Optimal location of logistics distribution centres with swarm intelligent clustering algorithms Article Swipe
Tsung‐Xian Lin
,
Zhong-huan Wu
,
Wen‐Tsao Pan
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0271928
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0271928
A clustering algorithm is a solution for grouping a set of objects and for distribution centre location problems. But the common K-means clustering algorithm may give local optimal solutions. Swarm intelligent algorithms simulate the social behaviours of animals and avoid local optimal solutions. We employ three swarm intelligent algorithms to avoid these solutions. We propose a new algorithm for the clustering problem, the fruit-fly optimization K-means algorithm (FOA K-means). We designed a distribution centre location problem and three clustering indicators to evaluate the performance of algorithms. We compare the algorithms of K-means with the ant colony optimization algorithm (ACO K-means), particle swarm optimization algorithm (PSO K-means), and fruit-fly optimization algorithm. We find K-Means modified by the fruit-fly optimization algorithm (FOA K-means) has the best performance on convergence speed and three clustering indicators, compactness, separation, and integration. Thus, we can apply FOA K-means to improve the distribution centre location solution and the efficiency for distribution in the future.
Related Topics
Concepts
Cluster analysis
Particle swarm optimization
Computer science
Ant colony optimization algorithms
Algorithm
Convergence (economics)
Canopy clustering algorithm
Swarm behaviour
Multi-swarm optimization
Mathematical optimization
Metaheuristic
Set (abstract data type)
Swarm intelligence
Distribution (mathematics)
CURE data clustering algorithm
k-means clustering
Correlation clustering
Mathematics
Artificial intelligence
Economic growth
Mathematical analysis
Economics
Programming language
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0271928
- https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0271928&type=printable
- OA Status
- gold
- Cited By
- 10
- References
- 43
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4293242230
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4293242230Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1371/journal.pone.0271928Digital Object Identifier
- Title
-
Optimal location of logistics distribution centres with swarm intelligent clustering algorithmsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-08-25Full publication date if available
- Authors
-
Tsung‐Xian Lin, Zhong-huan Wu, Wen‐Tsao PanList of authors in order
- Landing page
-
https://doi.org/10.1371/journal.pone.0271928Publisher landing page
- PDF URL
-
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0271928&type=printableDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0271928&type=printableDirect OA link when available
- Concepts
-
Cluster analysis, Particle swarm optimization, Computer science, Ant colony optimization algorithms, Algorithm, Convergence (economics), Canopy clustering algorithm, Swarm behaviour, Multi-swarm optimization, Mathematical optimization, Metaheuristic, Set (abstract data type), Swarm intelligence, Distribution (mathematics), CURE data clustering algorithm, k-means clustering, Correlation clustering, Mathematics, Artificial intelligence, Economic growth, Mathematical analysis, Economics, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 4, 2023: 4Per-year citation counts (last 5 years)
- References (count)
-
43Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4293242230 |
|---|---|
| doi | https://doi.org/10.1371/journal.pone.0271928 |
| ids.doi | https://doi.org/10.1371/journal.pone.0271928 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/36007089 |
| ids.openalex | https://openalex.org/W4293242230 |
| fwci | 1.9579882 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D000465 |
| mesh[0].is_major_topic | True |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Algorithms |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D000818 |
| mesh[1].is_major_topic | False |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Animals |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D016000 |
| mesh[2].is_major_topic | False |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Cluster Analysis |
| mesh[3].qualifier_ui | |
| mesh[3].descriptor_ui | D004330 |
| mesh[3].is_major_topic | True |
| mesh[3].qualifier_name | |
| mesh[3].descriptor_name | Drosophila |
| mesh[4].qualifier_ui | |
| mesh[4].descriptor_ui | D000465 |
| mesh[4].is_major_topic | True |
| mesh[4].qualifier_name | |
| mesh[4].descriptor_name | Algorithms |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D000818 |
| mesh[5].is_major_topic | False |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Animals |
