Many heuristic algorithms are available to solve VRP problems. This thesis will explore the possibilities of enhancing a recently published heuristic algorithms born from research at GOL and at Fleetmatics (see https://link.springer.com/article/10.1007/s13676-017-0110-y )
Optimization of pattern identification in RNA
Starting from the paper “A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications”, by Marco Pietrosanto, Eugenio Mattei, Manuela Helmer-Citterich,Fabrizio Ferrè, Nucleic Acids Research, 2016 1, doi: 10.1093/nar/gkw750, we wish to explore
OBA – Summer School on Optimization, Big Data and Application
The OBA summer school held in Veroli (FR) ia now closed. It has been a great success, from all point of views: scientific, didactic, social. Lectures have been given by: Saathiya Keerthy (Microsoft Research): Generative Adversarial Networks Chih-Jen Lin (Taiwan University): Optimization and
Improved space trajectories found by an undergraduate student at GOL
An undergraduate student, Tommaso Aldinucci, working for his first level degree thesis in Information Engineering at GOL, found as many as 6 improved trajectories for the Tandem mission test set maintained by ESA. The new improved routes are now available
Multi-modal, multi-objective shortest paths
Developing efficient shortest path algorithm in large urban graphs, with multiple, conflicting, objectives and different modes of transportation. Skills required: C++
Statistics from the optimization point of view
We would like to look inside some classical statistical procedures (e.g., forecasting time series) from an optimization point of view. The aim is to use global optimization techniques to solve optimal estimation problems in statistics
Optimization for molecular clusters
This thesis concerns the developement of specific tools for the optimization of atomic clusters based on the identification of surface atoms and their relocation. No previous knowledge of chemistry is required. The thesis will require python modules to be developed,
a GOL team participates to the Kaggle epileptic seizure prediction competition
A team composed by PhD students at the GOL lab is having quite successful scores at the Kaggle epilectic seizure prediction competition The competition is hard and far from being concluded, but the team is performing really well! Stay tuned…
Machine learning for detecting parasitic operators in Radio Base Stations
Radio Base Stations (RBSs) are among the constitutive bricks of a mobile network, acting both as interfaces with end users and transmissive units. Each RBS belongs to a network operator, who in turn allows other operators to use the infrastructure
A new startup from the GOL lab: Intuendi
A group from our lab started a new company: see their web page at www.intuendi.com