Evidence map›Paper›PMID 39727736›Full record

ArticleBiomimetics (Basel, Switzerland)2024

Nature-Inspired Approach: A Novel Rat Optimization Algorithm for Global Optimization.

Pianpian Yan, Jinzhong Zhang, Tan Zhang

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Pianpian YanSchool of Electrical and Photoelectronic Engineering, West Anhui University, Lu'an 237012, China.
Jinzhong ZhangSchool of Electrical and Photoelectronic Engineering, West Anhui University, Lu'an 237012, China.ORCID 0000-0001-5988-702X
Tan ZhangSchool of Electrical and Photoelectronic Engineering, West Anhui University, Lu'an 237012, China.

Funding

University scientific research projects 2022AH051674University scientific research projects 2024AH051989
6 · The paper itself

Abstract

This work presents a rat optimization algorithm (ROA), which simulates the social behavior of rats and is a new nature-inspired optimization technique. The ROA consists of three operators that simulate rats searching for prey, chasing and fighting prey, and jumping and hunting prey to deal with optimization issues. The Levy flight strategy is introduced into the ROA to keep the algorithm from running into issues with slow convergence and local optimums. The ROA is tested with four real-world engineering optimization issues and twenty-two benchmark functions. Experiments show that the ROA is particularly effective at solving real-world optimization problems compared to other well-known optimization techniques.

Indexed as

benchmark test functionsengineering optimization issuesLevy flight strategyrat optimization algorithm (ROA)swarm-intelligence

Identifiers

PMID39727736
PMCPMC11673259

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.