Artificial Bee Colony Optimization Algorithm with New Full Dimension Updating Strategy and Its Application Article Swipe
Yuangang Li
,
Xinrui GAO
,
Yingjie Song
,
Wu Deng
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4013944/v1
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-4013944/v1
For the low accuracy and slow convergence of artificial bee colony (ABC) algorithm in solving complex optimization problems, a new full dimensional updating ABC/best/1 evolutionary strategy is designed to propose an improved ABC based on the new full dimensional updating strategy(FNABC) in this paper. Because of the low efficiency of one-dimensional search, the full dimensional update search strategy and ABC/best /1 evolutionary strategy are used to design a new full dimensional update ABC/best/1 evolutionary strategy, which expands the search space, improves the mining ability and search efficiency. And a new evolutionary phase of full dimensional update strategy is designed to balance the global search ability and mining ability. Finally, the FNABC is compared with eight state-of-the-art ABC variants in solving 12 functions. The experiment results indicate that the FNABC has better search ability. Additionally, the FNABC is applied to solve a real-world train operation adjustment problem. The results show that it can obtain the ideal results of the train operation adjustment problem.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-4013944/v1
- https://www.researchsquare.com/article/rs-4013944/latest.pdf
- OA Status
- green
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392756831
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392756831Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-4013944/v1Digital Object Identifier
- Title
-
Artificial Bee Colony Optimization Algorithm with New Full Dimension Updating Strategy and Its ApplicationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-07Full publication date if available
- Authors
-
Yuangang Li, Xinrui GAO, Yingjie Song, Wu DengList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-4013944/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-4013944/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-4013944/latest.pdfDirect OA link when available
- Concepts
-
Dimension (graph theory), Artificial bee colony algorithm, Computer science, Optimization algorithm, Mathematical optimization, Fourth Dimension, Algorithm, Artificial intelligence, Mathematics, Combinatorics, Spacetime, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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31Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.solving | 15, 120 |
| abstract_inverted_index.ABC/best | 60 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Finally, | 109 |
| abstract_inverted_index.ability. | 108, 133 |
| abstract_inverted_index.accuracy | 4 |
| abstract_inverted_index.compared | 113 |
| abstract_inverted_index.designed | 28, 99 |
| abstract_inverted_index.improved | 32 |
| abstract_inverted_index.improves | 81 |
| abstract_inverted_index.indicate | 126 |
| abstract_inverted_index.problem. | 146, 162 |
| abstract_inverted_index.strategy | 26, 58, 63, 97 |
| abstract_inverted_index.updating | 23, 40 |
| abstract_inverted_index.variants | 118 |
| abstract_inverted_index.algorithm | 13 |
| abstract_inverted_index.operation | 144, 160 |
| abstract_inverted_index.problems, | 18 |
| abstract_inverted_index.strategy, | 75 |
| abstract_inverted_index.ABC/best/1 | 24, 73 |
| abstract_inverted_index.adjustment | 145, 161 |
| abstract_inverted_index.artificial | 9 |
| abstract_inverted_index.efficiency | 49 |
| abstract_inverted_index.experiment | 124 |
| abstract_inverted_index.functions. | 122 |
| abstract_inverted_index.real-world | 142 |
| abstract_inverted_index.convergence | 7 |
| abstract_inverted_index.dimensional | 22, 39, 55, 71, 95 |
| abstract_inverted_index.efficiency. | 87 |
| abstract_inverted_index.evolutionary | 25, 62, 74, 91 |
| abstract_inverted_index.optimization | 17 |
| abstract_inverted_index.Additionally, | 134 |
| abstract_inverted_index.one-dimensional | 51 |
| abstract_inverted_index.strategy(FNABC) | 41 |
| abstract_inverted_index.state-of-the-art | 116 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.04401437 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |