---
title: "DEoptim (R package): papers citing this CRAN package"
description: "5 papers in the tracked journals link to DEoptim (R package) in their Crossref records, the first in 2018; most of them (3) in 2020."
url: https://scholar4ai.com/code/cran-deoptim
markdown_url: https://scholar4ai.com/code/cran-deoptim.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to DEoptim (R package) in their Crossref records, the first in 2018; most of them (3) in 2020. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# DEoptim (R package): papers linking to it

Research papers in the 480 tracked journals that link to DEoptim (R package) (https://CRAN.R-project.org/package=DEoptim), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- CRAN
- https://CRAN.R-project.org/package=DEoptim

All repositories: https://scholar4ai.com/code.md

## Key findings

- 5 papers in the tracked journals link to DEoptim (R package) in their Crossref records, the first in 2018; most of them (3) in 2020.
- By category: Finance (2), Operations Research (1) and Statistics (1); the journals with the most are Financial markets and portfolio management (2), Transportation Research Part E Logistics and Transportation Review (1) and Computational Statistics & Data Analysis (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links DEoptim (R package).

## By year

*Papers linking to DEoptim (R package) by publication year*

| Year | Papers |
|---|---:|
| 2018 | 1 |
| 2019 | 1 |
| 2020 | 3 |

## Journals

*Journals whose papers link to DEoptim (R package) most*

| Journal | Papers |
|---|---:|
| [Financial markets and portfolio management](https://scholar4ai.com/journals/financial-markets-and-portfolio-management.md) | 2 |
| [Transportation Research Part E Logistics and Transportation Review](https://scholar4ai.com/journals/transportation-research-part-e-logistics-and-transportation-review.md) | 1 |
| [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | 1 |
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [A differential evolution copula-based approach for a multi-period cryptocurrency portfolio optimization](https://doi.org/10.1007/s11408-018-0320-9) (Financial markets and portfolio management, 2018)
  - [A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization](https://doi.org/10.1007/s11408-020-00346-4) (Financial markets and portfolio management, 2020) — cites the paper above

## Papers

*Papers linking to DEoptim (R package), most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2020-02-18 | [Efficiency of the rail sections in Brazilian railway system, using TOPSIS and a genetic algorithm to analyse optimized scenarios](https://doi.org/10.1016/j.tre.2020.101858) | [Transportation Research Part E Logistics and Transportation Review](https://scholar4ai.com/journals/transportation-research-part-e-logistics-and-transportation-review.md) | Dalmo dos Santos Marchetti, Peter Wänke | 43 | cites it |
| 2018-11-01 | [A differential evolution copula-based approach for a multi-period cryptocurrency portfolio optimization](https://doi.org/10.1007/s11408-018-0320-9) | [Financial markets and portfolio management](https://scholar4ai.com/journals/financial-markets-and-portfolio-management.md) | Jules Clément Mba, Edson Pindza, Ur Koumba | 33 | cites it |
| 2020-02-13 | [A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization](https://doi.org/10.1007/s11408-020-00346-4) | [Financial markets and portfolio management](https://scholar4ai.com/journals/financial-markets-and-portfolio-management.md) | Jules Clément Mba, Sutene Mwambetania Mwambi | 31 | cites it |
| 2020-12-13 | [Predicting tweet impact using a novel evidential reasoning prediction method](https://doi.org/10.1016/j.eswa.2020.114400) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Lucía Rivadeneira, Jianbo Yang, Manuel López‐Ibáñez | 23 | cites it |
| 2019-02-11 | [A nonparametric bootstrap method for spatial data](https://doi.org/10.1016/j.csda.2019.01.017) | [Computational Statistics & Data Analysis](https://scholar4ai.com/journals/computational-statistics-data-analysis.md) | Sergio Castillo-Páez, Rubén Fernández‐Casal, Pilar García Soidán | 12 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). DEoptim (R package): papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/cran-deoptim

```bibtex
@misc{scholar4ai-code-cran-deoptim,
  author = {{Scholar4AI}},
  title = {DEoptim (R package): papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/cran-deoptim}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).