Solving a class of robust vector rational optimization problems

Jian Huang

doi:10.1007/s10479-025-06938-5

Solving a class of robust vector rational optimization problems

2025-11-13

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DOI：10.1007/s10479-025-06938-5

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In this paper, we are interested in the study of finding robust efficient solutions in vector rational optimization problems with SOS-convex polynomials under data uncertainty. In order to solve such a class of vector rational optimization problems, we provide a mixed-type method consisting of the $$\varepsilon $$ -constraint method for vector optimization, the parameter-free approach for rational optimization, and the exact SDP-based relaxation method for SOS-convex polynomial programs. We also give a procedure (with a detailed computed example) to show how our method works.

Keywords:

Robust optimization

Semidefinite programming

Vector programming

Rational programming

Sum of squares convex polynomials

Solving a class of robust vector rational optimization problems

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