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 comparison 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-free optimization methods. All the numerical results show the effectiveness of the two new algorithms.
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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).
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Campana, E.F., Liuzzi, G., Lucidi, S. et al. New global optimization methods for ship design problems. Optim Eng 10, 533–555 (2009). https://doi.org/10.1007/s11081-009-9085-3
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DOI: https://doi.org/10.1007/s11081-009-9085-3