Single- and Multi-Objective Optimization Frameworks of Shape Design of Tubular Linear Synchronous Motor Article Swipe
Araby Mahdy
,
Abdullah M. Shaheen
,
Ragab A. El‐Sehiemy
,
Ahmed R. Ginidi
,
Saad F. Al‐Gahtani
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/en16052409
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/en16052409
The shape design of the Tubular Linear Synchronous Motor (TLSM) is a critical engineeri ng optimization problem which was handled as single- and multi-objective optimization frameworks. However, the different practical constraints for the TLSM design must be efficiently guaranteed. This paper proposes a developed multi-objective shape design of the TLSM to maximize the operating force and minimize the flux saturation. In this regard, a Multi-objective Grey Wolf Optimizer (MGWO) is developed, including an outside archive with a predetermined size that is integrated for storing and retrieving Pareto optimal solutions. Using this knowledge, the grey wolf social structure would then be established, and, in the multi-objective searching environments, grey wolf hunting behavior would then be replicated. The superiority and effectiveness of the developed MGWO is assessed in comparison to the Multi-objective Flower Pollination Algorithm (MFPA), Multi-objective Lichtenberg Algorithm (MOLA), and Multi-objective Grasshopper Optimization Algorithm (MGOA). The outcomes illustrate that the developed MGWO provides an average improvement of 73.46%, 19.07%, and 15.15% compared to MFPA, MOLA, and MGOA, respectively. The validation of the developed MGWO is extended for a multi-objective form of welded beam design (WBD) by simultaneously minimizing the deflection and the manufacturing costs. Similar findings are obtained with different reference points, the developed MGWO provides an average improvement of 2.8%, 0.7%, and 3.04% compared to MFPA, MOLA, and MGOA, respectively.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/en16052409
- https://www.mdpi.com/1996-1073/16/5/2409/pdf?version=1677821764
- OA Status
- gold
- Cited By
- 8
- References
- 55
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4323044432
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4323044432Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/en16052409Digital Object Identifier
- Title
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Single- and Multi-Objective Optimization Frameworks of Shape Design of Tubular Linear Synchronous MotorWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-03-02Full publication date if available
- Authors
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Araby Mahdy, Abdullah M. Shaheen, Ragab A. El‐Sehiemy, Ahmed R. Ginidi, Saad F. Al‐GahtaniList of authors in order
- Landing page
-
https://doi.org/10.3390/en16052409Publisher landing page
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https://www.mdpi.com/1996-1073/16/5/2409/pdf?version=1677821764Direct link to full text PDF
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/1996-1073/16/5/2409/pdf?version=1677821764Direct OA link when available
- Concepts
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Multi-objective optimization, Mathematical optimization, Computer science, Linear programming, Pareto principle, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2, 2023: 4Per-year citation counts (last 5 years)
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55Number 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/W6682642761, https://openalex.org/W3048311949, https://openalex.org/W4297198496, https://openalex.org/W3139484821, https://openalex.org/W4304690694, https://openalex.org/W4311723734, https://openalex.org/W3215102838, https://openalex.org/W4293213189, https://openalex.org/W3196661916, https://openalex.org/W4306377237, https://openalex.org/W2038659300, https://openalex.org/W2276743969, https://openalex.org/W2809587280, https://openalex.org/W3090396243, https://openalex.org/W4200073607, https://openalex.org/W1984762043, https://openalex.org/W2072955302, https://openalex.org/W2962182762, https://openalex.org/W3043211958, https://openalex.org/W1210381405, https://openalex.org/W2019091370, https://openalex.org/W3203480234, https://openalex.org/W2998757713, https://openalex.org/W2040786712, https://openalex.org/W3179665440, https://openalex.org/W3115290671, https://openalex.org/W4283725690, https://openalex.org/W3128772407, https://openalex.org/W2464411218, https://openalex.org/W2339349949, https://openalex.org/W2783580663, https://openalex.org/W2146439308, https://openalex.org/W3202542606, https://openalex.org/W2742961