IOSO NM software can be easily integrated with different applications for engineering analysis both in-house and commercial, such as NASTRAN, ANSYS, StarCD, FineDesign, Fluent etc.

Novelty and distinctive features of IOSO NM:

• multiobjective optimization for large-dimensionality problems (up to 100 independent design variables and up to 100 constraints), which allows to reach the increase of efficiency by 2 - 7 times higher than that of middle-dimensionality optimization tasks (20…40 design variables);

• low expenditures for optimal solution search (reduction of the number of analysis code direct calls calls up to 20 times in comparison with traditional approaches and genetic algorithms (GA), depending on the complexity and dimensionality of the task);

• full automatic optimization technology algorithms with easy to use procedure of task setting;

• the possibility to solve multidisciplinary optimization problems;

• multiobjective optimization for stochastic problems (up to 100 independent design variables), having complex topology of objective and the large number of constraints. Now it is well-known that many methods are capable of solving the tasks having up to 10 - 20 variables, and it is not known the analogues to IOSO  optimizer that is designed for large-dimensional multiobjective tasks (100 independent design variables and 20 objectives);

• solving all classes of optimization problems including stochastic, multiextreme and having non-differential peculiarities.

IOSO NM is successfully used for solving practical tasks for such companies as: NPO “Saturn”, Sukhoy’s Design Bureau and other enterprise companies. The software is implemented in these company's technological process of the development of complex, competitive engineering objects, it is used for solving following problems:

•  obtaining the most efficient technical solutions by means of the optimization of the models of large-dimensional systems providing extremum for the one or several efficiency indices of the system;

• determining optimal control laws for complex devices and for their different operational modes;

• comparative analysis of alternative optimum variants and the substantiation of choice of technical solution.