| mesh[6].qualifier_ui | |
| mesh[6].descriptor_ui | D016000 |
| mesh[6].is_major_topic | False |
| mesh[6].qualifier_name | |
| mesh[6].descriptor_name | Cluster Analysis |
| mesh[7].qualifier_ui | |
| mesh[7].descriptor_ui | D004330 |
| mesh[7].is_major_topic | True |
| mesh[7].qualifier_name | |
| mesh[7].descriptor_name | Drosophila |
| type | article |
| title | Optimal location of logistics distribution centres with swarm intelligent clustering algorithms |
| biblio.issue | 8 |
| biblio.volume | 17 |
| biblio.last_page | e0271928 |
| biblio.first_page | e0271928 |
| topics[0].id | https://openalex.org/T10100 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9983000159263611 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Metaheuristic Optimization Algorithms Research |
| topics[1].id | https://openalex.org/T12391 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9861999750137329 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2204 |
| topics[1].subfield.display_name | Biomedical Engineering |
| topics[1].display_name | Artificial Immune Systems Applications |
| topics[2].id | https://openalex.org/T11106 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9757000207901001 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1711 |
| topics[2].subfield.display_name | Signal Processing |
| topics[2].display_name | Data Management and Algorithms |
| is_xpac | False |
| apc_list.value | 1805 |
| apc_list.currency | USD |
| apc_list.value_usd | 1805 |
| apc_paid.value | 1805 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1805 |
| concepts[0].id | https://openalex.org/C73555534 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8406500220298767 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q622825 |
| concepts[0].display_name | Cluster analysis |
| concepts[1].id | https://openalex.org/C85617194 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7416203022003174 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q2072794 |
| concepts[1].display_name | Particle swarm optimization |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.6216602325439453 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C40128228 |
| concepts[3].level | 2 |
| concepts[3].score | 0.6133765578269958 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q460851 |
| concepts[3].display_name | Ant colony optimization algorithms |
| concepts[4].id | https://openalex.org/C11413529 |
| concepts[4].level | 1 |
| concepts[4].score | 0.5952131748199463 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[4].display_name | Algorithm |
| concepts[5].id | https://openalex.org/C2777303404 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5876570343971252 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q759757 |
| concepts[5].display_name | Convergence (economics) |
| concepts[6].id | https://openalex.org/C104047586 |
| concepts[6].level | 4 |
| concepts[6].score | 0.5531904101371765 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q5033439 |
| concepts[6].display_name | Canopy clustering algorithm |
| concepts[7].id | https://openalex.org/C181335050 |
| concepts[7].level | 2 |
| concepts[7].score | 0.5253055691719055 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q14915018 |
| concepts[7].display_name | Swarm behaviour |
| concepts[8].id | https://openalex.org/C122357587 |
| concepts[8].level | 3 |
| concepts[8].score | 0.518406867980957 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q6934508 |
| concepts[8].display_name | Multi-swarm optimization |
| concepts[9].id | https://openalex.org/C126255220 |
| concepts[9].level | 1 |
| concepts[9].score | 0.5023531913757324 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q141495 |
| concepts[9].display_name | Mathematical optimization |
| concepts[10].id | https://openalex.org/C109718341 |
| concepts[10].level | 2 |
| concepts[10].score | 0.49262768030166626 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q1385229 |
| concepts[10].display_name | Metaheuristic |
| concepts[11].id | https://openalex.org/C177264268 |
| concepts[11].level | 2 |
| concepts[11].score | 0.47054794430732727 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1514741 |
| concepts[11].display_name | Set (abstract data type) |
| concepts[12].id | https://openalex.org/C119487961 |
| concepts[12].level | 3 |
| concepts[12].score | 0.4275001287460327 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q863960 |
| concepts[12].display_name | Swarm intelligence |
| concepts[13].id | https://openalex.org/C110121322 |
| concepts[13].level | 2 |
| concepts[13].score | 0.4272741973400116 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q865811 |
| concepts[13].display_name | Distribution (mathematics) |
| concepts[14].id | https://openalex.org/C33704608 |
