Comprehensive Approach to the Design of Information Systems and Optimization of Technical Solutions according to Many Criteria
- Belarusian State University of Informatics and Radioelectronics
Pietrusia Brouki, 6, Minsk 220013 Belarus
tatur@bsuir.by - United Institute of Informatics Problems
Surganova 6, Minsk, 220012, Belarus
novos65@gmail.com - Belarusian State University
Nezavisimosti Avenue 4, Minsk, 220030, Belarus
LukashevichMM@bsu.by
Abstract
One of the problems of the modern information society is the development of effective complex multiprocessor information systems, taking into account the rational use of system resources. The problem of finding the optimal variant of a multiprocessor system is presented as a problem of multicriteria optimization and makes it possible to search for a trade-off between several alternatives. The paper describes several approaches to the comparative assessment of multiprocessor systems, including the search for the non-dominated solutions; narrowing down the Pareto space, using the additional expert information; converting the problem to single-criteria optimization with convolution of criteria; searching for the optimal solution that is closest to the reference point. In the paper the authors propose a ranking method to evaluate technical solutions. The method is based on ranking individual alternatives for each optimization criterion separately, followed by aggregation of ordered ranked lists. The advantage of using the ranking methods is to obtain a complete rating of technical solutions based on their effectiveness, assessed by several criteria. The paper has an educational character and considers the problem of finding a trade-off between system parameters when looking for technical solutions. The practical results of applying different approaches are demonstrated using a simple example.
Key words
multiprocessor information systems, genetic algorithm, multicriteria optimization
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Tatur, M., Novoselova, N., Lukashevich, M.: Comprehensive Approach to the Design of Information Systems and Optimization of Technical Solutions according to Many Criteria. Computer Science and Information Systems