# Weak and Strong Superiorization: Between Feasibility-Seeking and Minimization

arXiv: https://arxiv.org/abs/1410.0130 · HTML: https://mlsanity.com/paper/1410.0130/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Oct 2014.

## Built on by (most cited first, 1 of 1)

- [Feasibility-based Fixed Point Networks](https://mlsanity.com/paper/2104.14090/) (2021)

## Abstract (arXiv)

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 superiorization and clarify their nature.