Abstract:
A number of ways to accelerate homogeneous algorithms for global optimization are
proposed. Theorems on the possibilities of acceleration without loss of convergence
to the global minimum are proved. Models of objective functions are considered.
It is proved that the use of these models ensures a convergence to the global minimum
of the objective function. A model to determine the application field of the algorithm
is constructed. Some numerical results of testing the proposed algorithm are discussed.