EFFICIENCY OF PARALLEL GLOBAL OPTIMIZATION OF MULTIVARIABLE FUNCTIONS
A parallel algorithm for global optimization of multivariable functions is considered which is based on the modified bisection method and a local search algorithm. The main attention is paid to a proper balance of computing resources between the phases of local and global optimizations. The PGraph, a visual programming tool for parallel computations, is used to develop and study our algorithm. Numerical test results of the proposed algorithm are presented.