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A D.C. Programming Approach to Fractional Problems

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Learning and Intelligent Optimization (LION 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10556))

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Abstract

This paper addresses a rather general fractional optimization problem. There are two ways to reduce the original problem. The first one is a solution of an equation with the optimal value of an auxiliary d.c. optimization problem with a vector parameter. The second one is to solve the second auxiliary problem with nonlinear inequality constraints. Both auxiliary problems turn out to be d.c. optimization problems, which allows to apply Global Optimization Theory [11, 12] and develop two corresponding global search algorithms that have been tested on a number of test problems from the recent publications.

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References

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Acknowledgments

This work has been supported by the Russian Science Foundation, Project No. 15-11-20015.

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Authors and Affiliations

  1. Matrosov Institute for System Dynamics and Control Theory of SB RAS, Lermontov Str., 134, 664033, Irkutsk, Russia

    Tatiana Gruzdeva & Alexander Strekalovsky

Authors
  1. Tatiana Gruzdeva
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  2. Alexander Strekalovsky
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Corresponding author

Correspondence to Tatiana Gruzdeva .

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Editors and Affiliations

  1. University of Trento, Trento, Italy

    Roberto Battiti

  2. University of Calabria, Rende, Italy

    Dmitri E. Kvasov

  3. University of Calabria, Rende, Italy

    Yaroslav D. Sergeyev

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Gruzdeva, T., Strekalovsky, A. (2017). A D.C. Programming Approach to Fractional Problems. In: Battiti, R., Kvasov, D., Sergeyev, Y. (eds) Learning and Intelligent Optimization. LION 2017. Lecture Notes in Computer Science(), vol 10556. Springer, Cham. https://doi.org/10.1007/978-3-319-69404-7_27

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  • DOI: https://doi.org/10.1007/978-3-319-69404-7_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69403-0

  • Online ISBN: 978-3-319-69404-7

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