Superiorization and Perturbation Resilience of Algorithms: A Continuously Updated Bibliography

TL;DR

This paper collects and curates the body of work on superiorization and perturbation resilience, focusing on how perturbing feasibility-seeking algorithms can reduce a merit function at essentially the same computational cost. It positions the methodology as an alternative to traditional constrained optimization, emphasizing feasibility preservation while guiding iterates toward more desirable outcomes. The bibliography spans foundational works from the late 2000s to 2025, highlights developments such as the SNARK14 system and the Inverse Problems special issue, and documents ongoing updates and community contributions. The resource supports researchers in imaging, therapy planning, and related inverse problems by facilitating literature discovery, reproducibility, and cross-domain adoption.

Abstract

This document presents a (mostly) chronologically-ordered bibliography of scientific publications on the superiorization methodology and perturbation resilience of algorithms which is compiled and continuously updated by us at: http://math.haifa.ac.il/yair/bib-superiorization-censor.html. Since the beginnings of this topic we try to trace the work that has been published about it since its inception. To the best of our knowledge this bibliography represents all available publications on this topic to date, and while the URL is continuously updated we will revise this document and bring it up to date on arXiv approximately once a year. Abstracts of the cited works, and some links and downloadable files of preprints or reprints are available on the above mentioned Internet page. If you know of a related scientific work in any form that should be included here kindly write to me on: yair@math.haifa.ac.il with full bibliographic details, a DOI if available, and a PDF copy of the work if possible. The Internet page was initiated on March 7, 2015, and has been last updated on March 19, 2025. Comment: Some of the items have on the above mentioned Internet page more information and links than in this report. Acknowledgments: The compilation of this report was supported by the ISF-NSFC joint research program grant No. 2874/19, by the U.S. National Institutes of Health grant No. R01CA266467 and by the Cooperation Program in Cancer Research of the German Cancer Research Center (DKFZ) and the Israeli Ministry of Innovation, Science and Technology (MOST).