Polynomial optimization relaxations for generalized semi-infinite programs
Abstract This paper studies generalized semi-infinite programs (GSIPs) given by polynomials. We propose a hierarchy of polynomial optimization relaxations to solve them. They are based on Lagrange multiplier expressions and polynomial extensions. Moment-SOS relaxations are applied to solve the polynomial optimization. The convergence of this hierarchy is shown under certain conditions. In particular, the classical semi-infinite programs can be solved as a special case of GSIPs. We also study GSIPs that have convex infinity constraints and show that they can be solved exactly by a single polynomial optimization relaxation. The computational efficiency is demonstrated by extensive numerical results.
Authors
- Jiawang Nie (ORCID: https://orcid.org/0000-0003-2637-8274)
- Xiaomeng Hu (ORCID: https://orcid.org/0000-0001-9494-9003)
Institutions
- University of California San Diego (US)
Publication Details
- Journal
- Mathematical Programming Computation
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1007/s12532-025-00280-4
- Citations
- 1
- Primary Topic
- Advanced Optimization Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 2.63
Funders
- National Science Foundation