{"id":"https://openalex.org/W4404788326","doi":"https://doi.org/10.1109/access.2024.3507161","title":"Enhancing Supply Chain Efficiency Resilience Using Predictive Analytics and Computational Intelligence Techniques","display_name":"Enhancing Supply Chain Efficiency Resilience Using Predictive Analytics and Computational Intelligence Techniques","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4404788326","doi":"https://doi.org/10.1109/access.2024.3507161"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3507161","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3507161","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3507161","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115446343","display_name":"Lixing Bo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lixing Bo","raw_affiliation_strings":["Business School, Chongqing City Vocational College, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0000-8239-0644","affiliations":[{"raw_affiliation_string":"Business School, Chongqing City Vocational College, Chongqing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102371202","display_name":"Xu Jie","orcid":"https://orcid.org/0009-0001-6611-1550"},"institutions":[{"id":"https://openalex.org/I4210116886","display_name":"Chongqing Vocational Institute of Engineering","ror":"https://ror.org/0279ehd23","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210116886"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Xu","raw_affiliation_strings":["School of Finance and Tourism, Chongqing Vocational Institute of Engineering, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0001-6611-1550","affiliations":[{"raw_affiliation_string":"School of Finance and Tourism, Chongqing Vocational Institute of Engineering, Chongqing, China","institution_ids":["https://openalex.org/I4210116886"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":9.0986,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.97641061,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"12","issue":null,"first_page":"183451","last_page":"183465"},"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":0.9839000105857849,"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":0.9839000105857849,"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"}},{"id":"https://openalex.org/T10763","display_name":"Digital Transformation in Industry","score":0.9778000116348267,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10164","display_name":"Quality and Supply Management","score":0.9401000142097473,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"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/computer-science","display_name":"Computer science","score":0.6900752782821655},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.6857084035873413},{"id":"https://openalex.org/keywords/supply-chain","display_name":"Supply chain","score":0.6142943501472473},{"id":"https://openalex.org/keywords/predictive-analytics","display_name":"Predictive analytics","score":0.5817802548408508},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5442841053009033},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.41000792384147644},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3823060691356659},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22772634029388428},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.10441091656684875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6900752782821655},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.6857084035873413},{"id":"https://openalex.org/C108713360","wikidata":"https://www.wikidata.org/wiki/Q1824206","display_name":"Supply chain","level":2,"score":0.6142943501472473},{"id":"https://openalex.org/C83209312","wikidata":"https://www.wikidata.org/wiki/Q1053367","display_name":"Predictive analytics","level":2,"score":0.5817802548408508},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5442841053009033},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.41000792384147644},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3823060691356659},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22772634029388428},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.10441091656684875},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3507161","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3507161","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5bf0042e914644cfad6e00c06c4692b2","is_oa":true,"landing_page_url":"https://doaj.org/article/5bf0042e914644cfad6e00c06c4692b2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 183451-183465 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3507161","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3507161","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.4399999976158142,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2810603057","https://openalex.org/W2948427152","https://openalex.org/W2998399378","https://openalex.org/W3013509926","https://openalex.org/W3109490607","https://openalex.org/W3113923032","https://openalex.org/W3172123770","https://openalex.org/W3192029423","https://openalex.org/W3202408014","https://openalex.org/W4213190850","https://openalex.org/W4285187731","https://openalex.org/W4294647307","https://openalex.org/W4312397225","https://openalex.org/W4312703273","https://openalex.org/W4313177783","https://openalex.org/W4365129544","https://openalex.org/W4390970119","https://openalex.org/W4392979978","https://openalex.org/W4398187666","https://openalex.org/W4399282658","https://openalex.org/W4402858974"],"related_works":["https://openalex.org/W2052370551","https://openalex.org/W2570647323","https://openalex.org/W2206805568","https://openalex.org/W2076942471","https://openalex.org/W2515921780","https://openalex.org/W2863268765","https://openalex.org/W3027285423","https://openalex.org/W2896245927","https://openalex.org/W4205879366","https://openalex.org/W1961101704"],"abstract_inverted_index":{"This":[0],"study":[1,37,115,204],"addresses":[2],"critical":[3],"challenges":[4],"in":[5,24,94,108,125,157,165,199],"supply":[6,110,194,231],"chain":[7,232],"management,":[8,215],"particularly":[9],"focusing":[10],"on":[11],"enhancing":[12],"forecast":[13],"accuracy":[14],"and":[15,30,47,68,77,134,161,176,201,213,216,225],"optimizing":[16],"inventory":[17,28,53,69,102,170,214],"management.":[18],"Traditional":[19],"methods":[20],"often":[21],"fall":[22],"short":[23],"accuracy,":[25],"leading":[26],"to":[27,90,100,132,142,153,229],"imbalances":[29],"inefficiencies.":[31],"To":[32],"overcome":[33],"these":[34,207],"limitations,":[35],"the":[36,109,114],"employs":[38],"a":[39,59,123,154,162,189],"combination":[40],"of":[41,150],"Transformer":[42,80,120,184],"models":[43,81,185],"for":[44,52,84,192,210],"demand":[45],"forecasting":[46,146,212],"Particle":[48],"Swarm":[49],"Optimization":[50],"(PSO)":[51],"parameter":[54],"optimization.":[55],"The":[56,119,148,203],"methodology":[57],"involves":[58],"comprehensive":[60],"approach:":[61],"data":[62,67,227],"collection":[63],"includes":[64],"historical":[65],"sales":[66],"levels,":[70],"which":[71],"are":[72,82],"preprocessed":[73],"through":[74],"cleaning,":[75],"normalization,":[76],"feature":[78],"extraction.":[79],"used":[83],"predicting":[85],"demand,":[86],"leveraging":[87],"their":[88],"ability":[89],"capture":[91],"complex":[92],"patterns":[93],"time-series":[95],"data.":[96],"PSO":[97,151,187],"is":[98],"applied":[99],"optimize":[101],"parameters,":[103],"addressing":[104],"multi-objective":[105],"optimization":[106],"problems":[107],"chain.":[111],"Results":[112],"from":[113,130,140],"indicate":[116],"significant":[117],"improvements.":[118],"model":[121],"achieved":[122],"reduction":[124,156],"Mean":[126,136],"Absolute":[127],"Error":[128,138],"(MAE)":[129],"15.8":[131],"8.2":[133],"Root":[135],"Squared":[137],"(RMSE)":[139],"22.3":[141],"11.5,":[143],"demonstrating":[144],"enhanced":[145],"accuracy.":[147],"application":[149],"led":[152],"12%":[155],"overall":[158],"operational":[159],"costs":[160,172,178],"25%":[163],"improvement":[164],"order":[166],"fulfillment":[167],"times.":[168],"Additionally,":[169],"holding":[171],"decreased":[173],"by":[174,181],"18%,":[175],"transportation":[177],"were":[179],"reduced":[180],"10%.":[182],"Integrating":[183],"with":[186],"presents":[188],"robust":[190],"solution":[191],"modern":[193],"chains,":[195],"offering":[196],"substantial":[197],"improvements":[198],"efficiency":[200],"cost-effectiveness.":[202],"recommends":[205],"adopting":[206],"advanced":[208],"methodologies":[209],"better":[211],"suggests":[217],"further":[218],"research":[219],"into":[220],"additional":[221],"machine":[222],"learning":[223],"techniques":[224],"real-time":[226],"integration":[228],"enhance":[230],"performance.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":10}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
