{"id":"https://openalex.org/W7124712824","doi":"https://doi.org/10.1016/j.jii.2026.101075","title":"Ensemble-based ship weather multi-objective route optimization","display_name":"Ensemble-based ship weather multi-objective route optimization","publication_year":2026,"publication_date":"2026-01-18","ids":{"openalex":"https://openalex.org/W7124712824","doi":"https://doi.org/10.1016/j.jii.2026.101075"},"language":"en","primary_location":{"id":"doi:10.1016/j.jii.2026.101075","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jii.2026.101075","pdf_url":null,"source":{"id":"https://openalex.org/S2898195457","display_name":"Journal of Industrial Information Integration","issn_l":"2452-414X","issn":["2452-414X","2467-964X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Industrial Information Integration","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.jii.2026.101075","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015291242","display_name":"Kumars Mahmoodi","orcid":"https://orcid.org/0000-0002-9374-5970"},"institutions":[{"id":"https://openalex.org/I112281704","display_name":"Research Council of Finland","ror":"https://ror.org/05k73zm37","country_code":"FI","type":"government","lineage":["https://openalex.org/I112281704"]},{"id":"https://openalex.org/I130217899","display_name":"\u00c5bo Akademi University","ror":"https://ror.org/029pk6x14","country_code":"FI","type":"education","lineage":["https://openalex.org/I130217899"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Kumars Mahmoodi","raw_affiliation_strings":["Faculty of Natural Sciences and Engineering, \u00c5 bo Akademi University, Turku, Finland"],"raw_orcid":"https://orcid.org/0000-0002-9374-5970","affiliations":[{"raw_affiliation_string":"Faculty of Natural Sciences and Engineering, \u00c5 bo Akademi University, Turku, Finland","institution_ids":["https://openalex.org/I130217899","https://openalex.org/I112281704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078358573","display_name":"Jari M. B\u00f6ling","orcid":"https://orcid.org/0000-0002-6385-501X"},"institutions":[{"id":"https://openalex.org/I112281704","display_name":"Research Council of Finland","ror":"https://ror.org/05k73zm37","country_code":"FI","type":"government","lineage":["https://openalex.org/I112281704"]},{"id":"https://openalex.org/I130217899","display_name":"\u00c5bo Akademi University","ror":"https://ror.org/029pk6x14","country_code":"FI","type":"education","lineage":["https://openalex.org/I130217899"]},{"id":"https://openalex.org/I155660961","display_name":"University of Turku","ror":"https://ror.org/05vghhr25","country_code":"FI","type":"education","lineage":["https://openalex.org/I155660961"]},{"id":"https://openalex.org/I16231767","display_name":"Turku University of Applied Sciences","ror":"https://ror.org/04s0yt949","country_code":"FI","type":"education","lineage":["https://openalex.org/I16231767"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Jari B\u00f6ling","raw_affiliation_strings":["Automation, Mechanical and Materials Engineering, University of Turku, Finland","Faculty of Natural Sciences and Engineering, \u00c5 bo Akademi University, Turku, Finland"],"raw_orcid":"https://orcid.org/0000-0002-6385-501X","affiliations":[{"raw_affiliation_string":"Automation, Mechanical and Materials Engineering, University of Turku, Finland","institution_ids":["https://openalex.org/I155660961","https://openalex.org/I16231767"]},{"raw_affiliation_string":"Faculty of Natural Sciences and Engineering, \u00c5 bo Akademi University, Turku, Finland","institution_ids":["https://openalex.org/I130217899","https://openalex.org/I112281704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039608863","display_name":"Roberto Vettor","orcid":"https://orcid.org/0000-0001-9002-9971"},"institutions":[{"id":"https://openalex.org/I4210094142","display_name":"Napa (Finland)","ror":"https://ror.org/00n63p259","country_code":"FI","type":"company","lineage":["https://openalex.org/I4210094142"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Roberto Vettor","raw_affiliation_strings":["Napa Ltd., Tammasaarenkatu 3, 00180 Helsinki, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Napa Ltd., Tammasaarenkatu 3, 00180 Helsinki, Finland","institution_ids":["https://openalex.org/I4210094142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015291242"],"corresponding_institution_ids":["https://openalex.org/I112281704","https://openalex.org/I130217899"],"apc_list":{"value":2780,"currency":"USD","value_usd":2780},"apc_paid":{"value":2780,"currency":"USD","value_usd":2780},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10045692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":null,"first_page":"101075","last_page":"101075"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12126","display_name":"Maritime Transport Emissions and Efficiency","score":0.886900007724762,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12126","display_name":"Maritime Transport Emissions and