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Continuous Optimization

Research lines:

  • Nonlinear Programming
  • Derivative Free Methods
  • Global Optimization
  • Semidefinite Programming
  • Variational Inequalities
  • Game Engineering
  • Neural Networks and Support Vector Machines
  • Engineering Design Optimization
  • Resource allocation in communication networks

Gianni Di Pillo (leader), Francisco Facchinei, Luigi Grippo, Stefano Lucidi, Laura Palagi, Massimo Roma.

PhD Students:
Stefania De Angelis, Marianna De Santis, Andrea  Ianni, Lorenzo Lampariello, Vittorio La Torre, Mauro Piacentini, Simone Sagratella, Serena Teobaldo.

Post Docs:
Francesco Rinaldi.

Research  in continuous optimization has been active DIS since its foundation.  
Early research was essentially devoted to the theory of exact penalization and to the development of algorithms for the solution of  constrained  nonlinear  programming problems through unconstrained techniques.  Significant early contributions were also given in the field of  unconstrained optimization, with the introduction of  non monotone line searches, non monotone globalization strategies and convergent derivative-free line search techniques.
The Continuous Optimization group later expanded into an active and highly valued optimization research team with a wide range of interests. 
The following areas are object of current  research.
- Exact penalty and augmented Lagrangian methods, still constituting the founding block of many optimization methods and a springboard for many of the studies of the group.
- Non-monotone methods, decomposition techniques and preconditioning  methods for the solution of difficult large-scale nonlinear optimization problems and nonlinear equations.
- Preconditioning Newton-Krylov methods in nonconvex large scale optimization, which is an important tool for efficiently solving large difficult problems.
- Derivative-free algorithms, of special interest in many engineering applications where even the calculation of function values is problematic and very time-consuming.
- Global optimization, which is an essential tool for solving problems  where local non-global solutions may be meaningless.
- Semidefinite programming, that plays an essential role in the development of efficient algorithms for solving relaxations of non-convex and integer problems.
- Finite dimensional variational inequalities and complementarity problems, which often arise in modelling a wide array of real-world problems where competition is involved.
- Generalized Nash equilibrium problems, which are emerging as a winning way of looking at several classical and non-classical engineering problems.
-Training methods for neural networks and support vector machines, for constructing  surrogate models of   complex systems from sparse data through learning techniques.
-Mixed Integer Nonlinear Programming (MINLP) problems that combine combinatorial aspects with nonlinearities. 
The Continuous Optimization group interacts intensively with many other research groups, both in the academic and industrial world, in an ongoing  cross-fertilization process. This process led to several innovative applications in such different fields  as:
- design of electro-mechanic devices; 
- development of  electromagnetic diagnostic equipments;
- power allocation in TLC;
- shape optimization in ship design;
- multiobjective optimization of nanoelectronic devices.



Nonlinear Optimization, Variational Inequalities and Equilibrium Problems
September 2008 - September 2010  -   MIUR PRIN 

MODERN: MOdeling and Design of Reliable Nanoelectronics devices

March 2009-February 2012 ENIAC European Nanoelectronics Initiative Advisory Council 

MANON: Methods for Advanced multi-objective optimization of complex NANoscale circuits
April 2010 - March 2012  -  UE  FP7/PEOPLE

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