Revision as of 03:04, 24 January 2011 (view source)← Older edit Latest revision as of 01:33, 6 January 2012 (view source) (Blanked the page) (24 intermediate revisions not shown) Line 1: Line 1: - As its name means, gradient-based methods need the gradient of objective functions to design variables. The evaluation of gradient can be achieved by [[finite difference method, linearized method or adjoint method]]. Both finite difference method and linearized method has a time-cost proportional to the number of design variables and not suitable for design optimization with a large number of design variables. Apart from that, finite difference method has a notorious disadvantage of subtraction cancellation and is not recommended for practical design application. - $J=J(U(\alpha),\alpha)$ - - Finite difference method: - - Linearized method: - - Adjoint method: