MASSIMO ROMA
A SELECTION OF PUBBLICATIONS
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- Al-Baali M., Caliciotti A., Fasano G., Roma M., (2020).A Class of Approximate Inverse Preconditioners Based on Krylov-Subspace Methods for Large-Scale Nonconvex Optimization, SIAM Journal on Optimization. Vol. 30, No.3, pag. 1954-1979. DOI:10.1137/19M1256907
- De Leone R., Fasano G., Roma M., Sergeyev Y.D. , (2020).Iterative Grossone-Based Computation of Negative Curvature Directions in Large-Scale Optimization. Journal of Optimization Theory and Applications. DOI:10.1007/s10957-020-01717-7
- Di Pillo G., Fabiano M., Lucidi S., Roma M., (2020). Cruise itineraries optimal scheduling. Optimization Letters. DOI:10.1007/s11590-020-01605-z
- De Leone R., Fasano G., Roma M., Sergeyev Y.D., (2019). How Grossone Can Be Helpful to Iteratively Compute Negative Curvature Directions. Learning and Intelligent Optimization, Lecture Notes in Computer Science. Springer. Vol. 11353, pag. 180-183. DOI:10.1007/978-3-030-05348-2_16
- Al-Baali M., Caliciotti A., Fasano G., Roma M., (2018). Quasi-Newton Based Preconditioning and Damped Quasi-Newton Schemes for Nonlinear Conjugate Gradient Methods. Numerical Analysis and Optimization, Springer Proceedings in Mathematics & Statistics. Vol. 235, pag. 1-21. DOI: 10.1007/978-3-319-90026-1_1
- Caliciotti A., Fasano G., Nash S.G., Roma M., (2018). Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods in large scale nonconvex optimization. Data in Brief. Vol. 17, pag. 246-255. DOI:10.1016/j.dib.2018.01.012
- Caliciotti A., Fasano G., Nash S.G., Roma M., (2018). An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization. Operations Research Letters. Vol. 46, pag. 7-12. DOI: 10.1016/j.orl.2017.10.014
- Caliciotti A., Fasano G., Roma M., (2018). Preconditioned Nonlinear Conjugate Gradient methods based on a modified secant equation. Applied Mathematics and Computations. Vol. 318, pag.196-214. DOI: 10.1016/j.amc.2017.08.029
- Al-Baali M., Caliciotti A., Fasano G., Roma M., (2017). Exploiting damped techniques for nonlinear conjugate gradient methods. Mathematical Methods of Operations Research. Vol. 86, pag. 501-522. DOI: 10.1007/s00186-017-0593-1
- Caliciotti A., Fasano G., Roma M., (2017). Novel Preconditioners based on Quasi-Newton updates for Nonlinear Conjugate Gradient methods. Optimization Letters, Vol. 11, n.4, pag. 835-853. DOI: 10.1007/s11590-016-1060-2
- Caliciotti A., Fasano G., Roma M., (2016). Preconditioning strategies for Nonlinear Conjugate gradient methods, based on Quasi-Newton updates. The American Institute of Physics (AIP) Conference Proceedings, Vol. 1776, pp. 090007-1-090007-4. DOI: 10.1063/1.4965371
- Lucidi S., Maurici M., Paulon L., Rinaldi F., Roma M., (2016). A simulation-based multiobjective optimization approach for health care service management. IEEE Transactions on Automation Science and Engineering, Vol.13, n.4, pp. 1480-1491. DOI:10.1109/TASE.2016.2574950
- Fasano G., Roma M., (2016). A novel class of approximate inverse preconditioners for large positive definite linear systems in optimization. Computational Optimization and Applications, Vol. 65, n.2, pp. 399-429. DOI: 10.1007/s10589-015-9765-1
- Lucidi S., Maurici M., Paulon L., Rinaldi F., Roma M., (2016). A derivative-free approach for a simulation-based optimization problem in healthcare. Optimization Letters, Vol.10, n.2, pp. 219-235. DOI: 10.1007/s11590-015-0905-4
- Fasano G., Roma M., (2015). An estimation of the condition number for a class of indefinite preconditioned matrices. Technical Report n.1-2015 - Dipartimento di Ingegneria Informatica, Automatica e Gestionale. SAPIENZA Universita' di Roma.
- Huerta A., Brizi S., Elizondo M., Roma M., (2013). Analyzing the main and the second order effects of operational policies on the warehouse productivity. Proceedings of the 2013 Winter Simulation Conference, R. Pasupathy, S.-H. Kim, A. Tolk, R. Hill, and M. E. Kuhl, eds., pag.3950-3951. 978-1-4799-2076-1/13 IEEE. http://dl.acm.org/citation.cfm?id=2675919
- Fasano G., Roma M., (2013). Preconditioning Newton-Krylov methods in nonconvex large scale optimization. Computational Optimization and Applications, Vol. 56, n.2, pp.253-290. DOI: 10.1007/s10589-013-9563-6
- Fasano G., Roma M., (2012). Preconditioning large indefinite linear systems. SQU Journal for Science, 17, pp.. 63-79.
