Assistant Professors

She graduated with honors in Management Engineering at the University of Calabria. In 2002 she obtained a Master’s degree in Economics and Management of Health Care Services at La Sapienza University, Rome (Italy). In 2005 she received the title Doctor of Research in Operations Research at the University of Calabria with a thesis on Nonlinear Stochastic Mixed Integer Programming. Author of more than 30 publications on international journals, and of two book chapters. Winner of a Best Paper Prize for the journal IMA Journal of Management Mathematics. Member of the editorial board of two journals and referee for many top journals.

M.E. Bruni, P. Beraldi, D. Conforti, A stochastic programming approach for operating theatre scheduling under uncertainty, IMA Journal on Management Mathematics, 26, (2015), 99–119
M.E. Bruni, F.Guerriero, P. Beraldi, Designing robust routes for demand-responsive transport systems, Transportation Research Part E, 70(1), (2014) 1-16
M.E. Bruni, P. Beraldi, F. Guerriero, E. Pinto, A heuristic approach for resource con-strained pro ect scheduling with uncertain activity durations, Computers and Opera-tions Research. 38(9), (2011) 1305-1318
Aringhieri R., Bruni M.E., Khodarapasti S., Van essen J.T., Emergency medical services and beyond: addressing new challenges through a wide literature review, Computers and Operations Research, 78, (2017), 349 - 368.

• Stochastic Integer Programming 
The research activity carried out in this fi eld concerns the study of the structural properties and the design of innovative methods for solving stochastic programming problems both with recourse and under probabilistic constraints. 

• Routing problems under uncertainty
New models and methods are proposed for routing problems under different sources of uncertainty.

• Health care management
Optimization Models and Methods for relevant strategical, tactical and operational problems in Healthcare.

• Model for effi ciency evaluation under uncertainty.
Different models, representing an advance with respect to the state of the art have been proposed.

• Project scheduling under uncertainty 
New stochastic and robust models have been proposed, together with tailored solution approaches.

Please contact the Professor by phone or by email or you can stop directly in the office