IOSO is a new generation multidimensional nonlinear optimization technology. It is a powerful instrument for finding new technical solutions that provide maximum possible efficiency for complex systems.
Our software was designed to find the breakthrough approach solving "heavy tasks" of optimization in different branches of human being. There is no analogous software handling tasks of 100 variables and 20 criteria (goals) order of dimension.

IOSO Technology:

• provides significant reduction of time and cost for solving complex practical tasks;
• allows finding the most efficient technical solutions according to several goals or criteria (multiobjective formulation);
• provides minimization of the number of necessary engineering calculations or the amount of experimental work while searching for optimal parameters of the real-life systems;
• allows determining the maximum possible efficiency of a system;
• allows finding an optimal technical solution while there are different manufacturing precision, for technical systems with high probability (robust optimization).

The main advantages you can get from using the IOSO Technology is ability to solve very complex optimization tasks. IOSO Technology algorithms, in fact:

• are independent of the optimization task types;
• are able to find the global optimum;
• have high convergence rate and allow to quickly and efficiently find the region where optimum is located;
• allow the robust solving of stochastic optimization tasks, even if such problems have high level of noise with IOSO RD;
• provide the capabilities to solve real-life optimization tasks that involve complex modern high fidelity mathematical models or engineering applications (for example, 3D CAD, CFD or FEA software);
• have full-automatic optimization algorithms which do not need to be tuned up by a user.

Most of the real-life engineering optimization problems require simultaneous optimization of more than one objective function. In these cases to ensure a satisfactory design some trade-off between the objectives is necessary: for this purpose we use the multiobjective (multi goal) approach to optimize the overall efficiency also using the parallelization of the optimization process.

IOSO Technology algorithms are distributed in three different versions:

• IOSO NM, for optimizations on a single, stand-alone machine;
• IOSO PM, for parallel optimizations on multiple machines;
• IOSO RD, for robust optimizations on stochastic problems.

Our strategy of multilevel optimization ensures maximum reduction in time required to solve optimization problem. This becomes possible due to the simultaneous use of mathematical models of various fidelity and active automatic switching between them in the optimization process. The proposed procedure minimizes the number of times the highest fidelity model is involved without reducing the accuracy of the solution. Our experience shows that it is possible to solve the optimization problem when the number of times the highest fidelity model is involved is less than the number of design variables. This fact allows for considerable (several orders of magnitude) reduction in CPU time required to solve an optimization problem.