Control algorithm for decision making in multi-criteria optimization problems

The main feature of the multi-criteria optimization of the design processes of complex electronic devices is that they are all interconnected, heterogeneous in nature and, as a rule, non-linear. That is, by changing some of them by varying the corresponding parameters, we inevitably change other parameters of the system, and not always in the right direction. The purpose of the work is to propose a way to organize the procedure for finding the optimal solution to multicriteria design problems. When developing and creating new schemes, structures and systems, the task of determining the optimal values of the parameters of the designed technical device or system is reduced to the task of finding the extremum of a certain function, called the quality function. Usually, it is a non-linear function of many independent variables, which, as a rule, cannot be investigated by analytical methods. In this situation, it is advisable to search for a solution to the problem using special algorithms. At the early stages of designing complex radio electronic devices, an algorithm for finding the optimal solution based on the application of search optimization theory methods is proposed. The paper describes the procedure for finding the optimal solution, the distinctive feature of which is that during the search for a solution, information is accumulated and a search direction vector is constructed. This vector offers options for changing weights for subsequent search procedures. The algorithm developed on its basis is used in the information system for the complex analysis of the designs of radio-electronic facilities. The use of random search provides the algorithm with global properties, reduces the number of objective function calculations by one step, which is especially noticeable with a large number of optimized parameters. Allows you to quite simply include any restrictions on the set of valid values of the vector of optimized parameters, which is not always possible when using regular search methods. The proposed algorithm is simply tuned to search for a global extremum by selecting the appropriate parameters. For each specific case, there are some optimal ratios of the values of these algorithm parameters, which, when searching for a solution, reduce the number of working steps. The developed algorithm is less critical to the optimal values of its own parameters, which makes it much easier to tune it when solving practical problems of optimizing design processes.