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Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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Deterministic Neighborhood Rotation (DNR) for Categorical Variables in Derivative-Free Optimization

Authors: Madeira, J. F. A.;

Deterministic Neighborhood Rotation (DNR) for Categorical Variables in Derivative-Free Optimization

Abstract

Version 2 (major revision). This version replaces the previous file and contains the correct and updated manuscript. The theoretical positioning has been clarified as a finite-domain deterministic framework for categorical variables. The paper introduces deterministic neighborhood rotation (DNR), a fully deterministic and reproducible mechanism for exploring categorical variables without imposing artificial geometry. The logical structure has been strengthened, clearly separating exploration guarantees from algorithmic certification, and the numerical experiments have been significantly expanded. This version supersedes the previous preprint and should be considered the definitive version for citation.

Keywords

Deterministic methods, Permutation-based neighborhoods, Mixed-variable optimization, Derivative-free optimization, geometric optimization, Categorical variables

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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