Application of a Parallel Adaptive Cuckoo Search Algorithm in the Rectangle Layout Problem Article Swipe
Weimin Zheng
,
Mingchao Si
,
Xiao Sui
,
Shu‐Chuan Chu
,
Jeng‐Shyang Pan
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.32604/cmes.2023.019890
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.32604/cmes.2023.019890
The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution. It has good performance in global optimization fields such as maximization. In this paper, a new adaptive parameter strategy and a parallel communication strategy are proposed to further improve the Cuckoo Search (CS) algorithm. This strategy greatly improves the convergence speed and accuracy of the algorithm and strengthens the algorithm’s ability to jump out of the local optimal. This paper compares the optimization performance of Parallel Adaptive Cuckoo Search (PACS) with CS, Parallel Cuckoo Search (PCS), Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), Differential Evolution (DE) and Artificial Bee Colony (ABC) algorithms by using the CEC-2013 test function. The results show that PACS algorithm outperforms other algorithms in 20 of 28 test functions. Due to the superior performance of PACS algorithm, this paper uses it to solve the problem of the rectangular layout. Experimental results show that this scheme has a significant effect, and the material utilization rate is improved from 89.5% to 97.8% after optimization.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.32604/cmes.2023.019890
- https://file.techscience.com/ueditor/files/cmes/TSP_CMES-135-3/TSP_CMES_19890/TSP_CMES_19890.pdf
- OA Status
- diamond
- Cited By
- 3
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4309838237
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4309838237Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.32604/cmes.2023.019890Digital Object Identifier
- Title
-
Application of a Parallel Adaptive Cuckoo Search Algorithm in the Rectangle Layout ProblemWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-23Full publication date if available
- Authors
-
Weimin Zheng, Mingchao Si, Xiao Sui, Shu‐Chuan Chu, Jeng‐Shyang PanList of authors in order
- Landing page
-
https://doi.org/10.32604/cmes.2023.019890Publisher landing page
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https://file.techscience.com/ueditor/files/cmes/TSP_CMES-135-3/TSP_CMES_19890/TSP_CMES_19890.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
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https://file.techscience.com/ueditor/files/cmes/TSP_CMES-135-3/TSP_CMES_19890/TSP_CMES_19890.pdfDirect OA link when available
- Concepts
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Cuckoo search, Algorithm, Mathematical optimization, Computer science, Particle swarm optimization, Local search (optimization), Metaheuristic, Convergence (economics), Differential evolution, Mathematics, Economics, Economic growthTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 1, 2023: 1Per-year citation counts (last 5 years)
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70Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2913222812, https://openalex.org/W2314506207, https://openalex.org/W3010701680, https://openalex.org/W3013894079, https://openalex.org/W2030852225, https://openalex.org/W2085821381, https://openalex.org/W3094988667, https://openalex.org/W2039911195, https://openalex.org/W360308577, https://openalex.org/W2153879578, https://openalex.org/W6683338177, https://openalex.org/W2481194649, https://openalex.org/W3010558631, https://openalex.org/W3028989299, https://openalex.org/W2997318772, https://openalex.org/W2808768729, https://openalex.org/W2800318665, https://openalex.org/W4200506698, https://openalex.org/W2755257648, https://openalex.org/W2064995481, https://openalex.org/W6686097346, https://openalex.org/W3128420816, https://openalex.org/W3134245392, https://openalex.org/W2784329509, https://openalex.org/W6749282785, https://openalex.org/W1976744965, https://openalex.org/W18303278, https://openalex.org/W2753354457, https://openalex.org/W2049999744, https://openalex.org/W2329556607, https://openalex.org/W2094074979, https://openalex.org/W6603426030, https://openalex.org/W4250685322, https://openalex.org/W2986150947, https://openalex.org/W889051524, https://openalex.org/W2030346487, https://openalex.org/W2127607949, https://openalex.org/W2092589833, https://openalex.org/W4205803874, https://openalex.org/W2917884856, https://openalex.org/W6682642761, https://openalex.org/W2232317135, https://openalex.org/W2290883490, https://openalex.org/W2061438946, https://openalex.org/W2287814884, https://openalex.org/W1595159159, https://openalex.org/W2163535042, https://openalex.org/W6675949924, https://openalex.org/W2025427163, https://openalex.org/W91859521, https://openalex.org/W2009064545, https://openalex.org/W2105175235, https://openalex.org/W2131695829, https://openalex.org/W6679807127, https://openalex.org/W3202214494, https://openalex.org/W3196491814, https://openalex.org/W3134719405, https://openalex.org/W2082759946, https://openalex.org/W3214275271, https://openalex.org/W4205387711, https://openalex.org/W4200308385, https://openalex.org/W3041194909, https://openalex.org/W2917796313, https://openalex.org/W2103619936, https://openalex.org/W3197788851, https://openalex.org/W2181891850, https://openalex.org/W1526544557, https://openalex.org/W4362597634, https://openalex.org/W4253484285, https://openalex.org/W4365806373 |
