Optim Eng (2009) 10: 533–555 DOI 10.1007/s11081-009-9085-3 New global optimization methods for ship design problems Emilio Fortunato Campana · Giampaolo Liuzzi · Stefano Lucidi · Daniele Peri · Veronica Piccialli · Antonio Pinto Received: 1 January 2008 / Accepted: 6 April 2009 / Published online: 15 April 2009 © Springer Science+Business Media, LLC 2009 Abstract The aim of this paper is to solve optimal design problems for industrial applications when the objective function value requires the evaluation of expensive simulation codes and its first derivatives are not available. In order to achieve this goal we propose two new algorithms that draw inspiration from two existing approaches: a filled function based algorithm and a Particle Swarm Optimization method. In order to test the efficiency of the two proposed algorithms, we perform a numerical compar- ison both with the methods we drew inspiration from, and with some standard Global Optimization algorithms that are currently adopted in industrial design optimization. Finally, a realistic ship design problem, namely the reduction of the amplitude of the heave motion of a ship advancing in head seas (a problem connected to both safety and comfort), is solved using the new codes and other global and local derivative- This work has been partially supported by the Ministero delle Infrastrutture e dei Trasporti in the framework of the research plan “Programma di Ricerca sulla Sicurezza”, Decreto 17/04/2003 G.U. n. 123 del 29/05/2003, by MIUR, FIRB 2001 Research Program Large-Scale Nonlinear Optimization and by the U.S. Office of Naval Research (NICOP grant N. 000140510617). E.F. Campana ( ) · D. Peri · A. Pinto INSEAN—Istituto Nazionale per Studi ed Esperienze di Architettura Navale, Via di Vallerano 139, 00128 Roma, Italy e-mail: E.Campana@insean.it G. Liuzzi Consiglio Nazionale delle Ricerche, Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti”, Viale Manzoni 30, 00185 Roma, Italy S. Lucidi Dipartimento di Informatica e Sistemistica “A. Ruberti”, Università degli Studi di Roma “Sapienza”, Via Ariosto 25, 00185 Roma, Italy V. Piccialli Dipartimento di Ingegneria dell’Impresa, Università degli Studi di Roma “Tor Vergata”, Via del Policlinico 1, 00133 Roma, Italy