- Fasano G., Roma M., (2012). Quasi-Newton updates for preconditioned nonlinear conjugate gradient methods. V. De Simone, D. di Serafino, G. Toraldo eds., Recent Advances in Nonlinear Optimization and Equilibrium Problems: a Tribute to Marco D’Apuzzo. Quaderni di Matematica, Seconda Universita' di Napoli Vol. 27, pp. 175-200, Aracne, 2012. DOI: 10.4399/97888548568759
- Fasano G., Roma M., (2011). A class of preconditioners for large indefinite linear systems, as by product of Krylov subspace methods: part 1. Working paper series - Department of Management - Universita' Ca' Foscari Venezia. 5-2011. DOI: 10.2139/ssrn.2037860
- Fasano G., Roma M., (2011). A class of preconditioners for large indefinite linear systems, as by product of Krylov subspace methods: part 2. Working paper series - Department of Management - Universita' Ca' Foscari Venezia. 4-2011. DOI: 10.2139/ssrn.2037861
- Roma M., (2009). Large scale unconstrained optimization. Encyclopedia of Optimization, eds. Floudas C. Pardalos P., pag. 1831-1838. ISBN: 978-0-387-74758-3. DOI: 10.1007/978-0-387-74759-0_324
- Fasano G., Roma M., (2007). Iterative computation of negative curvature directions in large scale optimization. Computational Optimization and Applications, Vol. 38, pp. 81-104. DOI: 10.1007/s10589-007-9034-z
- Fasano G., Roma M., (2007). On the iterative computation of a l2-norm scaling based preconditioner, INSEAN Technical Report N. 2007-002, National Research Center for Ships and Marine Systems, Roma.
- Fasano G., Roma M., (2006). An approximate inverse preconditioner in truncated Newton methods for large scale optimization. Communications to SIMAI Congress, Vol. 1. DOI: 10.1685/CSC06076
- Di Pillo G., Roma M., eds., (2006). Large Scale Nonlinear Optimization. Series Nonconvex Optimization and its Applications, Vol. 83, Springer, 2006. http://link.springer.com/book/10.1007%2F0-387-30065-1
- Roma M., (2005). Dynamic scaling based preconditioning for truncated Newton methods in large scale unconstrained optimization. Optimization Methods and Software, Vol. 20, pp. 693-713. DOI: 10.1080/10556780410001727709
- Gould N.I.M, Lucidi S., Roma M., Toin P.L. (2000). Exploiting negative curvature directions in linesearch methods for unconstrained optimization. Optimization Methods and Software, Vol. 14, n.1-2, pag. 75-98. DOI: 10.1080/10556780008805794
- Gould N.I.M., Lucidi S., Roma M., Toint P.L. (1999). Solving the trust-region subproblem using the Lanczos methods. SIAM Journal on Optimization .Vol. 9, n.2, pag. 504-525. DOI: 10.1137/S1052623497322735
- Lucidi S., Palagi L., Roma M., (1998). On some properties of quadratic programs with a convex quadratic constraint. SIAM Journal on Optimization. Vol. 8, n. 1, pag. 105-122. DOI: 10.1137/S1052623494278049
- Lucidi S., Rochetich F., Roma M., (1998). Curvilinear stabilization techniques for truncated Newton methods in large scale unconstrained optimization. SIAM Journal on Optimization. Vol. 8, n. 4, pag. 916-939. DOI: 10.1137/S1052623495295250
- Gould N.I.M., Lucidi, S., Roma, M., Toint, P.L. (1998). A Linesearch Algorithm with Memory for Unconstrained Optimization. In High Performance Algorithms and Software in Nonlinear Optimization, R. De Leone, A. Murli, P.M. Pardalos, G. Toraldo (eds.) Applied Optimization series, vol. 24, pp. 207-223. Kluwer Academic Publishers. DOI: 10.1007/978-1-4613-3279-4_14
- Di Pillo, G., Lucidi, S., Palagi L., Roma, M. (1998). A Controlled Random Search Algorithm with Local Newton-type Search for Global Optimization. In High Performance Algorithms and Software in Nonlinear Optimization, R. De Leone, A. Murli, P.M. Pardalos, G. Toraldo, (eds.) Applied Optimization series, vol. 24, pp. 143-159. Kluwer Academic Publishers. DOI: 10.1007/978-1-4613-3279-4_10
- Lucidi S., Roma M. (1997). Numerical Experiences with New Truncated Newton Methods in Large scale Unconstrained Optimization. Computational Optimization and Applications. Vol. 7, n. 1, pag. 71-87. DOI: 10.1023/A:1008619812615
- Ferris M.C., Lucidi S., Roma M. (1996). Nonmontone curvilinear line search methods for unconstrained optimization. Computational Optimization and Applications. Vol. 6, n.2, pag. 117-136. DOI: 10.1007/BF00249642
- Lucidi S., Rochetich, F., Roma, M., (1995). A Modified Truncated Newton Method Which Uses Negative Curvature Directions for Large Scale Unconstrained Problems. Selected Papers of the International Conference on Operations Research, Berlin, August 30-September 2, 1994.U. Derigs, A Bachem, A Drexl (eds.). Operations Research Proceedings 1994, pp. 54-59. Springer Berlin Heidelberg. DOI: 10.1007/978-3-642-79459-9_11
- Lucidi, S., Roma M., (1994). Nonmonotone conjugate gradient methods for optimization. In System Modelling and Optimization, Proceedings of the 16th IFIP-TC7 Conference, Compiegne, France, July 5-9, 1993. J. Henry, J.-P. Yvon (eds.) Lecture Notes in Control and Information Sciences, vol. 197, pp 206-214. Springer Berlin Heidelberg. DOI: 10.1007/BFb0035469
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