course is to introduce and give basic knowledge of optimization and analytics for problems arising in the forest value chain. This include understanding of models and modeling of forest planning problems. Moreover, the course includes basic understanding of important solution methods for linear, nonlinear and integer programming problems. In addition, it provides basic knowledge in how to implement models and methods using modeling languages.
Content: The course have three parts. The first part is a one-week intensive workshop. This includes lectures, educational games, and team assignments. All students participate active onsite in this week. The lectures cover modeling, models, methods for LP, nonlinear and MIP problems, implementation using modeling languages, and description of a number of applications from forestry. The second part is a set of smaller projects and assignment where students work individually or in teams of two. The third part is work on a larger project. A set of alternatives are described which the students can choose among. This also include writing a short report and an oral presentation. The latter will be done during an online web seminar.
Content: The course have three parts. The first part is a one-week intensive workshop. This includes lectures, educational games, and team assignments. All students participate active onsite in this week. The lectures cover modeling, models, methods for LP, nonlinear and MIP problems, implementation using modeling languages, and description of a number of applications from forestry. The second part is a set of smaller projects and assignment where students work individually or in teams of two. The third part is work on a larger project. A set of alternatives are described which the students can choose among. This also include writing a short report and an oral presentation. The latter will be done during an online web seminar.
Syllabus and other information
Syllabus
PFS0175 Operations Research and Analytics in forestry, 4.5 Credits
Subjects
Forest ManagementEducation cycle
Postgraduate levelGrading scale
Pass / Failed
Prior knowledge
Students should be enrolled as PhD-students.Objectives
After completing the course, the students should: • Have basic knowledge to formulate optimization models • Have knowledge of important models for forest applications • Understand basic methodology to solve linear programing (LP) problems • Understand basic methods to solve nonlinear problems • Understand basic methods to some mixed integer programming (MIP) problems • Understand basic heuristic methods for combinatorial optimization and MIP problems • Have basic knowledge in using a modeling language, e.g., AMPL, for model and method development • Have basic understanding to analyze data quality • Have an understanding of important logistic concepts using collaboration and coordinationContent
Purpose: The aim of the course is to introduce and give basic knowledge of optimization and analytics for problems arising in the forest value chain. This include understanding of models and modeling of forest planning problems. Moreover, the course includes basic understanding of important solution methods for linear, nonlinear and integer programming problems. In addition, it provides basic knowledge in how to implement models and methods using modeling languages. Content: The course have three parts. The first part is a one-week intensive workshop. This includes lectures, educational games, and team assignments. All students participate active onsite in this week. The lectures cover modeling, models, methods for LP, nonlinear and MIP problems, implementation using modeling languages, and description of a number of applications from forestry. The second part is a set of smaller projects and assignment where students work individually or in teams of two. The third part is work on a larger project. A set of alternatives are described which the students can choose among. This also include writing a short report and an oral presentation. The latter will be done during an online web seminar.Additional information
The first week of the course is on-campus teaching in Umeå and the second and third week consist of off campus teaching complemented with a few lectures through skype where the assignments and project work is discussed and results are presented.The course can accommodate a maximum of 20 students. Students belonging to the BECFOR research school, and the Swedish University of Agricultural Sciences, in that order, have priority. Apply to the course by sending an email to karin.ohman@slu.se
Responsible department
Department of Forest Resource Management