WISO001045 AI, Machine Learning, and Optimization for Wood Transport and Forest Logistics

Type
Seminar
Semester hours
1
Lecturer (assistant)
Kogler, Christoph , Acuna, Mauricio
Organisation
Production and Logistics
Offered in
Wintersemester 2025/26
Languages of instruction
Englisch
Content

This course, taught by internationally leading expert Prof. Mauricio Acuna from the Natural Resources Institute Finland (LUKE), who has been specially invited to BOKU for this purpose, offers a unique opportunity for students to learn from one of the most distinguished researchers in the field of forest digitalization and logistics.At its core, the course focuses on the application of Artificial Intelligence (AI), Machine Learning, and advanced optimization techniques to address real-world challenges in timber transport, machine coordination, and biomass logistics.
The research-led seminar is highly exploratory in nature: participants are encouraged to develop, prototype, and critically evaluate innovative digital solutions. The course combines practical exercises, case studies, and project-based work with interdisciplinary thinking to advance efficiency, sustainability, and resilience in forest-based value chains.
The course is particularly well-suited for doctoral and master’s students in forestry, wood technology and management, and related disciplines with a strong interest in digitalization and sustainability. In addition, highly motivated bachelor students, students from other universities, and guest researchers are warmly welcome to participate in this unique learning opportunity – please reach out in advance via email to christoph.kogler@boku.ac.at.
Previous knowledge expected

Participants are expected to have basic knowledge in forestry, logistics, or data analysis, as well as a keen interest in digital technologies and sustainable value chains.
Objective (expected results of study and acquired competences)

1.Understand the role of AI, machine learning, and optimization in modern wood transport, forest logistics, and biomass supply chains.
2.Collect, process, and analyze forestry logistics data from various sources (e.g., GNSS, telematics, UAVs, and sensor networks).
3.Apply machine learning techniques (e.g., predictive modeling, anomaly detection, deep learning) to solve real-world problems in forest transport operations.
4.Design and implement optimization models for routing, scheduling, and resource allocation in wood supply chains, balancing multiple objectives (e.g., cost, time, emissions).
5.Develop and evaluate AI-driven decision-support systems for dynamic forest logistics and supply chain management.
6.Critically assess emerging technologies such as blockchain, IoT, and real-time AI for enhancing transparency, traceability, and efficiency in forest logistics.
7.Formulate practical solutions for sustainable and smart forest logistics by integrating AI, optimization, and digital tools.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.