Efficiency","score":0.886900007724762,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.07119999825954437,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T11223","display_name":"Maritime Ports and Logistics","score":0.014800000004470348,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/fuel-efficiency","display_name":"Fuel efficiency","score":0.6887999773025513},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6000000238418579},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5557000041007996},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5083000063896179},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.4133000075817108},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.35749998688697815},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3549000024795532},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.34689998626708984}],"concepts":[{"id":"https://openalex.org/C45882903","wikidata":"https://www.wikidata.org/wiki/Q5042317","display_name":"Fuel efficiency","level":2,"score":0.6887999773025513},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6000000238418579},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5557000041007996},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5540000200271606},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5083000063896179},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.3824000060558319},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.35749998688697815},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C193254401","wikidata":"https://www.wikidata.org/wiki/Q2160088","display_name":"Robust optimization","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2937000095844269},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28690001368522644},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.2768999934196472},{"id":"https://openalex.org/C20820323","wikidata":"https://www.wikidata.org/wiki/Q6496514","display_name":"Latin hypercube sampling","level":3,"score":0.2752000093460083},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2583000063896179},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1016/j.jii.2026.101075","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jii.2026.101075","pdf_url":null,"source":{"id":"https://openalex.org/S2898195457","display_name":"Journal of Industrial Information Integration","issn_l":"2452-414X","issn":["2452-414X","2467-964X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Industrial Information Integration","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire/783ad0d3-099f-40ae-a21c-8bb243051de0","is_oa":true,"landing_page_url":"https://research.abo.fi/en/publications/783ad0d3-099f-40ae-a21c-8bb243051de0","pdf_url":null,"source":{"id":"https://openalex.org/S4406923060","display_name":"\u00c5bo Akademi University Research Portal","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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mahmoodi, K, B\u00f6ling, J & Vettor, R 2026, 'Ensemble-based ship weather multi-objective route optimization', Journal of Industrial Information Integration, vol. 50, 101075. https://doi.org/10.1016/j.jii.2026.101075","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:publications/783ad0d3-099f-40ae-a21c-8bb243051de0","is_oa":true,"landing_page_url":"https://www.sciencedirect.com/science/article/pii/S2452414X26000166","pdf_url":null,"source":{"id":"https://openalex.org/S4406923060","display_name":"\u00c5bo Akademi University Research Portal","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-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Mahmoodi, K, B\u00f6ling, J & Vettor, R 2026, 'Ensemble-based ship weather multi-objective route optimization', Journal of Industrial Information Integration, vol. 50, 101075. https://doi.org/10.1016/j.jii.2026.101075","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1016/j.jii.2026.101075","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.jii.2026.101075","pdf_url":null,"source":{"id":"https://openalex.org/S2898195457","display_name":"Journal of Industrial Information Integration","issn_l":"2452-414X","issn":["2452-414X","2467-964X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Industrial Information Integration","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2841551805","display_name":null,"funder_award_id":"7682/31/2022","funder_id":"https://openalex.org/F4320328501","funder_display_name":"Business Finland"}],"funders":[{"id":"https://openalex.org/F4320328501","display_name":"Business