Parallel machine scheduling under uncertainty

This report investigates a scheduling problem where task duration is uncertain. The duration per task has a lower and upper bound, and is dependent on observed duration of other tasks. This tries to closer model real life. We reduce all possible different outcomes to a few extreme scenarios. The report compares two types of heuristcs: one which...

Optimize the indescribable: A Look at the Unification between Machine Learning and Optimization

Packages to encode Machine Learned models into optimization problems is an underdeveloped area, despite the advantages is could provide. The main draw of implementing Machine Learned models into optimization models, is that it allows the optimizer to better account for the human experience.<br/>Maragno D., Wiberg H. et al. constructed an...

Neural networks for Gamma cameras

In this research the effectiveness of analytical neural networks compared to the maximum likelihood method on the prediction of spatial and DOI positioning of a Gamma detector with a NaI(Tl) scintillator of size 590mm x 470mm x 40mm (x,y,z), with a glass lightguide of size 620mm x 500mm x 4mm and a PMT area of 620mm x 500mm x 40mm with 2-inch...

Robust OCTs: Investigating classification tree robustness

The application of machine learning in daily life requires interpretability and robustness. In this paper we try to make the process of building robust and interpretable decision trees more accessible. We do this by making the fitting of these models cheaper and simpler. We build on previous research and see if changing input data or the fitting...

Machine learning to support cutting plane selection in two-stage robust optimization problems using a column-and-constraint-generation algorithm

The field of robust optimization deals with problems where uncertainty influences the optimal decision. Some of these problems can be formulated in a ‘two-stage’ formulation, such as the location transportation problem. To solve such a problem, a column-and-constraint-generation algorithm has been introduced in which constraints are iteratively...

Optimal here and now decisions of multi stage robust optimisation: Optimale hier en nu beslissingen in multi stadia robuuste optimalisatie

Robust optimisation is shown to be extremely important in a wide range of applications including real life. Many research projects are dedicated to this relatively young and active research field and show the significant value of robust optimisation. Since many researchers have developed complex methods dedicated to robust optimisation, the aim...