Probabilistic optimization via approximate p-efficient points and bundle methods. (January 2017)

• Record Type: Journal Article
• Authors: van Ackooij, W.; Berge, V.; de Oliveira, W.; Sagastizábal, C.
• Is Part Of: Computers & operations research. Volume 77(2017)
• Page Start: 177
• Page End: 193
• Publication Date: 2017-01
• Subjects: Probabilistic constraints -- Stochastic programming -- Duality -- Bundle methods -- p-efficient points; Operations research -- Periodicals; Electronic digital computers -- Periodicals; 004.05
• DOI: 10.1016/j.cor.2016.08.002
• Languages: English
• ISSNs: 0305-0548

Abstract

Abstract: For problems when decisions are taken prior to observing the realization of underlying random events, probabilistic constraints are an important modeling tool if reliability is a concern. A key concept to numerically dealing with probabilistic constraints is that of p -efficient points. By adopting a dual point of view, we develop a solution framework that includes and extends various existing formulations. The unifying approach is built on the basis of a recent generation of bundle methods called with on-demand accuracy, characterized by its versatility and flexibility. Numerical results for several difficult problems confirm the interest of the approach.