Finland","ror":"https://ror.org/05bgf9v38"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1879836922","https://openalex.org/W2033371750","https://openalex.org/W2061438946","https://openalex.org/W2174096823","https://openalex.org/W2755339499","https://openalex.org/W2770073247","https://openalex.org/W2792187930","https://openalex.org/W2909679734","https://openalex.org/W2921660753","https://openalex.org/W2964177704","https://openalex.org/W2991285945","https://openalex.org/W2999082917","https://openalex.org/W3006565436","https://openalex.org/W3009283923","https://openalex.org/W3046981189","https://openalex.org/W3158593921","https://openalex.org/W3166478336","https://openalex.org/W3203339410","https://openalex.org/W4200044824","https://openalex.org/W4200212986","https://openalex.org/W4210743812","https://openalex.org/W4212994175","https://openalex.org/W4213072557","https://openalex.org/W4220846342","https://openalex.org/W4221125177","https://openalex.org/W4280515439","https://openalex.org/W4293411891","https://openalex.org/W4294724304","https://openalex.org/W4310215787","https://openalex.org/W4321794006","https://openalex.org/W4322767733","https://openalex.org/W4368374818","https://openalex.org/W4385071479","https://openalex.org/W4385820046","https://openalex.org/W4385979938","https://openalex.org/W4388407530","https://openalex.org/W4390770894","https://openalex.org/W4392078769","https://openalex.org/W4400081834","https://openalex.org/W4408324558","https://openalex.org/W4408477302","https://openalex.org/W4408520038","https://openalex.org/W4408619660","https://openalex.org/W4410093088","https://openalex.org/W4410110344","https://openalex.org/W4410944148","https://openalex.org/W4413310315","https://openalex.org/W4413767396"],"related_works":[],"abstract_inverted_index":{"Many":[0],"traditional":[1],"and":[2,29,63,77,109,120,163,255,264,296,306,313],"state-of-the-art":[3],"ship":[4,42,60,75,258,276,284],"routing":[5,25,277],"methods":[6],"rely":[7],"on":[8,57,74,149],"single-objective":[9],"formulations,":[10],"deterministic":[11],"weather":[12,47,79,84,272],"inputs,":[13],"or":[14,23],"fixed":[15],"operational":[16],"assumptions,":[17],"which":[18],"may":[19,208],"lead":[20],"to":[21,69,88,133,212,251],"suboptimal":[22],"impractical":[24],"decisions":[26],"under":[27,45,266],"realistic":[28],"uncertain":[30,46],"marine":[31,78],"environments.":[32],"This":[33],"study":[34],"presents":[35],"an":[36],"ensemble-based":[37],"multi-objective":[38,244],"optimization":[39,112,254,300],"framework":[40,50,248],"for":[41,169],"route":[43,89,146],"planning":[44],"conditions.":[48,269],"The":[49,140,246],"integrates":[51],"a":[52,92,128,159,230],"neural":[53],"network":[54],"model,":[55],"trained":[56],"real":[58],"onboard":[59],"performance":[61,147],"data":[62,273],"tuned":[64],"using":[65,91],"Bayesian":[66],"hyperparameter":[67],"optimization,":[68],"predict":[70],"fuel":[71,107,167,189,203,262,285,293],"consumption":[72,168,204],"based":[73,148],"speed":[76],"parameters.":[80],"An":[81],"ensemble":[82,116,196,302],"of":[83,98],"forecasts":[85],"is":[86,249],"assigned":[87],"waypoints":[90],"bootstrapping":[93],"method,":[94],"enabling":[95],"the":[96,150,155,170,179,187,195,200,210,216],"evaluation":[97],"multiple":[99],"cost":[100],"functions":[101],"reflecting":[102],"trade-offs":[103,291],"between":[104,161],"voyage":[105,166,211,253],"time,":[106],"consumption,":[108,294],"safety.":[110,319],"Four":[111,288],"objective":[113],"strategies":[114,289],"\u2014":[115,124],"mean,":[117,303],"worst-case,":[118,304],"risk-aware,":[119,305],"Conditional":[121],"Value-at-Risk":[122],"(CVaR)":[123],"are":[125],"implemented":[126],"within":[127,229],"Grey":[129],"Wolf":[130],"Optimizer":[131],"(GWO)":[132],"derive":[134],"optimal":[135],"routes":[136],"across":[137,233],"various":[138],"voyages.":[139],"results":[141],"demonstrate":[142],"notable":[143],"variations":[144],"in":[145,186,222,241,260,292],"selected":[151],"strategy.":[152],"For":[153],"example,":[154],"CVaR":[156,307,310],"approach":[157],"achieves":[158],"balance":[160],"robustness":[162],"efficiency,":[164],"with":[165],"longest":[171],"journey":[172],"(Voyage":[173],"3)":[174],"reaching":[175],"490,475":[176],"kg,":[177],"while":[178,315],"worst-case":[180,316],"strategy":[181,198],"prioritizes":[182],"risk-averse":[183],"paths,":[184],"resulting":[185],"highest":[188],"usage":[190],"at":[191],"505,308":[192],"kg.":[193],"Conversely,":[194],"mean":[197],"offers":[199],"lowest":[201],"average":[202],"(474,078":[205],"kg)":[206],"but":[207],"expose":[209],"higher":[213],"uncertainty.":[214],"Furthermore,":[215],"proposed":[217],"GWO":[218],"demonstrates":[219],"high":[220],"precision":[221],"schedule":[223],"adherence,":[224],"maintaining":[225],"arrival":[226],"time":[227],"deviations":[228],"30-minute":[231],"margin":[232],"all":[234],"optimized":[235],"voyages,":[236],"thereby":[237],"justifying":[238],"its":[239],"effectiveness":[240],"handling":[242],"complex":[243],"constraints.":[245],"developed":[247],"applicable":[250],"real-time":[252],"can":[256],"support":[257],"operators":[259],"achieving":[261],"efficiency":[263,312],"safety":[265],"varying":[267],"ocean":[268],"\u2022":[270,279,287,298,309],"Ensemble":[271],"integrated":[274],"into":[275],"optimization.":[278],"Bayesian-optimized":[280],"NN":[281],"model":[282],"predicts":[283],"consumption.":[286],"compare":[290],"duration,":[295],"risk.":[297],"GWO-based":[299],"applies":[301],"objectives.":[308],"balances":[311],"risk,":[314],"ensures":[317],"maximum":[318]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2026-01-20T00:00:00"}