| referenced_works_count | 70 |
| abstract_inverted_index.a | 4, 27, 33, 162 |
| abstract_inverted_index.20 | 130 |
| abstract_inverted_index.28 | 132 |
| abstract_inverted_index.In | 24 |
| abstract_inverted_index.It | 13 |
| abstract_inverted_index.as | 22 |
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| abstract_inverted_index.in | 17, 129 |
| abstract_inverted_index.is | 3, 170 |
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| abstract_inverted_index.of | 56, 67, 77, 131, 140, 151 |
| abstract_inverted_index.to | 39, 64, 136, 147, 174 |
| abstract_inverted_index.Bee | 110 |
| abstract_inverted_index.CS, | 84 |
| abstract_inverted_index.Due | 135 |
| abstract_inverted_index.The | 0, 120 |
| abstract_inverted_index.and | 32, 54, 59, 108, 165 |
| abstract_inverted_index.are | 37 |
| abstract_inverted_index.for | 9 |
| abstract_inverted_index.has | 14, 161 |
| abstract_inverted_index.new | 28 |
| abstract_inverted_index.out | 66 |
| abstract_inverted_index.the | 10, 42, 51, 57, 61, 68, 74, 116, 137, 149, 152, 166 |
| abstract_inverted_index.(CS) | 45 |
| abstract_inverted_index.(DE) | 107 |
| abstract_inverted_index.Grey | 97 |
| abstract_inverted_index.PACS | 124, 141 |
| abstract_inverted_index.Sine | 93 |
| abstract_inverted_index.This | 47, 71 |
| abstract_inverted_index.Wolf | 98 |
| abstract_inverted_index.from | 172 |
| abstract_inverted_index.good | 15 |
| abstract_inverted_index.jump | 65 |
| abstract_inverted_index.rate | 169 |
| abstract_inverted_index.show | 122, 157 |
| abstract_inverted_index.such | 21 |
| abstract_inverted_index.test | 118, 133 |
| abstract_inverted_index.that | 123, 158 |
| abstract_inverted_index.this | 25, 143, 159 |
| abstract_inverted_index.uses | 145 |
| abstract_inverted_index.with | 83 |
| abstract_inverted_index.(ABC) | 112 |
| abstract_inverted_index.89.5% | 173 |
| abstract_inverted_index.97.8% | 175 |
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| abstract_inverted_index.Whale | 101 |
| abstract_inverted_index.after | 176 |
| abstract_inverted_index.local | 69 |
| abstract_inverted_index.other | 127 |
| abstract_inverted_index.paper | 72, 144 |
| abstract_inverted_index.solve | 148 |
| abstract_inverted_index.speed | 53 |
| abstract_inverted_index.using | 115 |
| abstract_inverted_index.(GWO), | 100 |
| abstract_inverted_index.(PACS) | 82 |
| abstract_inverted_index.(PCS), | 88 |
| abstract_inverted_index.(PSO), | 92 |
| abstract_inverted_index.(SCA), | 96 |
| abstract_inverted_index.(WOA), | 104 |
| abstract_inverted_index.Colony | 111 |
| abstract_inverted_index.Cosine | 94 |
| abstract_inverted_index.Cuckoo | 43, 80, 86 |
| abstract_inverted_index.Search | 44, 81, 87 |
| abstract_inverted_index.fields | 20 |
| abstract_inverted_index.global | 5, 18 |
| abstract_inverted_index.paper, | 26 |
| abstract_inverted_index.scheme | 160 |
| abstract_inverted_index.search | 7 |
| abstract_inverted_index.ability | 63 |
| abstract_inverted_index.effect, | 164 |
| abstract_inverted_index.further | 40 |
| abstract_inverted_index.greatly | 49 |
| abstract_inverted_index.improve | 41 |
| abstract_inverted_index.layout. | 154 |
| abstract_inverted_index.problem | 150 |
| abstract_inverted_index.results | 121, 156 |
| abstract_inverted_index.Adaptive | 79 |
| abstract_inverted_index.CEC-2013 | 117 |
| abstract_inverted_index.Parallel | 78, 85 |
| abstract_inverted_index.Particle | 89 |
| abstract_inverted_index.accuracy | 55 |
| abstract_inverted_index.adaptive | 29 |
| abstract_inverted_index.compares | 73 |
| abstract_inverted_index.improved | 171 |
| abstract_inverted_index.improves | 50 |
| abstract_inverted_index.material | 167 |
| abstract_inverted_index.optimal. | 70 |
| abstract_inverted_index.parallel | 34 |
| abstract_inverted_index.proposed | 38 |
| abstract_inverted_index.strategy | 31, 36, 48 |
| abstract_inverted_index.superior | 138 |
| abstract_inverted_index.Algorithm | 95, 103 |
| abstract_inverted_index.Evolution | 106 |
| abstract_inverted_index.Optimizer | 99 |
| abstract_inverted_index.algorithm | 2, 8, 58, 125 |
| abstract_inverted_index.function. | 119 |
| abstract_inverted_index.iterative | 11 |
| abstract_inverted_index.parameter | 30 |
| abstract_inverted_index.solution. | 12 |
| abstract_inverted_index.Artificial | 109 |
| abstract_inverted_index.algorithm, | 142 |
| abstract_inverted_index.algorithm. | 46 |
| abstract_inverted_index.algorithms | 113, 128 |
| abstract_inverted_index.functions. | 134 |
| abstract_inverted_index.convergence | 52 |
| abstract_inverted_index.outperforms | 126 |
| abstract_inverted_index.performance | 16, 76, 139 |
| abstract_inverted_index.rectangular | 153 |
| abstract_inverted_index.significant | 163 |
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| abstract_inverted_index.Experimental | 155 |
| abstract_inverted_index.Optimization | 91, 102 |
| abstract_inverted_index.optimization | 19, 75 |
| abstract_inverted_index.algorithm’s | 62 |
| abstract_inverted_index.communication | 35 |
| abstract_inverted_index.maximization. | 23 |
| abstract_inverted_index.optimization. | 177 |
| abstract_inverted_index.probabilistic | 6 |
| abstract_inverted_index.meta-heuristic | 1 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5019810689 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I80143920 |
| citation_normalized_percentile.value | 0.69153452 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |