The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.
Emperor penguin optimizer: A bio-inspired algorithm for engineering problems
Abstract
Abstract This paper proposes a novel optimization algorithm, called Emperor Penguin Optimizer (EPO), which mimics the huddling behavior of emperor penguins (Aptenodytes forsteri). The main steps of EPO are to generate the huddle boundary, compute temperature around the huddle, calculate the distance, and find the effective mover. These steps are mathematically modeled and implemented on 44 well-known benchmark test functions. It is compared with eight state-of-the-art optimization algorithms. The paper also considers for solving six real-life constrained and one unconstrained engineering design problems. The convergence and computational complexity are also analyzed to ensure the applicability of proposed algorithm. The experimental results show that the proposed algorithm is able to provide better results as compared to the other well-known metaheuristic algorithms.
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Self-citationTunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization
Kaur, S., Awasthi, L. K., Sangal, A. L., & Dhiman, G. (2020) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2020.103541 · Cited by 1,246
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Metadata
- Authors
- Dhiman, G., & Kumar, V.
- Venue
- Knowledge-Based Systems
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 159
- Pages
- 20-50
- ISSN
- 0950-7051 (ISSN-L)
- OpenAlex
- W2807821935
- Cited by
- 720
- References
- 52
- FWCI
- 44.13
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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