| concepts[14].level | 4 |
| concepts[14].score | 0.4201880693435669 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q5014717 |
| concepts[14].display_name | CURE data clustering algorithm |
| concepts[15].id | https://openalex.org/C207968372 |
| concepts[15].level | 3 |
| concepts[15].score | 0.4194904863834381 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q310401 |
| concepts[15].display_name | k-means clustering |
| concepts[16].id | https://openalex.org/C94641424 |
| concepts[16].level | 3 |
| concepts[16].score | 0.35990267992019653 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q5172845 |
| concepts[16].display_name | Correlation clustering |
| concepts[17].id | https://openalex.org/C33923547 |
| concepts[17].level | 0 |
| concepts[17].score | 0.25415411591529846 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[17].display_name | Mathematics |
| concepts[18].id | https://openalex.org/C154945302 |
| concepts[18].level | 1 |
| concepts[18].score | 0.17530369758605957 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[18].display_name | Artificial intelligence |
| concepts[19].id | https://openalex.org/C50522688 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q189833 |
| concepts[19].display_name | Economic growth |
| concepts[20].id | https://openalex.org/C134306372 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q7754 |
| concepts[20].display_name | Mathematical analysis |
| concepts[21].id | https://openalex.org/C162324750 |
| concepts[21].level | 0 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[21].display_name | Economics |
| concepts[22].id | https://openalex.org/C199360897 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[22].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/cluster-analysis |
| keywords[0].score | 0.8406500220298767 |
| keywords[0].display_name | Cluster analysis |
| keywords[1].id | https://openalex.org/keywords/particle-swarm-optimization |
| keywords[1].score | 0.7416203022003174 |
| keywords[1].display_name | Particle swarm optimization |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.6216602325439453 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/ant-colony-optimization-algorithms |
| keywords[3].score | 0.6133765578269958 |
| keywords[3].display_name | Ant colony optimization algorithms |
| keywords[4].id | https://openalex.org/keywords/algorithm |
| keywords[4].score | 0.5952131748199463 |
| keywords[4].display_name | Algorithm |
| keywords[5].id | https://openalex.org/keywords/convergence |
| keywords[5].score | 0.5876570343971252 |
| keywords[5].display_name | Convergence (economics) |
| keywords[6].id | https://openalex.org/keywords/canopy-clustering-algorithm |
| keywords[6].score | 0.5531904101371765 |
| keywords[6].display_name | Canopy clustering algorithm |
| keywords[7].id | https://openalex.org/keywords/swarm-behaviour |
| keywords[7].score | 0.5253055691719055 |
| keywords[7].display_name | Swarm behaviour |
| keywords[8].id | https://openalex.org/keywords/multi-swarm-optimization |
| keywords[8].score | 0.518406867980957 |
| keywords[8].display_name | Multi-swarm optimization |
| keywords[9].id | https://openalex.org/keywords/mathematical-optimization |
| keywords[9].score | 0.5023531913757324 |
| keywords[9].display_name | Mathematical optimization |
| keywords[10].id | https://openalex.org/keywords/metaheuristic |
| keywords[10].score | 0.49262768030166626 |
| keywords[10].display_name | Metaheuristic |
| keywords[11].id | https://openalex.org/keywords/set |
| keywords[11].score | 0.47054794430732727 |
| keywords[11].display_name | Set (abstract data type) |
| keywords[12].id | https://openalex.org/keywords/swarm-intelligence |
| keywords[12].score | 0.4275001287460327 |
| keywords[12].display_name | Swarm intelligence |
| keywords[13].id | https://openalex.org/keywords/distribution |
| keywords[13].score | 0.4272741973400116 |
| keywords[13].display_name | Distribution (mathematics) |
| keywords[14].id | https://openalex.org/keywords/cure-data-clustering-algorithm |
| keywords[14].score | 0.4201880693435669 |
| keywords[14].display_name | CURE data clustering algorithm |
| keywords[15].id | https://openalex.org/keywords/k-means-clustering |
| keywords[15].score | 0.4194904863834381 |
| keywords[15].display_name | k-means clustering |
| keywords[16].id | https://openalex.org/keywords/correlation-clustering |
| keywords[16].score | 0.35990267992019653 |
| keywords[16].display_name | Correlation clustering |
| keywords[17].id | https://openalex.org/keywords/mathematics |
| keywords[17].score | 0.25415411591529846 |
| keywords[17].display_name | Mathematics |
| keywords[18].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[18].score | 0.17530369758605957 |
| keywords[18].display_name | Artificial intelligence |
