Method of convolution in multicriteria problems with uncertainty

Abstract

The problem of optimizing complex systems under incomplete information when there are several criteria for the system’s efficiency (optimization goals) is considered. The properties of different types of the convolution of these criteria, as well as the method of successive concessions for formalizing the concept of the solution of multicriteria (MC) problems with uncertainty, are analyzed. We show that there is a difference between the solutions obtained with different convolutions and method modifications. The advantages of the inverse logical convolution are demonstrated.