Global Optimization Using the Multistart Method

Abstract

Multistart is a stochastic global optimization method for finding the global optimum of highly nonlinear mechanical problems. In this paper we introduce and develop a variant of the multistart method in which a fraction of the sample points in the feasible region with smallest function value are clustered using the Vector Quantization technique. The theories of lattices and sphere packing are used to define optimal lattices. These lattices are optimal with respect to quantization error and are used as code points for vector quantization. The implementation of these ideas has resulted in the VQ-multistart algorithm for finding the global optimum with substantial reductions in both the incore memory requirements and the computation time. We solve several mathematical test problems and a mechanical optimal design problem using the VQ-multistart algorithm.