Dholes-inspired optimization (DIO): a nature-inspired algorithm for engineering optimization problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10260597" target="_blank" >RIV/61989100:27240/25:10260597 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s10586-025-05543-2" target="_blank" >https://link.springer.com/article/10.1007/s10586-025-05543-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10586-025-05543-2" target="_blank" >10.1007/s10586-025-05543-2</a>
Alternative languages
Result language
angličtina
Original language name
Dholes-inspired optimization (DIO): a nature-inspired algorithm for engineering optimization problems
Original language description
This paper proposes the Dhole-Inspired Optimization (DIO) algorithm, a novel metaheuristic inspired by the cooperative hunting behavior of dholes (Cuon alpinus). The algorithm employs a hierarchical pack structure, where a Lead Vocalizer guides the search process while subordinate members adapt their movements to balance exploration and exploitation dynamically. This structure enhances search efficiency, prevents premature convergence, and improves solution accuracy across different problem landscapes. DIO is benchmarked on unimodal, multimodal, and composite test functions, demonstrating superior performance compared to established optimization algorithms, including Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Gravitational Search Algorithm (GSA), Fast Evolutionary Programming (FEP), and Differential Evolution (DE). The results show that DIO achieves higher accuracy and faster convergence rates on a majority of test cases, validating its robustness and reliability in tackling complex optimization problems. Furthermore, the algorithm is evaluated on real-world engineering applications, demonstrating its adaptability and effectiveness in practical scenarios. The findings highlight DIO as a versatile and competitive optimization approach, suitable for a wide range of applications in science and engineering.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Cluster Computing-The Journal of Networks Software Tools and Applications
ISSN
1386-7857
e-ISSN
1573-7543
Volume of the periodical
28
Issue of the periodical within the volume
13
Country of publishing house
US - UNITED STATES
Number of pages
38
Pages from-to
nestránkováno
UT code for WoS article
001576153100032
EID of the result in the Scopus database
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