Enhanced Multi-Strategy Improved Animated Oat Optimization Algorithm and Its Engineering Application.

Sunde Wang, Beilei Yin, Pu Wang, Zihao Cheng

Abstract read

In one paragraph

Article in Biomimetics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

4 authors.

Sunde WangSchool of Electronics and Electrical Engineering, Wenzhou University of Technology, Wenzhou 325035, China.

Beilei YinEngineering Technology Department, Shanghai Caoyang Vocational School, Shanghai 200333, China.

Pu WangSchool of Computer Engineering, Hubei University of Arts and Science, Xiangyang 441053, China.ORCID 0000-0003-4295-2053

Zihao ChengCollege of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To address the inherent limitations of the traditional Animated Oat Optimization Algorithm (AOO), including poor uniformity of initial random population distribution and insufficient dynamic balance between global exploration and local exploitation, this paper proposes an Enhanced Animated Oat Optimization Algorithm (EAOO) incorporating multi-strategy improvements. First, the Sinusoidal chaotic map is introduced to replace the original random initialization method. Leveraging the ergodicity and uniformity of chaotic sequences, the spatial distribution of the population is optimized, and the diversity of the initial population is significantly enhanced. Second, a nonlinear disturbance factor is embedded into the position update of leaders during both the exploration and exploitation phases, enabling dynamic and adaptive adjustment of the search range. This effectively balances the algorithm's capabilities in global exploration and local exploitation. Finally, an adaptive

Indexed as

adaptive t-distributionAnimated Oat Optimization Algorithmdisturbance factorengineering design optimizationSinusoidal chaotic mapswarm intelligence optimization

Identifiers

PMID42505519

DOI10.3390/biomimetics11070486

PMCPMC13406925

What OpenQuestion holds

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LicenceCC BY

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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.