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2023, Volume 8, Issue 1: 1959-1974. doi: 10.3934/math.2023101
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Research article

Outer space branching search method for solving generalized affine fractional optimization problem

  • 1.
    School of Mathematical Sciences, Henan Institute of Science and Technology, Xinxiang 453003, China
  • 2.
    Postdoctoral Research Station of Control Science and Engineering, Henan University of Science and Technology, Luoyang 471023, China
  • Received: 18 July 2022 Revised: 23 September 2022 Accepted: 10 October 2022 Published: 26 October 2022

  • MSC : 90C26, 90C32, 65K05

  • This paper proposes an outer space branching search method, which is used to globally solve the generalized affine fractional optimization problem (GAFOP). First, we will convert the GAFOP into an equivalent problem (EP). Next, we structure the linear relaxation problem (LRP) of the EP by using the linearization technique. By subsequently partitioning the initial outer space rectangle and successively solving a series of LRPs, the proposed algorithm globally converges to the optimum solution of the GAFOP. Finally, comparisons of numerical results are reported to show the superiority and the effectiveness of the presented algorithm.

    Citation: Junqiao Ma, Hongwei Jiao, Jingben Yin, Youlin Shang. Outer space branching search method for solving generalized affine fractional optimization problem[J]. AIMS Mathematics, 2023, 8(1): 1959-1974. doi: 10.3934/math.2023101

    Related Papers:

  • This paper proposes an outer space branching search method, which is used to globally solve the generalized affine fractional optimization problem (GAFOP). First, we will convert the GAFOP into an equivalent problem (EP). Next, we structure the linear relaxation problem (LRP) of the EP by using the linearization technique. By subsequently partitioning the initial outer space rectangle and successively solving a series of LRPs, the proposed algorithm globally converges to the optimum solution of the GAFOP. Finally, comparisons of numerical results are reported to show the superiority and the effectiveness of the presented algorithm.


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