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
On the combination of Clustering and Multi-Objective Approaches
This proposal regards two relevant themes of Artificial Intelligence and Optimization Research: clustering and multi-objective optimization. Multi-objective optimization problems have a significant relevance in many applications of various fields, such as engineering, management, statistics, space exploration, etc…On the other side,
Memetic Algorithms for Standard Quadratic Programming Problems
Standard Quadratic Optimization problems are an important family of problems with a large number of applications in finance, decision science, graphs algorithms, etc.For these nonconvex problems, we are interested in finding global optima; however, exact global optimization algorithms hardly scale
Hybrid machine learning / simulation methods
Within a recent industrial collaboration we have been asked to develop a machine learning model for estimation problems in a mechanical device. For the same device, a model-based simulator is also available. In this thesis we would like to explore
Heuristic approaches for airport personnel shift scheduling
While in a recent thesis we considered exact methods for large scale personnel scheduling problems, in this thesis we would like to explore heuristic strategies. This thesis might be adapt also for a Management Engineering student, provided she/he possess some
Hyperparameter optimization in machine learning via black-box global optimization
This topic deals with the application of advanced GO methods to optimally choose hyperparameters in machine learning training. The idea is to use GO methods to find good hyperparameters based on a small set of trials, each consisting in chosing
Advanced Global Optimization algorithms based on Clustering and Random Projections
This topic is related to a recently published paper: F. Schoen and L. Tigli, “Efficient large scale global optimization through clustering-based population methods“, Computers & Operations Research, 127, 2021. We wish to extend those methods to large dimension by suitable
Advanced memetic algorithms for clustering
This topic is related to a paper we recently published on this subject: P. Mansueto and F. Schoen, “Memetic differential evolution methods for clustering problems“, Pattern Recognition, 114, 2021. The idea is to extend those methods and experiment with different