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Global Optimization Laboratory "Gerardo Poggiali"

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Theses: discussed

An efficient implementation of the FALKON algorithm for Large Scale kernel methods and an extension to the semi-supervised scenario

This thesis is devoted to the re-implementation  of a very large scale kernel ridge regression software tool and to its extension to the semi-supervised case Started: November 2018 Candidate: Enrico Civitelli Graduated: April 2019

Fabio Schoen April 11, 2019 Theses: discussed Read more

Optimization Methods and Models for replenishment with constraints

Managing inventories when the demand is uncertain is a challenging problem involving forecasting, modeling and optimization. This thesis is devoted to the extension of classical models, like the newsvendor, to multiple products, integer order quantities, logical constraints, assortment, and other

Fabio Schoen April 11, 2019 Theses: discussed Read more

Discrete optimization on a quantum computer

This thesis is devoted to experiment numerical optimization techniques on the D-Wave quantum computer We will simulate some combinatorial optimization problems and try to find innovative problem mapping in order to fully exploit the capacity of the quantum annealing machine.

Fabio Schoen October 29, 2018April 11, 2019 Theses: discussed Read more

Optimal decision trees

Based on a paper by D. Bertsimas, we experimented on discrete optimization algorithms for the optimal training of a decision tree. Assigned: July 2018, discussed December 2018 Student: Francesca Del Lungo  

Fabio Schoen September 21, 2018December 31, 2018 Theses: discussed Read more

Scheduling staff in an hospital ward

This thesis dealt with developing an optimization algorithm for health care staff planning, based on a real ward requirements. Required skills: linear programming, possibly python, Java or C++ Student: Giulia Forasassi (based on an initial model prepared by Ayca Sarikaya,

Fabio Schoen September 21, 2018September 29, 2021 Theses: discussed Read more

Predicting drug consumption

Hospital wards are faced with day-to-day necessity to accurately forecast the consumption of drugs in order not to under stock nor to have too large inventories. This thesis explores the capabilities of some time series and some machine learning tools

Fabio Schoen February 9, 2018February 21, 2018 Theses: discussed Read more

Predicting the results of soccer matches via machine learning

How to use information collected during past matches in order to be able to predict the final result of a match? This thesis explores machine learning methods and features extraction towards the goal of being able to anticipate the final result.  

Fabio Schoen February 5, 2018April 29, 2019 Theses: discussed Read more

Methods for epileptic seizures prediction based on features extraction from time series

Despite the progress of medicine in recent decades, epilepsy is a disease whose knowledge is still limited. About one third of patients with this disease continue to present crises despite pharmacological treatments, surgical interventions, and the medical assistance. The most

Fabio Schoen February 2, 2018February 21, 2018 Theses: discussed Read more

Clustering and feature selection methods for interplanetary space trajectory optimization

by Cosimo Casini Planning the optimal trajectory of an interplanetary space mission allows to save large amounts of fuel and time. Such a task can be modelled as a constrained global optimization problem. However, solving the resulting model is extremely

Fabio Schoen May 8, 2017February 21, 2018 Theses: discussed Read more

Data mining on students careers

We have got some data on students’ careers in the Engineerring school. We would like to apply some machine learning technique to find useful information inside. E.g., which part of the pre-admission test is correlated with the career? How to

Fabio Schoen April 4, 2017February 2, 2018 Theses: discussed Read more
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Recent News from the Lab

  • 2022 Summer – Two International Events Organized by GOL

  • Optimization Models

  • Master Thesis Proposals / Information Engineering & Artificial Intelligence, Management Engineering et al.

  • Open Day Engineering School

  • Introduction to Operations Research

Theses (proposals)

  • Machine Learning & Optimization for Cancer Research

  • Global Optimization methods based on Clustering, Populations, Random Projections

  • Experiments in quantum computing and optimization

  • Algorithms for Sparse Optimization

  • On the combination of Clustering and Multi-Objective Approaches

COVID-19 emergency

  • Crowded Zone – a Web App for social-distancing

  • Personnel scheduling in health care

  • Covering and localization problems

  • folding@home – GPU sharing initiative to fight the virus

  • Shift planning for emergency

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