Development of an Algorithm and Software for Evaluating alternatives based on the Method of additive Convolution of Criteria
Abstract
Objective . The aim of the study is to develop an algorithm and software for evaluating alternatives based on the additive convolution method of criteria. Method . The additive convolution method allows summing up individual criteria based on their importance, forming a single integral value; the calculation algorithm includes sequential steps, normalization, determination of weights, and integration of the obtained data; the developed software product, implemented in the Python programming language using the Tkinter library, provides a convenient graphical representation of the result. Result . The stages of the method implementation are presented, including normalization of criteria, determination of importance weights, and the convolution procedure that combines different indicators into an integral indicator. The algorithm describes the calculation functions and provides a code listing. An algorithm for software development is presented. An example of applying the method to assess the effectiveness of antihistamines is given. Conclusion . The program allows calculating integral indicators and finding criterion weights using a pairwise comparison matrix, as well as presenting the result in the form of a graph. The proposed method and the developed software package represent an effective tool for decision-making with the selection of the optimal alternative. Using the software product simplifies the process of comparing and analyzing a large number of factors, increasing the accuracy and objectivity of selection.
Fields of Study & Subjects
Scientific Research and Studies
Quality of Life Measurement
Aerospace
Electronics
Mathematical Modeling
Publication details
- Journal / source
- Herald of Dagestan State Technical University Technical Sciences
- Publisher
- FSB Educational Establishment of Higher Education Daghestan State Technical University
- Volume
- 52
- Issue
- 4
- Pages
- 126–136
- Publication date
- 4 February 2026
- Language
- RU