Abstract
To accelerate the computational speed of data-driven distributionally robust optimization (DDRO), this letter presents a novel algorithmic approach to solve the inner max-min model under norm-2 type uncertainty set in DDRO. The proposed method can solve the problem in an easily implemented way instead of a time-consuming optimization process using commercial solvers. Comparisons of computational time between the algorithmic approach and optimization solvers verify the effectiveness of the proposed method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.