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Multistage Global Search Using Various Scalarization Schemes in Multicriteria Optimization Problems

  • Victor GergelEmail author
  • Evgeniy Kozinov
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)

Abstract

In this paper, an approach, in which the decision making problems are reduced to solving the multicriteria time-consuming global optimization problems is proposed. The developed approach includes various methods of scalarization of the vector criteria, the dimensionality reduction with the use of the Peano space-filling curves and the efficient global search algorithms. In the course of computations, the optimization problem statements and the applied methods of the criteria scalarization can be altered in order to achieve more complete compliance to available requirements to the optimality. The overcoming of the computational complexity of the developed approach is provided by means of the reuse of the whole search information obtained in the course of computations. The performed numerical experiments have confirmed the reuse of the search information to allow reducing essentially the amount of computations for solving the global optimization problems.

Keywords

Decision making Multicriteria optimization Criteria scalarization Global optimization with nonlinear constraints Numerical experiment 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Lobachevsky State University of Nizhni NovgorodNizhni NovgorodRussia

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