| language | en |
| locations[0].id | doi:10.1371/journal.pone.0271928 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S202381698 |
| locations[0].source.issn | 1932-6203 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1932-6203 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | PLoS ONE |
| locations[0].source.host_organization | https://openalex.org/P4310315706 |
| locations[0].source.host_organization_name | Public Library of Science |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310315706 |
| locations[0].source.host_organization_lineage_names | Public Library of Science |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0271928&type=printable |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | PLOS ONE |
| locations[0].landing_page_url | https://doi.org/10.1371/journal.pone.0271928 |
| locations[1].id | pmid:36007089 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | PloS one |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/36007089 |
| locations[2].id | pmh:oai:doaj.org/article:f42a857e11974c02904048e86271986e |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-sa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | PLoS ONE, Vol 17, Iss 8, p e0271928 (2022) |
| locations[2].landing_page_url | https://doaj.org/article/f42a857e11974c02904048e86271986e |
| locations[3].id | pmh:oai:pubmedcentral.nih.gov:9409525 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S2764455111 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | PubMed Central |
| locations[3].source.host_organization | https://openalex.org/I1299303238 |
| locations[3].source.host_organization_name | National Institutes of Health |
| locations[3].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[3].license | other-oa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/other-oa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | PLoS One |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/9409525 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5064633628 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-6558-9114 |
| authorships[0].author.display_name | Tsung‐Xian Lin |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4400573295 |
| authorships[0].affiliations[0].raw_affiliation_string | Institute for Economic and Social Research, Guangzhou Huashang College, Guangzhou, China |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I4210113138, https://openalex.org/I4400573295 |
| authorships[0].affiliations[1].raw_affiliation_string | Department of Management, Guangzhou Huashang College, Guangzhou, China |
| authorships[0].institutions[0].id | https://openalex.org/I4400573295 |
| authorships[0].institutions[0].ror | https://ror.org/0546x0d08 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I4400573295 |
| authorships[0].institutions[0].country_code | |
| authorships[0].institutions[0].display_name | Guangzhou Huashang College |
| authorships[0].institutions[1].id | https://openalex.org/I4210113138 |
| authorships[0].institutions[1].ror | https://ror.org/026fzn952 |
| authorships[0].institutions[1].type | company |
| authorships[0].institutions[1].lineage | https://openalex.org/I4210113138 |
| authorships[0].institutions[1].country_code | CN |
| authorships[0].institutions[1].display_name | Guangzhou Automobile Group (China) |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Tsung-Xian Lin |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Management, Guangzhou Huashang College, Guangzhou, China, Institute for Economic and Social Research, Guangzhou Huashang College, Guangzhou, China |
| authorships[1].author.id | https://openalex.org/A5020787211 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-6133-8297 |
| authorships[1].author.display_name | Zhong-huan Wu |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210113138, https://openalex.org/I4400573295 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Management, Guangzhou Huashang College, Guangzhou, China |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I4400573295 |
| authorships[1].affiliations[1].raw_affiliation_string | Institute for Economic and Social Research, Guangzhou Huashang College, Guangzhou, China |
| authorships[1].institutions[0].id | https://openalex.org/I4400573295 |
| authorships[1].institutions[0].ror | https://ror.org/0546x0d08 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I4400573295 |
| authorships[1].institutions[0].country_code | |
| authorships[1].institutions[0].display_name | Guangzhou Huashang College |
| authorships[1].institutions[1].id | https://openalex.org/I4210113138 |
| authorships[1].institutions[1].ror | https://ror.org/026fzn952 |
| authorships[1].institutions[1].type | company |
| authorships[1].institutions[1].lineage | https://openalex.org/I4210113138 |
