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Parallel Computing for Time-Consuming Multicriterial Optimization Problems

  • Victor GergelEmail author
  • Evgeny Kozinov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10421)

Abstract

In the present paper, an efficient method for parallel solving the time-consuming multicriterial optimization problems, where the optimality criteria can be multiextremal, and the computation of the criteria values can require a large amount of computations, is proposed. The proposed scheme of parallel computations allows obtaining several efficient decisions of a multicriterial problem. During performing the computations, the maximum use of the search information is provided. The results of the numerical experiments have demonstrated such an approach to allow reducing the computational costs of solving the multicriterial optimization problems essentially – several tens and hundred times.

Keywords

Decision making Multicriterial optimization Parallel computing Dimensionality reduction Criteria convolution Algorithm of global search Computation complexity 

Notes

Acknowledgements

This work has been supported by Russian Science Foundation, project No 16-11-10150 “Novel efficient methods and software tools for time-consuming decision making problems using superior-performance supercomputers.”

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Lobachevsky State University of Nizhny NovgorodNizhny NovgorodRussia

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