An e-book on modeling techniques for Operations Research. Version 0.99, August 2023 A new book on the art of modeling optimization problems. This text is used in the “Optimization and Data Science for Management” course, Master degree in Management Engineering.
Machine Learning & Optimization for Cancer Research
This post contains several thesis proposals, all connected with an ambitious research project we have recently been assigned through a 5-year grant obtained from AIRC, the Italian Association for Cancer Research. Possible thesis topics include: How to deal with missing
Global Optimization methods based on Clustering, Populations, Random Projections
We recently published a paper on GO methods based on Differential Evolution. We would like to perform more experiments and possibly extend the methods in several directions: experimenting with different dimensionality reduction techniques, apply to a large set of test
Experiments in quantum computing and optimization
In this thesis we would like to make a few experiments on available quantum computers. We might wish to get a try to qiskit, an open source SDK for working with quantum computers. The objective will be that of implementing
Exact optimization models for airport personnel scheduling
Student: Giulia Pellegrini (December 2021) In this thesis we explored the power and the limits of exact optimization models for large personnel scheduling problems. Scheduling at airports has the additional complication, with respect to other personnel scheduling problems, that shifts
Master Thesis Proposals / Information Engineering & Artificial Intelligence, Management Engineering et al.
We have just update a list of available topics for a Master Degree Thesis. Most of the proposals are for a master degree in Computer Science Engineering, Artificial Intelligence, Mathematics. A few are suitable for management Engineering too. Many more
Machine learning techniques for attributes extraction in apparel images
Student: Francesca Del Lungo, 2021. This thesis was developed during a stage at Intuendi srl, Florence Clothing classification algorithms often face several challenges. First of all,clothing items often have many variations in style, texture and cutting. Second, clothing attributes are
Optimization methods for risk scores learning
Student: Luca Ciabini, 2021 Risk scores are classi fication models that predict the risk of an event using a value de fined by the sum of a few integers. They are particularly interesting as they are easy to learn, to use, to
Machine learning models for sports betting on professional Tennis
Student: Lorenzo Amato, graduated: 2021
Image Captioning road scenes: a multitask deep learning approach
Student: Niccolò Bellaccini, 2020. Thesis developed partially during a stage at Verizon Connect Research Italy, Florence Image Captioning tackles the problem of generating textual descriptionsfrom pictures, and thus lies in the intersection of the Computer Vision (CV)and Natural Language Processing