367, https://openalex.org/W3216947555, https://openalex.org/W3199882012, https://openalex.org/W2920992411, https://openalex.org/W4206716538, https://openalex.org/W3155620759, https://openalex.org/W4225131036, https://openalex.org/W2772966406, https://openalex.org/W2165171393, https://openalex.org/W2024383721, https://openalex.org/W2043371295, https://openalex.org/W2341858307, https://openalex.org/W2901122870, https://openalex.org/W3035428097, https://openalex.org/W2174096823, https://openalex.org/W4283325844, https://openalex.org/W6745554188, https://openalex.org/W4205375719, https://openalex.org/W2999332419, https://openalex.org/W4206574885, https://openalex.org/W2735292160, https://openalex.org/W2766724133 |
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| abstract_inverted_index.as | 20 |
| abstract_inverted_index.be | 36, 99, 113 |
| abstract_inverted_index.by | 184 |
| abstract_inverted_index.in | 102, 125 |
| abstract_inverted_index.is | 10, 69, 80, 123, 173 |
| abstract_inverted_index.ng | 14 |
| abstract_inverted_index.of | 3, 47, 119, 155, 169, 179, 208 |
| abstract_inverted_index.to | 50, 127, 161, 214 |
| abstract_inverted_index.The | 0, 115, 144, 167 |
| abstract_inverted_index.and | 22, 55, 84, 117, 138, 158, 164, 189, 211, 217 |
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| abstract_inverted_index.for | 31, 82, 175 |
| abstract_inverted_index.the | 4, 27, 32, 48, 52, 57, 92, 103, 120, 128, 148, 170, 187, 190, 201 |
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| abstract_inverted_index.TLSM | 33, 49 |
| abstract_inverted_index.This | 39 |
| abstract_inverted_index.Wolf | 66 |
| abstract_inverted_index.and, | 101 |
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| abstract_inverted_index.that | 79, 147 |
| abstract_inverted_index.then | 98, 112 |
| abstract_inverted_index.this | 61, 90 |
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| abstract_inverted_index.wolf | 94, 108 |
| abstract_inverted_index.(WBD) | 183 |
| abstract_inverted_index.0.7%, | 210 |
| abstract_inverted_index.2.8%, | 209 |
| abstract_inverted_index.3.04% | 212 |
| abstract_inverted_index.MFPA, | 162, 215 |
| abstract_inverted_index.MGOA, | 165, 218 |
| abstract_inverted_index.MOLA, | 163, 216 |
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| abstract_inverted_index.paper | 40 |
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| abstract_inverted_index.would | 97, 111 |
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| abstract_inverted_index.(TLSM) | 9 |
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| abstract_inverted_index.Linear | 6 |
| abstract_inverted_index.Pareto | 86 |
| abstract_inverted_index.costs. | 192 |
| abstract_inverted_index.design | 2, 34, 46, 182 |
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| abstract_inverted_index.welded | 180 |
| abstract_inverted_index.(MFPA), | 133 |
| abstract_inverted_index.(MGOA). | 143 |
| abstract_inverted_index.(MOLA), | 137 |
| abstract_inverted_index.19.07%, | 157 |
| abstract_inverted_index.73.46%, | 156 |
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| abstract_inverted_index.Tubular | 5 |
| abstract_inverted_index.archive | 74 |
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| abstract_inverted_index.points, | 200 |
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| abstract_inverted_index.regard, | 62 |
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| abstract_inverted_index.proposes | 41 |
| abstract_inverted_index.provides | 151, 204 |
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| abstract_inverted_index.including | 71 |
| abstract_inverted_index.operating | 53 |
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| abstract_inverted_index.knowledge, | 91 |
| abstract_inverted_index.minimizing | 186 |
| abstract_inverted_index.retrieving | 85 |
| abstract_inverted_index.solutions. | 88 |
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| abstract_inverted_index.Grasshopper | 140 |
| abstract_inverted_index.Lichtenberg | 135 |
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| abstract_inverted_index.saturation. | 59 |
| abstract_inverted_index.superiority | 116 |
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| abstract_inverted_index.respectively. | 166, 219 |
| abstract_inverted_index.simultaneously | 185 |
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| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5019940948 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I130309236 |
| citation_normalized_percentile.value | 0.78817136 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |