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Fasano Giovanni M. Eng, Ph.D. (Operations Research)

Department of  Computer and Systems Science 'A. Ruberti'
"Sapienza" University of Rome 
Via Ariosto  25, 00185
Rome, Italy
room:  A115

Phone: +39 06 77274 084
Fax:     +39 06 77274 074

MAIL  fasano(at)dis(dot)uniroma1(dot)it   

Curriculum Vitae et Studiorum (italian)

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General Research Interests: Unconstrained Optimization, Nonlinear Least Squares, Global Optimization, Neural Networks.

Working Groups:

Actual Interests: Conjugate Gradient Schemes, Iterative Methods for Indefinite Linear Systems, Global Optimization, Multidisciplinary Optimization.

Papers on International Journals:

  1. Globally convergent modifications of Particle Swarm Optimization for Unconstrained Optimization, E. F.Campana, G.Fasano,  D.Peri, book chapter in  Particle Swarm Optimization: Theory, Techniques and Applications,  Nova Publishers, Series: Advances in Engineering Mechanics (Series Editor: Dr. Bohua Sun), ISBN: 978-1-61668-527-0, 2010.
  1. Dynamic system analysis for the selection of parameters and initial population, in Particle Swarm Optimization, E. F.Campana, G.Fasano,  A.Pinto, published online on Journal of Global Optimization, DOI: 10.1007/s10898-009-9493-0, 2009.

  2. A nonmonotone truncated Newton-Krylov method exploiting negative curvature directions, for large scale unconstrained optimization, G.Fasano, S.Lucidi,  Optimization Letters, Vol. 3, no. 4, pp. 521 - 535, DOI10.1007/s11590-009-0132-y, 2009.

  3. A Modified Galam's Model for Word-of-Mouth  Information Exchange, A.Ellero, G.Fasano, A.Sorato, Physica A: Statistical Mechanics and its Applications, Vol. 388, no. 18, pp. 3901-3910, DOI 10.1016/j.physa.2009.06.002, 2009.

  4. On the Geometry Phase in Model-Based Algorithms for Derivative-Free Optimization, G. Fasano, J. L. Morales, J. Nocedal, Optimization Methods and Software, Vol. 24, n. 1, pp. 145 - 154, 2009.

  5. Iterative Computation of Negative Curvature Directions in Large Scale Optimization,  G.Fasano, M.Roma, Computational Optimization and Applications, vol. 38, n. 1, pp. 81-104, 2007. 

  6. A Truncated Nonmonotone Gauss-Newton  Method for Large-Scale Nonlinear Least-Squares Problems,  G.Fasano, F.Lampariello,M.Sciandrone,  Computational Optimization and Applications, Vol. 34, n. 3, pp. 343-358, 2006.

  7. Lanczos-Conjugate Gradient method and pseudoinverse computation, on indefinite and singular systems, G.Fasano, Journal of Optimization Theory and Applications, vol. 132, n. 2, pp. 267-285, 2007.
  1. Panar-Conjugate Gradient algorithm for Large Scale Unconstrained Optimization, Part I: Theory, G.Fasano,  Journal of Optimization Theory and Applications, vol. 125, n. 3, pp. 523-541, 2005.
  1. Planar-Conjugate Gradient algorithm for Large Scale Unconstrained Optimization, Part 2: Application, G.Fasano,  Journal of Optimization Theory and Applications, vol. 125, n. 3, pp. 543-558, 2005.
  1. Conjugate Gradient (CG)-type Method for the Solution of Newton's equation within  Optimization Frameworks, G.Fasano,  Optimization Methods and Software, vol. 19, No. 3-4, pp. 267-290, 2004.

Papers under Peer-Revision:   

  1. Penalty Function approaches for Ship Multidisciplinary Design Optimization (MDO), E.F.Campana, G.Fasano, D.Peri, submitted to European Journal of Industrial Engineering, 2009.
  2. Preconditioning Newton--Krylov Methods in Non-Convex Large Scale Optimization, G.Fasano, M.Roma, submitted to Computational Optimization and Applications, 2009.
  3. Methods for large scale unconstrained optimization, G.Fasano, submitted as the Section 1.2.1.8 for Wiley Encyclopedia of Operations Research and Management Science, Sherry Wasserman Editorial Assistant, John Wiley & Sons, Inc., NJ, 2010.

