{"id":"https://openalex.org/W4401414914","doi":"https://doi.org/10.1109/cec60901.2024.10612056","title":"Ingredient Planning for Copper Industry: A Deep Reinforcement Learning-Based $\\epsilon$-Constrained Multi-Objective Optimization Framework","display_name":"Ingredient Planning for Copper Industry: A Deep Reinforcement Learning-Based $\\epsilon$-Constrained Multi-Objective Optimization Framework","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4401414914","doi":"https://doi.org/10.1109/cec60901.2024.10612056"},"language":"en","primary_location":{"id":"doi:10.1109/cec60901.2024.10612056","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cec60901.2024.10612056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"},"type":"article","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/A5109000154","display_name":"Xuerui Zhang","orcid":"https://orcid.org/0009-0004-7213-5462"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xuerui Zhang","raw_affiliation_strings":["School of Control Science and Engineering, Dalian University of Technology,Dalian,China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Dalian University of Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068402684","display_name":"Zhongyang Han","orcid":"https://orcid.org/0000-0002-3397-4915"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyang Han","raw_affiliation_strings":["School of Control Science and Engineering, Dalian University of Technology,Dalian,China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Dalian University of Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100462278","display_name":"Zhiyuan Wang","orcid":"https://orcid.org/0000-0001-6986-9589"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Wang","raw_affiliation_strings":["School of Control Science and Engineering, Dalian University of Technology,Dalian,China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Dalian University of Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100358009","display_name":"Jun Zhao","orcid":"https://orcid.org/0000-0002-3573-152X"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhao","raw_affiliation_strings":["School of Control Science and Engineering, Dalian University of Technology,Dalian,China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Dalian University of Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391742","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0001-7608-7438"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["School of Control Science and Engineering, Dalian University of Technology,Dalian,China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Dalian University of Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109000154"],"corresponding_institution_ids":["https://openalex.org/I27357992"],"apc_list":null,"apc_paid":null,"fwci":0.3814,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62637226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"3809","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":0.9599999785423279,"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":0.9599999785423279,"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/T11663","display_name":"Viral Infectious Diseases and Gene Expression in Insects","score":0.919700026512146,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11053","display_name":"Process Optimization and Integration","score":0.9194999933242798,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8360520601272583},{"id":"https://openalex.org/keywords/ingredient","display_name":"Ingredient","score":0.6686214804649353},{"id":"https://openalex.org/keywords/copper","display_name":"Copper","score":0.6080782413482666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5617564916610718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45733386278152466},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.44062158465385437},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.41541868448257446},{"id":"https://openalex.org/keywords/industrial-engineering","display_name":"Industrial engineering","score":0.3632400631904602},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23683086037635803},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1646876037120819},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.1608138084411621},{"id":"https://openalex.org/keywords/metallurgy","display_name":"Metallurgy","score":0.0869617760181427},{"id":"https://openalex.org/keywords/structural-engineering","display_name":"Structural engineering","score":0.07392236590385437}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8360520601272583},{"id":"https://openalex.org/C2780589914","wikidata":"https://www.wikidata.org/wiki/Q10675206","display_name":"Ingredient","level":2,"score":0.6686214804649353},{"id":"https://openalex.org/C544778455","wikidata":"https://www.wikidata.org/wiki/Q753","display_name":"Copper","level":2,"score":0.6080782413482666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5617564916610718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45733386278152466},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.44062158465385437},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.41541868448257446},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.3632400631904602},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23683086037635803},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1646876037120819},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.1608138084411621},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0869617760181427},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.07392236590385437},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec60901.2024.10612056","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cec60901.2024.10612056","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W113753875","https://openalex.org/W2049862811","https://openalex.org/W2106334424","https://openalex.org/W2502455647","https://openalex.org/W2582113504","https://openalex.org/W2588878409","https://openalex.org/W2736601468","https://openalex.org/W2889721727","https://openalex.org/W2955804429","https://openalex.org/W2962947982","https://openalex.org/W2963495312","https://openalex.org/W3036925570","https://openalex.org/W3123270512","https://openalex.org/W3140707475","https://openalex.org/W3159417211","https://openalex.org/W3166571664","https://openalex.org/W3169726339","https://openalex.org/W4214941022","https://openalex.org/W4281561236","https://openalex.org/W4285219208","https://openalex.org/W4379977613","https://openalex.org/W4393379586","https://openalex.org/W6809897037"],"related_works":["https://openalex.org/W2490316842","https://openalex.org/W1650653924","https://openalex.org/W4221018629","https://openalex.org/W1997883897","https://openalex.org/W2475097056","https://openalex.org/W2088663511","https://openalex.org/W2366664701","https://openalex.org/W3161375132","https://openalex.org/W4296885217","https://openalex.org/W3159569875"],"abstract_inverted_index":{"Effective":[0],"ingredient":[1,35,143],"plan":[2],"plays":[3],"a":[4,33,53,68,90],"crucial":[5],"role":[6],"in":[7,43,74,146],"the":[8,22,51,76,100,118,127,132],"copper":[9,147],"industry":[10],"as":[11],"it":[12],"directly":[13],"impacts":[14],"both":[15,27],"economic":[16],"interest":[17],"and":[18,30,129,140],"resource":[19],"utilization":[20],"of":[21,131],"enterprise.":[23],"Aims":[24],"at":[25],"minimizing":[26],"production":[28],"cost":[29],"loss":[31],"simultaneously,":[32],"multi-objective":[34,60],"optimization":[36,61,145],"model":[37],"considering":[38],"practical":[39],"constraints":[40],"is":[41,64,72,96,108],"established":[42],"this":[44],"study.":[45],"In":[46,66],"order":[47],"to":[48],"effectively":[49],"address":[50],"model,":[52],"deep":[54,113],"reinforcement":[55,114],"learning-based":[56],"<tex":[57,92,104],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[58,93,105],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\varepsilon$</tex>-constrained":[59,94],"framework":[62,134],"(DRL-ECMO)":[63],"designed.":[65],"detail,":[67],"dynamic":[69],"assistant":[70,101],"population":[71],"introduced,":[73],"which":[75],"involved":[77],"solutions":[78],"are":[79],"infeasible":[80],"but":[81],"potentially":[82],"valuable":[83],"for":[84,99,142],"giving":[85],"further":[86],"search":[87],"directions.":[88],"Then":[89],"new":[91],"method":[95],"correspondingly":[97],"developed":[98],"population,":[102],"where":[103],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\varepsilon$</tex>":[106],"value":[107],"adaptively":[109],"adjusted":[110],"based":[111,121],"on":[112,122],"learning":[115],"(DRL).":[116],"Finally,":[117],"experimental":[119],"results":[120],"real":[123],"world":[124],"data":[125],"demonstrate":[126],"effectiveness":[128],"superiority":[130],"proposed":[133],"comparing":[135],"with":[136],"other":[137],"state-of-the-art":[138],"algorithms":[139],"methods":[141],"planning":[144],"industry.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}