Multi-objective approach for robust design optimization problems

This article demonstrates the main capabilities of IOSO (indirect Optimization based on Self-organization) technology algorithms, tools, and software, which can be used for the optimization of complex systems and objects. IOSO algorithms have higher efficiency, provide a wider range of capabilities, and are practically insensitive with respect to the types of objective function and constraints. They could be smooth, non-differentiable, and stochastic, with multiple optima, with the portions of the design space where objective function and constraints could not be evaluated at all, with the objective function and constraints dependent on mixed variables, etc. The capabilities of IOSO software are demonstrated using examples of solving complex multi-objective (up to 8 simultaneous objectives) problems, which are solved in deterministic and robust design optimization statements. The results of this study show the Pareto set probability statement, which decreases technical risks when developing modern objects and systems with the highest level of efficiency.