Greener logistics with AI
In this week’s NORA webinar, you will meet Signe Riemer-Sørensen and Camilla Sterud from SINTEF Digital. They will talk about greener logistics using AI.Transportation of goods from A to B is directly linked to CO2 emission and hence efficient logistics will reduce emission. Efficient transportation is a classical problem in optimization theory, but recent advances in machine learning open new possibilities.
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Rather than optimizing on simplified analytical systems, we can use data driven descriptions of the systems. We will demonstrate the idea on a practical example with improved coordination between excavators and dumpers in large road construction projects. In addition, machine learning can potentially improve the internal efficiency of optimization algorithms, in particular for situations where similar optimization tasks are solved on a regular basis. We will illustrate this through a real life example of stacking boxes on pallets.
About Signe Riemer-Sørensen
Signe Riemer-Sørensen, PhD, is a researcher at SINTEF Digital. Her expertise is focused on the development of hybrid machine learning algorithms combining data driven methods and domain knowledge, for use in industrial settings, in particular within the domains of energy, construction and logistics.
About Camilla Sterud
Camilla Sterud, M.Sc., is a researcher at SINTEF Digital. She has a background in cybernetics and autonomous system theory. Her main focus areas are enhancing optimisation algorithms using machine learning, and applying machine learning in industrial settings, especially in the process industry.