RICERCA ITALIANA     

Programmi di ricerca simili:

• 1 - Ottimizzazione Nonlineare, Disequazioni Variazionali, e Problemi di Equilibrio.
• 2 - Modelli e algoritmi di ottimizzazione per il progetto di reti wireless
• 3 - Problemi variazionali con scale multiple
• 4 - Problemi di routing e packing nell'ottimizzazione dei sistemi di trasporto
• 5 - Metodi numerici e software matematico per le applicazioni
• 6 - Modelli ed applicazioni della monotonia generalizzata
• 7 - Problemi Inversi in Medicina ed Astronomia
• 8 - Modelli ed algoritmi per l'ottimizzazione robusta delle reti
• 9 - Metodi numerici avanzati per equazioni alle derivate parziali di interesse applicativo
• 10 - Sviluppo ed analisi di modelli matematici e di metodi numerici per equazioni alle derivate parziali per le applicazioni a problemi ambientali ed industriali

Classificazione scientifico-disciplinare

• Area scientifico disciplinare: Scienze matematiche e informatiche
  • ANALISI NUMERICA
  • RICERCA OPERATIVA

Classificazione brevettuale

• PHYSICS
  • COMPUTING; CALCULATING; COUNTING (score computers for games A63; combinations of writing applicances with computing devices B43K29/08)
    • COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS [N0004]
  • EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS (devices for psychotechnics or for testing reaction times A61B5/16; games, sports, amusements A63; projectors, projector screens G03B)

Classificazione geografica

• Regione: Lazio

Bibliografia

B. Addis, F. Schoen, Docking of atomic clusters through nonlinear optimization, J. of Global Opt., 30, 1-21, 2004

C. Audet, Convergence Results for Pattern Search Algorithms are Tight, Opt. and Engineering, 5, 101-122, 2004

C. Audet, J.E. Dennis, A Pattern Search Filter Method for Nonlinear Programming without Derivatives, SIAM J. on Opt., 14, 980-1010, 2004

T. Basar, G.J. Olsder, Dynamic noncooperative game theory. SIAM Classic in Appl. Math., 1999

L. Biegler, T. Coleman, A. Conn, F. Santosa eds., Large scale optimization with applications, Part I-II-III, IMA Vol. in Math. and its Appl., Springer, 1997

D. P. Bertsekas, Nonlinear Programming, Athena, 1999

D. P. Bertsekas, Convex Analysis and Optimization, Athena, 2003

S. Boyd, L. Vandenberghe Convex Optimization, Cambridge Univ. Press, 2004

S. Cafieri, M. D’Apuzzo, V. De Simone, D. di Serafino, On the iterative solution of KKT systems in potential reduction software for large scale quadratic programming. Comp. Opt. and Appl., to appear 2005

E.F. Campana, G. Liuzzi, S. Lucidi, D. Peri, V. Piccialli, A. Pinto. New global optimization methods for ship design problems. Tech. Rep. INSEAN 2005-1, 2005

E. Cavazzuti, M. Pappalardo, M. Passacantando, Nash equilibria, varational inequalities and dynamical systems, J. Opt. Theory and Appl., 114, 2002

A. R. Conn, N. I. M. Gould, P. L. Toint, Trust-region methods, MPS-SIAM Series on Opt., 2000

A.R. Conn, K. Scheinberg, Ph.L. Toint. Recent progress in unconstrained nonlinear without derivatives. Math. Progr.79, 397-414, 1997

E. Chiricozzi, G. Liuzzi, S. Lucidi, G. Placidi, A. Sotgiu, M. Villani, Cylindrical and elliptical geometry for the design and optimization of small dedicated magnets for magnetic resonance imaging, Biomedical Eng., 2, 129-135, 2001

L. Cirio, S. Lucidi, G. Placidi, A. Sotgiu, Automatic optimization strategy for the design of circular multipolar magnets, J. of Physics D: Appl. Physics, 34, 313-318, 2001

M. D'Apuzzo, M. Marino. Parallel Computational Issues of an Interior Point Method for Solving Large Bound-Constrained Quadratic Programming Problems. Parallel Comp. 29, 467-483, 2003

M. D'Apuzzo, M. Marino, A. Migdalas, P.M. Pardalos, G. Toraldo. Parallel Computing in Global Optimization. In Handbook of Parallel Comp. and Stat., Kontoghiorghes ed., Dekker, 2004

T. De Luca, F. Facchinei, C. Kanzow, A theoretical and numerical comparison of some semismooth algorithms for complementarity problems, Comp. Opt. and App., 16, 173-205, 2000

R. De Leone, A. Murli, P. Pardalos, G. Toraldo eds., High Performance Algorithms and Software in Nonlinear Opt., Kluwer, 1998

G. Di Pillo, F. Giannessi eds., Nonlinear optimization and related topics, Kluwer, 2000

G. Di Pillo, S. Lucidi, L. Palagi, A shifted-barrier primal-dual algorithm model for linearly constrained optimization problems, Comp. Opt. and App., 12, 1998

G. Di Pillo, S. Lucidi, L. Palagi, A superlinearly convergent primal-dual algorithm for constrained optimization problems with bounded variables, Opt. Meth. and Soft., 1, 1-25, 2000

G. Di Pillo, A. Murli eds., High performance algorithms and software for Nonlinear Opt., Kluwer, 2003.

G. Di Pillo, L. Palagi, Nonlinear Programming. Handbook of Appl. Opt., Pardalos, Resende eds., Oxford Univ. Press, 2002

J.P.K. Doye, R.H. Leary, M. Locatelli and F. Schoen, Global Optimization of Morse Clusters by Potential Energy Transformations, INFORMS J. on Comp., 16, 371-379, 2004

