implementation and testing of an algorithm for global optimizations with noise
An implementation problem of an algorithm for one-dimensional global optimization in the presence of noise is considered. The approach is based on modelling the objective function as a standard Wiener process. The testing results of the implemented algorithm are presented using several well known test functions. The efficiency of the algorithm is evaluated for different levels of noise.
optimization software testing, algorithms