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 fledged 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 superior-ization and clarify their nature.
| Original language | English |
|---|---|
| Pages (from-to) | 41-54 |
| Number of pages | 14 |
| Journal | Analele Stiintifice ale Universitatii Ovidius Constanta, Seria Matematica |
| Volume | 23 |
| Issue number | 3 |
| DOIs | |
| State | Published - 15 Jul 2015 |
Keywords
- Constrained minimization
- Convex feasibility problem
- Dynamic string-averaging
- Perturbation resilience
- Strict Fejer monotonicity
- Superiorization methodology
- Superiorized version of an algorithm
ASJC Scopus subject areas
- Analysis
- Applied Mathematics