A global minimization algorithm with two parallel iterations

An algorithm is proposed for minimizing multi-extremum functions in which the function is evaluated simultaneously at several points (on several concurrently running processors) in eauych iteration. Conditions are established when the proposed concurrent method does not perform redundant computations compared with the efficient purely sequential method, which is the basis for the concurrent scheme. The algorithm is generalized to the multidimensional case. Some applications of the method are described.