%0 Journal Article
%T A Derivative-Free Optimization Algorithm Using Sparse Grid Integration
%A Shengyuan Chen
%A Xiaogang Wang
%J American Journal of Computational Mathematics
%P 16-26
%@ 2161-1211
%D 2013
%I Scientific Research Publishing
%R 10.4236/ajcm.2013.31003
%X <p align=\"justify\">
	<span style=\"font-family:;\">We present a new derivative-free optimization algorithm based on the sparse grid numerical integration. The algorithm applies to a smooth nonlinear objective function where calculating its gradient is impossible and evaluating its value is also very expensive. The new algorithm has: </span><span style=\"font-family:;\">1</span><span style=\"font-family:;\">) a unique starting point strategy; </span><span style=\"font-family:;\">2</span><span style=\"font-family:;\">) an effective global search heuristic; and </span><span style=\"font-family:;\">3</span><span style=\"font-family:;\">) consistent local convergence. These are achieved through a uniform use of sparse grid numerical integration. Numerical experiment result indicates that the algorithm is accurate and efficient, and benchmarks favourably against several state-of-art derivative free algorithms.</span> 
</p>
%K Nonlinear Programming
%K Derivative Free Optimization
%K Sparse Grid Numerical Integration
%K Conditional Moment
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=29076