Evidence map›Paper›PMID 39281471›Full record

ReviewHeliyon2024

Comparative analysis of the gazelle Optimizer and its variants.

Raghav Mahajan, Himanshu Sharma, Krishan Arora, Gyanendra Prasad Joshi, Woong Cho

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Raghav MahajanSchool of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, 144411, India.
Himanshu SharmaSchool of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, 144411, India.
Krishan AroraSchool of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, 144411, India.
Gyanendra Prasad JoshiDepartment of Computer Science and Engineering, Sejong University, Seoul 05006, Republic of Korea.
Woong ChoDepartment of Electronics, Information and Communication Engineering, Kangwon National University, Samcheok 25913, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Gazelle Optimization Algorithm (GOA) is an innovative nature-inspired metaheuristic algorithm, designed to mimic the agile and efficient hunting strategies of gazelles. Despite its promising performance in solving complex optimization problems, there is still a significant scope for enhancing its efficiency and robustness. This paper introduces several novel variants of GOA, integrating adaptive strategy, Levy flight strategy, Roulette wheel selection strategy, and random walk strategy. These enhancements aim to address the limitations of the original GOA and improve its performance in diverse optimization scenarios. The proposed algorithms are rigorously tested on CEC 2014 and CEC 2017 benchmark functions, five engineering problems, and a Total Harmonic Distortion (THD) minimization problem. The results demonstrate the superior performance of the proposed variants compared to the original GOA, providing valuable insights into their applicability and effectiveness.

Indexed as

Benchmark functionsEngineering design problemGazelle optimization algorithmTotal harmonic distortion

Identifiers

PMID39281471
PMCPMC11401037

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.