Abstract
A key procedure in proximal bundle methods for convex minimization problems is the definition of stability centres, which are points generated by the iterative process that successfully decrease the objective function. In this paper we study a different stability-centre classification rule for proximal bundle methods. We show that the proposed bundle variant has at least two particularly interesting features: (i) the sequence of stability centres generated by the method converges strongly to the solution that lies closest to the initial point; (ii) if the sequence of stability centres is finite, being its last element, then the sequence of non-stability centres (null steps) converges strongly to . Property (i) is useful in some practical applications in which a minimal norm solution is required. We show the interest of this property on several instances of a full sized unit-commitment problem.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