Other Peer-Reviewed Papers:

  1. Nonlinear Programming Approaches in the Multidisciplinary Design Optimization of a Sailing Yacht Keel Fin, E.F.Campana, G.Fasano, D.Peri, A.Pinto, 9th International Conference on Numerical Ship Hydrodynamics, Ann  Arbor, Michigan, August 5-8, 2007 (refereed volume).
  2. Particle Swarm Optimization: efficient globally convergent modifications, E. F.Campana, G.Fasano, D.Peri,  A.Pinto, III European Conference On Computational Mechanics - Solids, Structures and Coupled Problems in Engineering, Lisbon 05-09/06/2006 (refereed volume).
  3. Dynamic system analysis and initial particles position in Particle Swarm Optimization, E.F.Campana, G.Fasano, A.Pinto, IEEE Swarm Intelligence Symposium 2006, Indianapolis 12-14/05/2006 (refereed volume).
  4. Issues on Nonlinear Programming for Multidisciplinary Design Optimization (MDO) in Ship Design Framework, E.F.Campana, G.Fasano, D.Peri, 8th Numerical Towing Tank Symposium (NuTTS '05), Varna, Bulgaria 2-4 October 2005  (invited lecture on conference volume).
  5. Planar-CG methods and Matrix Tridiagonalization in Large scale Unconstrained Optimization, G.Fasano,  in  High Performance Algorithms and Software for Nonlinear Optimization, G. Di Pillo and A. Murli, Eds., Kluwer Academic Publishers, pp. 243-263, 2003  (refereed volume).
  6. Use of Conjugate Directions inside Newton-type Algorithms for Large Scale Unconstrained Optimization,G.Fasano, PhD final dissertation in Operations Research, XIII course.

Other Papers:

Teaching & Course Materials (Italian):

Modelli di Programmazione
Matematica

(Prof. Luigi Grippo)

 A.A. 2006/2007  (esercitazioni07.pdf ). Il corso di esercitazioni è corredato del materiale integrativo (NEOS.zip , amplplus.pdf , AmplMan2.pdf):  modalità prova esercitazioni.
A.A. 2005/2006  (esercitazioni06.pdf ). Il corso di esercitazioni è corredato del materiale integrativo (NEOS.zip , amplplus.pdf , AmplMan2.pdf):  modalità prova esercitazioni. 
A.A. 2004/2005  (esercitazioni05.pdf). Il corso di esercitazioni è corredato del materiale integrativo (NEOS.zip , amplplus.pdf , AmplMan2.pdf , Allegato_1.pdf , Allegato_2.pdf) e prevede il superamento di una prova con le seguenti modalità: modalità prova esercitazioni.
A.A. 2003/2004 (Corso 2004)  (esercitazioni04.pdf). Il corso di esercitazioni è corredato del materiale integrativo (Allegato_1.pdf , Allegato_2.pdf , amplplus.pdf , AmplMan2.pdf)  e prevede il superamento di una prova con le seguenti modalità:  modalità prova esercitazioni. 
A.A. 2003/2004 (Corso 2003)  (esercitazioni03.pdf). Il corso di esercitazioni è corredato del materiale integrativo (Allegato_1.pdf , Allegato_2.pdf , amplplus.pdf , AmplMan2.pdf)  e prevede il superamento di una prova con le seguenti modalità:  modalità prova esercitazioni.

 

Sistemi di Servizio
e Simulazione

(Prof. Massimo Roma)


 A.A. 2004-2005  (Ese_26_11_04.zip , Ese_03_12_04.zip), materiale integrativo relativo all'uso del simulatore Arena della Rockwell Software Inc.
A.A. 2005-2006 (Eserc_Arena_A.A.2005), materiale integrativo relativo all'uso del simulatore Arena della Rockwell Software Inc.

 

Ricerca Operativa

(Prof. Luigi Grippo)

 

 A.A. 2002-2003  (esercitazioni02.ps  oppure  esercitazioni02.pdf , amplplus.pdf , AmplMan2.pdf).

 

Dottorato In Ingegneria
dei Sistemi

 

 A.A. 2001-2002  Note di Ottimizzazione Vincolata su Insiemi Convessi , G.Fasano.
A.A. 2003-2004  Cenni sulle Reti Neurali e sui Metodi di Ottimizzazione per le Reti Neurali , G.Fasano
A.A. 2009-2010  Cenni sui Metodi di Ottimizzazione Vincolata , G.Fasano

Here you can find some links to relevant Optimization URLs:

           AMPL Student Edition
           Society for Industrial and Applied Mathematics
           American Mathematical Society
           Northwestern University, Dept. of Mathematics
           INFORMS

FD    NEOS  ,  Try AMPL  ,  Guide to Available Mathematical Software

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