{"id":"https://openalex.org/W4407126725","doi":"https://doi.org/10.1007/s10791-025-09501-9","title":"Simulation optimization of supply chain uncertainty factors based on support vector machines optimized with improved Jellyfish Search Algorithm","display_name":"Simulation optimization of supply chain uncertainty factors based on support vector machines optimized with improved Jellyfish Search Algorithm","publication_year":2025,"publication_date":"2025-02-04","ids":{"openalex":"https://openalex.org/W4407126725","doi":"https://doi.org/10.1007/s10791-025-09501-9"},"language":"en","primary_location":{"id":"doi:10.1007/s10791-025-09501-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10791-025-09501-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09501-9.pdf","source":{"id":"https://openalex.org/S5407036663","display_name":"Discover Computing","issn_l":"2948-2992","issn":["2948-2992"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09501-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Xilong Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xilong Lin","raw_affiliation_strings":["School of Engineering, Huaqiao University, Quanzhou, Fujian, 362011, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Huaqiao University, Quanzhou, Fujian, 362011, China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100731525","display_name":"Jiabin Wang","orcid":"https://orcid.org/0000-0003-4870-3744"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiabin Wang","raw_affiliation_strings":["School of Engineering, Huaqiao University, Quanzhou, Fujian, 362011, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering, Huaqiao University, Quanzhou, Fujian, 362011, China","institution_ids":["https://openalex.org/I119045251"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100731525"],"corresponding_institution_ids":["https://openalex.org/I119045251"],"apc_list":null,"apc_paid":null,"fwci":8.2216,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.96586854,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"28","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11864","display_name":"Supply Chain Resilience and Risk Management","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11864","display_name":"Supply Chain Resilience and Risk Management","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/jellyfish","display_name":"Jellyfish","score":0.9454233646392822},{"id":"https://openalex.org/keywords/supply-chain","display_name":"Supply chain","score":0.6241440773010254},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5784135460853577},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5119627714157104},{"id":"https://openalex.org/keywords/optimization-algorithm","display_name":"Optimization algorithm","score":0.4989042282104492},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4836543798446655},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4265413284301758},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.20351624488830566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16203156113624573},{"id":"https://openalex.org/keywords/fishery","display_name":"Fishery","score":0.10210537910461426},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.07496747374534607},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.06695601344108582}],"concepts":[{"id":"https://openalex.org/C2779735984","wikidata":"https://www.wikidata.org/wiki/Q30178","display_name":"Jellyfish","level":2,"score":0.9454233646392822},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.6241440773010254},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5784135460853577},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5119627714157104},{"id":"https://openalex.org/C2987595161","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Optimization algorithm","level":2,"score":0.4989042282104492},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4836543798446655},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4265413284301758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20351624488830566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16203156113624573},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.10210537910461426},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.07496747374534607},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.06695601344108582},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10791-025-09501-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10791-025-09501-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09501-9.pdf","source":{"id":"https://openalex.org/S5407036663","display_name":"Discover Computing","issn_l":"2948-2992","issn":["2948-2992"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10791-025-09501-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10791-025-09501-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09501-9.pdf","source":{"id":"https://openalex.org/S5407036663","display_name":"Discover Computing","issn_l":"2948-2992","issn":["2948-2992"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4407126725.pdf","grobid_xml":"https://content.openalex.org/works/W4407126725.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W2004510681","https://openalex.org/W2011289111","https://openalex.org/W2079544428","https://openalex.org/W2090804287","https://openalex.org/W2102731100","https://openalex.org/W2950849820","https://openalex.org/W3005111669","https://openalex.org/W3010563482","https://openalex.org/W3048311949","https://openalex.org/W3109369928","https://openalex.org/W3136575572","https://openalex.org/W3190722902","https://openalex.org/W3195790260","https://openalex.org/W3201548965","https://openalex.org/W4226262670","https://openalex.org/W4282942908","https://openalex.org/W4285228297","https://openalex.org/W4312181065","https://openalex.org/W4317425870","https://openalex.org/W4384010844","https://openalex.org/W4386195489","https://openalex.org/W4386211913","https://openalex.org/W4387807251"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W1495501409","https://openalex.org/W4226377888","https://openalex.org/W2144833504","https://openalex.org/W4306893319","https://openalex.org/W4311965611","https://openalex.org/W4246426680","https://openalex.org/W973108520","https://openalex.org/W2340822924","https://openalex.org/W1494624369"],"abstract_inverted_index":{"To":[0],"address":[1],"uncertainties":[2,11],"in":[3,119],"the":[4,30,42,47,61,78,84,90,96,100,106,113,128,140,150,159,182,210],"supply":[5,16,151,175,212],"chain,":[6,152],"this":[7,126],"paper":[8],"analyzes":[9],"potential":[10],"by":[12,83,95,105],"constructing":[13],"a":[14],"three-tier":[15],"chain":[17,176,213],"simulation":[18,160],"model":[19,131,183],"and":[20,56,67,112,153,166,200,207],"proposes":[21],"an":[22],"optimized":[23,82,94,104],"support":[24,79,91,101,115],"vector":[25,80,92,102,116],"machine":[26,81,93,103,117],"algorithm":[27,49,98,110],"(IJS-SVM)":[28],"using":[29],"improved":[31],"Jellyfish":[32,44,86],"Search":[33,45,87],"Algorithm":[34,88],"to":[35,41,134,162,169,204],"optimize":[36],"these":[37,155],"uncertainties.":[38],"In":[39],"comparison":[40],"classical":[43,85],"Algorithm,":[46],"proposed":[48],"incorporates":[50],"Logistic":[51],"chaotic":[52],"mapping,":[53],"Cauchy":[54],"variation,":[55],"inverse":[57],"learning":[58],"strategies,":[59],"with":[60],"goal":[62],"of":[63,121,143,149],"improving":[64],"solution":[65],"efficiency":[66],"avoiding":[68],"local":[69],"optima.":[70],"The":[71,178],"experimental":[72],"results":[73,157],"indicate":[74],"that":[75,181],"IJS-SVM":[76],"outperforms":[77],"(JS-SVM),":[89],"genetic":[97],"(GA-SVM),":[99],"particle":[107],"swarm":[108],"optimization":[109,208],"(PSO-SVM),":[111],"traditional":[114],"(SVM)":[118],"terms":[120],"classification":[122],"accuracy.":[123],"Building":[124],"on":[125,146],"study,":[127],"SHAP":[129],"explanatory":[130],"is":[132],"employed":[133],"interpret":[135],"IJS-SVM\u2019s":[136],"prediction":[137],"results,":[138],"quantify":[139],"specific":[141],"impact":[142],"uncertainty":[144,205],"factors":[145],"each":[147],"stage":[148],"input":[154],"quantitative":[156],"into":[158],"system":[161],"assess":[163],"warehouse":[164,171],"allocation":[165],"identify":[167],"strategies":[168],"enhance":[170],"utilization,":[172],"ultimately":[173],"minimizing":[174],"costs.":[177],"experiment":[179],"demonstrates":[180],"not":[184],"only":[185],"offers":[186],"valuable":[187],"practical":[188],"guidance":[189],"for":[190],"CEPC":[191],"engineering":[192],"project":[193],"planning":[194],"but":[195],"also":[196],"has":[197],"broad":[198],"applicability":[199],"can":[201],"be":[202],"extended":[203],"management":[206],"within":[209],"tertiary":[211],"sector.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
