This contribute deals with the use of Kriging surrogates in multi-objective engineering design optimization. The surrogate management issue to find a tradeoff between accuracy, efficiency and solutions quality is addressed. A Data Envelopment, Analysis (DEA) approach to the performance assessment is proposed. The method is applied to carry out a comparative analysis of different strategies for a case study devoted to the design of a component of the injection system for compressed natural gas (CNG) engines.
Performance evaluation of the evolution control in design optimization assisted by Kriging surrogates / Dellino, Gabriella; Lino, Paolo; Meloni, Carlo; Rizzo, Alessandro. - STAMPA. - (2007), pp. 49-51. (Intervento presentato al convegno 5th International Industrial Simulation Conference, ISC 2007 tenutosi a Delft, NL nel June 11-13, 2007).
Performance evaluation of the evolution control in design optimization assisted by Kriging surrogates
Paolo Lino;Carlo Meloni;
2007-01-01
Abstract
This contribute deals with the use of Kriging surrogates in multi-objective engineering design optimization. The surrogate management issue to find a tradeoff between accuracy, efficiency and solutions quality is addressed. A Data Envelopment, Analysis (DEA) approach to the performance assessment is proposed. The method is applied to carry out a comparative analysis of different strategies for a case study devoted to the design of a component of the injection system for compressed natural gas (CNG) engines.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