F. Facchinei, H. Jiang, L. Qi, A smoothing method for mathematical programs with equilibrium constraint, Math. Progr., 85, 107-134, 1999

F. Facchinei, J. Pang, Finite-Dimensional Variational Inequalities and Complementarity Problems, Vol. I-II, Springer, 2003

C.A. Floudas, P.M. Pardalos eds. Optimization in computational chemistry and molecular biology, local and global approaches, Kluwer, 2000

A. Fuduli, M. Gaudioso, G. Giallombardo, Minimizing nonconvex nonsmooth functions via cutting planes and proximity control. SIAM J. on Opt., 14, 743-756, 2004

M. Gaudioso, Nonsmooth optimization, in Pardalos, Resende eds., Handbook of App. Opt., Oxford Univ. Press, 2002

F. Giannessi, A. Maugeri, P. Pardalos, Equilibrium Problems: Nonsmooth Optimization and Variational Inequality Models, Kluwer, 2001

M. Good, J.P. Goux, J. Nocedal. iNEOS: an interactive environment for Nonlinear Optimization, Appl. Num. Math., 40, 49-58, 2002

N. Gould, S. Leyffer, An introduction to algorithms for nonlinear optimization. In Blowey, Craig, Shardlow eds., Frontiers in Num. Anal., 109-197. Springer, 2003

N. Gould, S. Lucidi, M. Roma, P. L. Toint, Solving the trust-region subproblem using the Lanczos method. SIAM J. On Opt., 9, 504-525, 1999

N. Gould, S. Lucidi, M. Roma, P. L. Toint, Exploiting negative curvature direction in linesearch methods for unconstrained optimisation, Opt. Meth. and Soft., 14, 75-98, 2000

N. Gould, Ph. L. Toint, How Mature is Nonlinear Optimization? In App. Math. entering the 21st cent., Hill, Moore eds, SIAM, 141-161, 2004

L. Grippo, Convergent On-Line Algorithms for Supervised Learning in Neural Networks", IEEE Trans. on Neural Net., 6, 1284-1299, 2000

L. Grippo, Unconstrained minimization methods for neural network training, in Floudas, Pardalos eds., Encycl. of Optimization, Kluwer, 2001

L. Grippo, M. Sciandrone, Globally convergent block-coordinate techniques for unconstrained optimization, Opt. Meth. and Soft., 10, 587-637, 1999

L. Grippo, M. Sciandrone, Metodi di Ottimizzazione per le Reti Neurali, Agnetis, Di Pillo eds.,Pitagora, 2002

T.G. Kolda, R.M. Lewis, V. Torczon, Optimization by direct search: new perspectives on some classical and modern methods, SIAM Review, 45, 385-482, 2003

R.M. Lewis, V. Torczon, A globally convergent augmented Lagrangian Pattern search algorithm for optimization with general constraints and simple bounds, SIAM J. on Opt., 12, 1075-1089, 2002

G.Liuzzi, S.Lucidi, V.Piccialli, A.Sotgiu, A Magnetic Resonance device designed
via global optimization techniques, Math. Progr., 101, 339-364, 2004

M. Locatelli, F. Schoen, Efficient Algorithms for Large Scale Global Optimization: Lennard-Jones Clusters, Comp. Opt. and App., 26, 173-190, 2003

S. Lucidi, L. Palagi, M. Roma, On some properties of quadratic programs with a convex quadratic constraint, SIAM J. Opt., 8, 105-122, 1998

S. Lucidi, F. Rochetich, M. Roma, Curvilinear stabilization techniques for truncated Newton methods in large scale unconstrained optimization, SIAM J. Opt., 8, 916-939, 1998

S. Lucidi, M. Sciandrone, On the Global Convergence of Derivative Free Methods for Unconstrained Optimization, SIAM J. Opt., 13, 97-116, 2002

S. Lucidi, M. Sciandrone, P. Tseng, Objective-derivative-free methods for constrained optimization, Math. Progr., 92, 37-59, 2002

T.S. Munson, F. Facchinei, M.C. Ferris, A. Fisher, C. Kanzow, The semismooth algorithm for large scale complementarity problems. INFORMS J. on Comp., 13, 294-311, 2001

J. Nocedal, S. J. Wright, Numerical Optimization, Springer, 1999

D.P. O'Leary. Symbiosis between Linear Algebra and Optimization, J. of Comp. and Appl. Math. 123, 447-465, 2000

L. Palagi, Large scale trust region problems, in Floudas, Pardalos eds., Encycl. of Optimization, Kluwer, 2001

L. Palagi, M. Sciandrone, On the convergence of a modified version of the SVMlight algorithm, Opt. Meth. and Soft., 20, 315-332, 2005

J. Pang, M. Fukushima, Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games, Comput. Manag. Science, 1, 21-56, 2005

M. Pappalardo, M. Passacantando, Stability for equilibrium problems: from
variational inequalities to dynamical systems, J. of Opt. Theory and App., 113, 2002

M.J.D. Powell. The NEWUOA software for unconstrained optimization without derivatives. Tech. Rep. NA2004/08, DAMTP, Univ. of Cambridge, 2004

M. Roma, Large scale unconstrained optimization, in Floudas, Pardalos eds., Encycl. of Optimization, Kluwer, 2001

Parole Chiave

OTTIMIZZAZIONE NONLINEARE; OTTIMIZZAZIONE GLOBALE; DISEQUAZIONI VARIAZIONALI E PROBLEMI DI EQUILIBRIO; RETI NEURALI E MACCHINE A VETTORI DI SUPPORTO; METODI SENZA DERIVATE; PROGRAMMAZIONE NONLINEARE A GRANDE DIMENSIONE; AMBIENTI COMPUTAZIONALI PER L'OTTIMIZZAZIONE NONLINEARE