| authorships[1].institutions[1].country_code | CN |
| authorships[1].institutions[1].display_name | Guangzhou Automobile Group (China) |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Zhong-huan Wu |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | Department of Management, Guangzhou Huashang College, Guangzhou, China, Institute for Economic and Social Research, Guangzhou Huashang College, Guangzhou, China |
| authorships[2].author.id | https://openalex.org/A5100785652 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-0999-5257 |
| authorships[2].author.display_name | Wen‐Tsao Pan |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I186272606 |
| authorships[2].affiliations[0].raw_affiliation_string | School of business, Guangdong University of Foreign Studies, Guangzhou, China |
| authorships[2].institutions[0].id | https://openalex.org/I186272606 |
| authorships[2].institutions[0].ror | https://ror.org/00fhc9y79 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I186272606 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Guangdong University of Foreign Studies |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Wen-Tsao Pan |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of business, Guangdong University of Foreign Studies, Guangzhou, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0271928&type=printable |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Optimal location of logistics distribution centres with swarm intelligent clustering algorithms |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10100 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9983000159263611 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Metaheuristic Optimization Algorithms Research |
| related_works | https://openalex.org/W2559422900, https://openalex.org/W3144143113, https://openalex.org/W4306940721, https://openalex.org/W3022637481, https://openalex.org/W3120229345, https://openalex.org/W2160785859, https://openalex.org/W2491448268, https://openalex.org/W2738096727, https://openalex.org/W2374506950, https://openalex.org/W1584028106 |
| cited_by_count | 10 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 4 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 4 |
| locations_count | 4 |
| best_oa_location.id | doi:10.1371/journal.pone.0271928 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S202381698 |
| best_oa_location.source.issn | 1932-6203 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1932-6203 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | PLoS ONE |
| best_oa_location.source.host_organization | https://openalex.org/P4310315706 |
| best_oa_location.source.host_organization_name | Public Library of Science |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310315706 |
| best_oa_location.source.host_organization_lineage_names | Public Library of Science |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0271928&type=printable |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | PLOS ONE |
| best_oa_location.landing_page_url | https://doi.org/10.1371/journal.pone.0271928 |
| primary_location.id | doi:10.1371/journal.pone.0271928 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S202381698 |
| primary_location.source.issn | 1932-6203 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1932-6203 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | PLoS ONE |
| primary_location.source.host_organization | https://openalex.org/P4310315706 |
| primary_location.source.host_organization_name | Public Library of Science |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310315706 |
| primary_location.source.host_organization_lineage_names | Public Library of Science |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0271928&type=printable |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | PLOS ONE |
| primary_location.landing_page_url | https://doi.org/10.1371/journal.pone.0271928 |
| publication_date | 2022-08-25 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2758354840, https://openalex.org/W6718670374, https://openalex.org/W6760895094, https://openalex.org/W6753110908, https://openalex.org/W2183140507, https://openalex.org/W2013723438, https://openalex.org/W2766555770, https://openalex.org/W3018825249, https://openalex.org/W1987741571, https://openalex.org/W2841402245, https://openalex.org/W2809007828, https://openalex.org/W2909060208, https://openalex.org/W2766534319, https://openalex.org/W2129066856, https://openalex.org/W4211177544, https://openalex.org/W1981903823, https://openalex.org/W1990368529, https://openalex.org/W1987971958, https://openalex.org/W2085487226, https://openalex.org/W101836494, https://openalex.org/W1983494083, https://openalex.org/W2137654055, https://openalex.org/W1977556410, https://openalex.org/W4301173492, https://openalex.org/W2035364453, https://openalex.org/W2103868202, https://openalex.org/W2543580944, https://openalex.org/W4292083457, https://openalex.org/W2163163936, https://openalex.org/W2749827977, https://openalex.org/W2750762343, https://openalex.org/W3126523341, https://openalex.org/W2888679805, https://openalex.org/W2915022649, https://openalex.org/W2889376548, https://openalex.org/W2152195021, https://openalex.org/W2092294827, https://openalex.org/W2884992769, https://openalex.org/W2964095005, https://openalex.org/W4288418027, https://openalex.org/W2487955119, https://openalex.org/W2071949631, https://openalex.org/W3021096642 |
