2015/11/01 by Yair Censor · 2 citations
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #Optimization and Variational Analysis #Sparse and Compressive Sensing Techniques
paper · pdf · doi:10.1515/auom-2015-0046
openalex publication_date 2015/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Abstract We review the superiorization methodology, which can be thought of, in some cases, as lying between feasibility-seeking and constrained minimization. It is not quite trying to solve the full edged constrained minimization problem; rather, the task is to find a feasible point which is superior (with respect to an objective function value) to one returned by a feasibility-seeking only algorithm. We distinguish between two research directions in the superiorization methodology that nourish from the same general principle: Weak superiorization and strong superiorization and clarify their nature.