Testing results

We constantly test the efficiency of our optimization algorithms using various classes of test functions and optimization problems of complex real-life systems. Based on the results of these tests we may conclude that IOSO Technology Algorithms:

• are comparable in performance with well known highly efficient optimization algorithms for smooth single extremum function (comparison);

• have a distinct advantage over the other algorithms when considering non-smooth function, which are most frequently encountered in real-life problems;

• could be equally efficiently used to solve problems with various types of objective functions: smooth, non-differentiable, stochastic, dependent on mixed variables, the objective functions that could potentially have the regions where they can not be evaluated;

• have good global properties and in most of the cases allow the users to solve the problems with multiple optima;

• are not sensitive to “noise” when solving stochastic optimization problems;

• have unique capabilities when applied to multiobjective, multilevel, and parallel optimization.
  

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