| referenced_works_count | 43 |
| abstract_inverted_index.A | 0 |
| abstract_inverted_index.a | 4, 8, 55, 71 |
| abstract_inverted_index.We | 43, 53, 69, 86, 110 |
| abstract_inverted_index.by | 114 |
| abstract_inverted_index.in | 154 |
| abstract_inverted_index.is | 3 |
| abstract_inverted_index.of | 10, 36, 84, 90 |
| abstract_inverted_index.on | 125 |
| abstract_inverted_index.to | 49, 80, 142 |
| abstract_inverted_index.we | 137 |
| abstract_inverted_index.But | 18 |
| abstract_inverted_index.FOA | 140 |
| abstract_inverted_index.and | 12, 38, 76, 106, 128, 134, 149 |
| abstract_inverted_index.ant | 94 |
| abstract_inverted_index.can | 138 |
| abstract_inverted_index.for | 6, 13, 58, 152 |
| abstract_inverted_index.has | 121 |
| abstract_inverted_index.may | 24 |
| abstract_inverted_index.new | 56 |
| abstract_inverted_index.set | 9 |
| abstract_inverted_index.the | 19, 33, 59, 62, 82, 88, 93, 115, 122, 144, 150, 155 |
| abstract_inverted_index.(ACO | 98 |
| abstract_inverted_index.(FOA | 67, 119 |
| abstract_inverted_index.(PSO | 104 |
| abstract_inverted_index.best | 123 |
| abstract_inverted_index.find | 111 |
| abstract_inverted_index.give | 25 |
| abstract_inverted_index.with | 92 |
| abstract_inverted_index.Swarm | 29 |
| abstract_inverted_index.Thus, | 136 |
| abstract_inverted_index.apply | 139 |
| abstract_inverted_index.avoid | 39, 50 |
| abstract_inverted_index.local | 26, 40 |
| abstract_inverted_index.speed | 127 |
| abstract_inverted_index.swarm | 46, 101 |
| abstract_inverted_index.these | 51 |
| abstract_inverted_index.three | 45, 77, 129 |
| abstract_inverted_index.centre | 15, 73, 146 |
| abstract_inverted_index.colony | 95 |
| abstract_inverted_index.common | 20 |
| abstract_inverted_index.employ | 44 |
| abstract_inverted_index.social | 34 |
| abstract_inverted_index.K-Means | 112 |
| abstract_inverted_index.K-means | 21, 65, 91, 141 |
| abstract_inverted_index.animals | 37 |
| abstract_inverted_index.compare | 87 |
| abstract_inverted_index.future. | 156 |
| abstract_inverted_index.improve | 143 |
| abstract_inverted_index.objects | 11 |
| abstract_inverted_index.optimal | 27, 41 |
| abstract_inverted_index.problem | 75 |
| abstract_inverted_index.propose | 54 |
| abstract_inverted_index.K-means) | 120 |
| abstract_inverted_index.designed | 70 |
| abstract_inverted_index.evaluate | 81 |
| abstract_inverted_index.grouping | 7 |
| abstract_inverted_index.location | 16, 74, 147 |
| abstract_inverted_index.modified | 113 |
| abstract_inverted_index.particle | 100 |
| abstract_inverted_index.problem, | 61 |
| abstract_inverted_index.simulate | 32 |
| abstract_inverted_index.solution | 5, 148 |
| abstract_inverted_index.K-means), | 99, 105 |
| abstract_inverted_index.K-means). | 68 |
| abstract_inverted_index.algorithm | 2, 23, 57, 66, 97, 103, 118 |
| abstract_inverted_index.fruit-fly | 63, 107, 116 |
| abstract_inverted_index.problems. | 17 |
| abstract_inverted_index.algorithm. | 109 |
| abstract_inverted_index.algorithms | 31, 48, 89 |
| abstract_inverted_index.behaviours | 35 |
| abstract_inverted_index.clustering | 1, 22, 60, 78, 130 |
| abstract_inverted_index.efficiency | 151 |
| abstract_inverted_index.indicators | 79 |
| abstract_inverted_index.solutions. | 28, 42, 52 |
| abstract_inverted_index.algorithms. | 85 |
| abstract_inverted_index.convergence | 126 |
| abstract_inverted_index.indicators, | 131 |
| abstract_inverted_index.intelligent | 30, 47 |
| abstract_inverted_index.performance | 83, 124 |
| abstract_inverted_index.separation, | 133 |
| abstract_inverted_index.compactness, | 132 |
| abstract_inverted_index.distribution | 14, 72, 145, 153 |
| abstract_inverted_index.integration. | 135 |
| abstract_inverted_index.optimization | 64, 96, 102, 108, 117 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 95 |
| corresponding_author_ids | https://openalex.org/A5020787211 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| corresponding_institution_ids | https://openalex.org/I4210113138, https://openalex.org/I4400573295 |
| citation_normalized_percentile.value | 0.84822322 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |