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Programme systems to estimate the Pareto-approximation quality in the problem of multi-criteria optimization. A review.
Author(s) -
Valentina Belous,
Sergey Groshev,
Anatoly Karpenko,
Ivan Shibitov
Publication year - 2014
Publication title -
nauka i obrazovanie
Language(s) - English
Resource type - Journals
ISSN - 1994-0408
DOI - 10.7463/0414.0709198
Subject(s) - pareto principle , mathematical optimization , multi objective optimization , quality (philosophy) , computer science , mathematics , physics , quantum mechanics

The paper considers a relatively new and rapidly growing class of multi-criteria optimization (MCO) methods. This class is based on the preliminary creation of a finite-dimensional approximation of the Pareto set and, subsequently, the Pareto-approximation of MCO problem. Since many different methods are known, there is a problem to compare these methods with each other. Solving real world MCO problems one often faces more than two criterion functions. This fact makes it difficult to perform a visual analysis of the proper Pareto-approximation. Therefore,

A lot of quality indicators of Pareto-approximation have been developed. In this work a statement of multi-criteria optimization problem was presented along with a brief review of the specified class of methods and existent quality indicators. The paper itself is devoted to the review of existent programme systems, designed for building Pareto-approximation, which implement various algorithms of quality estimation.

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