{"id":"https://openalex.org/W2897642573","doi":"https://doi.org/10.1109/cec.2018.8477711","title":"A Decomposition-Based Local Search Algorithm for Multi-Objective Sequence Dependent Setup Times Permutation Flowshop Scheduling","display_name":"A Decomposition-Based Local Search Algorithm for Multi-Objective Sequence Dependent Setup Times Permutation Flowshop Scheduling","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897642573","doi":"https://doi.org/10.1109/cec.2018.8477711","mag":"2897642573"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2018.8477711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2018.8477711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032983671","display_name":"Murilo Zangari","orcid":null},"institutions":[{"id":"https://openalex.org/I123443094","display_name":"Universidade Estadual de Maring\u00e1","ror":"https://ror.org/04bqqa360","country_code":"BR","type":"education","lineage":["https://openalex.org/I123443094"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Murilo Zangari","raw_affiliation_strings":["Computer Science Department, State University of Maring\u00e1, Maring\u00e1, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, State University of Maring\u00e1, Maring\u00e1, Brazil","institution_ids":["https://openalex.org/I123443094"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071233329","display_name":"Ademir Aparecido Constantino","orcid":"https://orcid.org/0000-0002-9617-5256"},"institutions":[{"id":"https://openalex.org/I123443094","display_name":"Universidade Estadual de Maring\u00e1","ror":"https://ror.org/04bqqa360","country_code":"BR","type":"education","lineage":["https://openalex.org/I123443094"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ademir Aparecido Constantino","raw_affiliation_strings":["Computer Science Department, State University of Maring\u00e1, Maring\u00e1, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, State University of Maring\u00e1, Maring\u00e1, Brazil","institution_ids":["https://openalex.org/I123443094"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017102186","display_name":"Josu Ceberio","orcid":"https://orcid.org/0000-0001-7120-6338"},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Josu Ceberio","raw_affiliation_strings":["Department of Languages and Computer Systems, University of the Basque Country (UPV/EHU), Donostia, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Languages and Computer Systems, University of the Basque Country (UPV/EHU), Donostia, Spain","institution_ids":["https://openalex.org/I169108374"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17468031,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.9998999834060669,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/tardiness","display_name":"Tardiness","score":0.8722771406173706},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.7932537794113159},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6111560463905334},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5934714674949646},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5525377988815308},{"id":"https://openalex.org/keywords/permutation","display_name":"Permutation (music)","score":0.5451487898826599},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5327332615852356},{"id":"https://openalex.org/keywords/local-search","display_name":"Local search (optimization)","score":0.5309704542160034},{"id":"https://openalex.org/keywords/flow-shop-scheduling","display_name":"Flow shop scheduling","score":0.5127209424972534},{"id":"https://openalex.org/keywords/iterated-local-search","display_name":"Iterated local search","score":0.5114763975143433},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48104146122932434},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4726791977882385},{"id":"https://openalex.org/keywords/tabu-search","display_name":"Tabu search","score":0.4319082498550415},{"id":"https://openalex.org/keywords/iterated-function","display_name":"Iterated function","score":0.4251718819141388},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2934023141860962},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.08894899487495422}],"concepts":[{"id":"https://openalex.org/C2778047078","wikidata":"https://www.wikidata.org/wiki/Q82299449","display_name":"Tardiness","level":4,"score":0.8722771406173706},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.7932537794113159},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6111560463905334},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5934714674949646},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5525377988815308},{"id":"https://openalex.org/C21308566","wikidata":"https://www.wikidata.org/wiki/Q7169365","display_name":"Permutation (music)","level":2,"score":0.5451487898826599},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5327332615852356},{"id":"https://openalex.org/C135320971","wikidata":"https://www.wikidata.org/wiki/Q1868524","display_name":"Local search (optimization)","level":2,"score":0.5309704542160034},{"id":"https://openalex.org/C158336966","wikidata":"https://www.wikidata.org/wiki/Q3074426","display_name":"Flow shop scheduling","level":4,"score":0.5127209424972534},{"id":"https://openalex.org/C124145224","wikidata":"https://www.wikidata.org/wiki/Q6094397","display_name":"Iterated local search","level":3,"score":0.5114763975143433},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48104146122932434},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4726791977882385},{"id":"https://openalex.org/C123370116","wikidata":"https://www.wikidata.org/wiki/Q1424540","display_name":"Tabu search","level":2,"score":0.4319082498550415},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.4251718819141388},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2934023141860962},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.08894899487495422},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2018.8477711","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2018.8477711","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1497425225","https://openalex.org/W1543809355","https://openalex.org/W1895669308","https://openalex.org/W1973770389","https://openalex.org/W1976159118","https://openalex.org/W1982956761","https://openalex.org/W1989396603","https://openalex.org/W1995660472","https://openalex.org/W2006358835","https://openalex.org/W2011615458","https://openalex.org/W2026828926","https://openalex.org/W2068003474","https://openalex.org/W2079661120","https://openalex.org/W2090069860","https://openalex.org/W2096415085","https://openalex.org/W2106334424","https://openalex.org/W2143381319","https://openalex.org/W2156391157","https://openalex.org/W2519112510","https://openalex.org/W2556913477","https://openalex.org/W2591140818","https://openalex.org/W2624035465","https://openalex.org/W2725272085","https://openalex.org/W3121748795","https://openalex.org/W3140662957","https://openalex.org/W3146507833","https://openalex.org/W6674531384","https://openalex.org/W6740831121"],"related_works":["https://openalex.org/W2089884908","https://openalex.org/W2083844986","https://openalex.org/W1980879778","https://openalex.org/W3216729967","https://openalex.org/W2041102680","https://openalex.org/W2900006172","https://openalex.org/W2902517208","https://openalex.org/W2113526966","https://openalex.org/W2034702700","https://openalex.org/W1533229056"],"abstract_inverted_index":{"The":[0,95],"ftowshop":[1],"scheduling":[2,32],"problem":[3,131],"(FSP)":[4],"has":[5,40],"been":[6],"widely":[7],"studied":[8],"in":[9,14,21],"the":[10,15,22,28,34,57,68,71,88,115,120,130],"last":[11],"decades,":[12],"both":[13],"single":[16],"objective":[17],"as":[18,20],"well":[19],"multi-objective":[23,58],"scenario.":[24],"Besides,":[25],"due":[26],"to":[27,54,66,98],"real-world":[29],"considerations":[30],"on":[31,80],"problems,":[33],"concern":[35],"regarding":[36],"sequence-dependent":[37,59],"setup":[38,60],"times":[39,61],"emerged.":[41],"In":[42,64],"this":[43],"paper,":[44],"we":[45,74,123],"present":[46],"a":[47,81,110,126],"decomposition-based":[48],"iterated":[49],"local":[50],"search":[51],"algorithm":[52],"(MOLS/D)":[53],"deal":[55],"with":[56],"permutation":[62],"FSP.":[63],"order":[65],"demonstrate":[67],"validity":[69],"of":[70,83],"proposed":[72],"algorithm,":[73],"have":[75,124],"conducted":[76],"an":[77],"experimental":[78],"study":[79],"set":[82],"220":[84],"benchmark":[85],"instances":[86],"minimizing":[87],"criteria":[89],"makespan":[90],"and":[91,102,114],"total":[92],"weighted":[93],"tardiness.":[94],"results,":[96],"according":[97],"various":[99],"performance":[100],"metrics":[101],"statistical":[103],"analysis,":[104],"show":[105],"that":[106],"MOLS/D":[107],"significantly":[108],"outperforms":[109],"tailored":[111],"MOEA/D":[112],"variant":[113],"best-known":[116],"reference":[117],"sets":[118],"from":[119],"literature.":[121],"Thus,":[122],"established":[125],"state-of-the-art":[127],"approach":[128],"for":[129],"considered.":[132]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
