Title :
Global Optimization With Multivariate Adaptive Regression Splines
Author :
Crino, Scott ; Brown, Donald E.
Author_Institution :
US Mil. Acad., West Point, NY
fDate :
4/1/2007 12:00:00 AM
Abstract :
This paper presents a novel procedure for approximating the global optimum in structural design by combining multivariate adaptive regression splines (MARS) with a response surface methodology (RSM). MARS is a flexible regression technique that uses a modified recursive partitioning strategy to simplify high-dimensional problems into smaller yet highly accurate models. Combining MARS and RSM improves the conventional RSM by addressing highly nonlinear high-dimensional problems that can be simplified into lower dimensions, yet maintains a low computational cost and better interpretability when compared to neural networks and generalized additive models. MARS/RSM is also compared to simulated annealing and genetic algorithms in terms of computational efficiency and accuracy. The MARS/RSM procedure is applied to a set of low-dimensional test functions to demonstrate its convergence and limiting properties
Keywords :
convergence of numerical methods; design of experiments; genetic algorithms; regression analysis; response surface methodology; simulated annealing; splines (mathematics); structural engineering computing; convergence; generalized additive models; genetic algorithms; global structural design optimization; low-dimensional test functions; multivariate adaptive regression splines; neural networks; nonlinear high-dimensional problems; recursive partitioning strategy; regression technique; response surface methodology; simulated annealing; Additives; Computational efficiency; Computational modeling; Convergence; Genetic algorithms; Mars; Neural networks; Response surface methodology; Simulated annealing; Testing; Genetic algorithm (GA); neural network (NN); simulated annealing (SA); successive response surface methodology (SRSM); Algorithms; Artificial Intelligence; Computer Simulation; Models, Theoretical; Multivariate Analysis; Numerical Analysis, Computer-Assisted; Regression Analysis;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2006.883430
