{"id":"https://openalex.org/W3016020363","doi":"https://doi.org/10.1137/17m1156332","title":"Scheduling to Minimize Total Weighted Completion Time via Time-Indexed Linear Programming Relaxations","display_name":"Scheduling to Minimize Total Weighted Completion Time via Time-Indexed Linear Programming Relaxations","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3016020363","doi":"https://doi.org/10.1137/17m1156332","mag":"3016020363"},"language":"en","primary_location":{"id":"doi:10.1137/17m1156332","is_oa":false,"landing_page_url":"https://doi.org/10.1137/17m1156332","pdf_url":null,"source":{"id":"https://openalex.org/S153560523","display_name":"SIAM Journal on Computing","issn_l":"0097-5397","issn":["0097-5397","1095-7111"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Computing","raw_type":"journal-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/A5100430766","display_name":"Shi Li","orcid":"https://orcid.org/0000-0001-9140-9415"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shi Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9140-9415","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100430766"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9323,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.87987077,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"49","issue":"4","first_page":"FOCS17","last_page":"409"},"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/T12288","display_name":"Optimization and Search Problems","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-programming","display_name":"Linear programming","score":0.6544721126556396},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.6262971758842468},{"id":"https://openalex.org/keywords/linear-programming-relaxation","display_name":"Linear programming relaxation","score":0.6128057837486267},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5985519289970398},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5811688899993896},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.5218623876571655},{"id":"https://openalex.org/keywords/job-shop-scheduling","display_name":"Job shop scheduling","score":0.5114309191703796},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.5077670812606812},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.43879881501197815},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3746027946472168},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32488831877708435},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.08044475317001343},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.07215020060539246}],"concepts":[{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.6544721126556396},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.6262971758842468},{"id":"https://openalex.org/C25360446","wikidata":"https://www.wikidata.org/wiki/Q1512771","display_name":"Linear programming relaxation","level":3,"score":0.6128057837486267},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5985519289970398},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5811688899993896},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.5218623876571655},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.5114309191703796},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.5077670812606812},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.43879881501197815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3746027946472168},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32488831877708435},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.08044475317001343},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.07215020060539246},{"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1137/17m1156332","is_oa":false,"landing_page_url":"https://doi.org/10.1137/17m1156332","pdf_url":null,"source":{"id":"https://openalex.org/S153560523","display_name":"SIAM Journal on Computing","issn_l":"0097-5397","issn":["0097-5397","1095-7111"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G3350261587","display_name":null,"funder_award_id":"CCF-1717134","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5149950309","display_name":null,"funder_award_id":"CCF-1566356","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1488422606","https://openalex.org/W1495318531","https://openalex.org/W1531908439","https://openalex.org/W1556839242","https://openalex.org/W2006905044","https://openalex.org/W2013170874","https://openalex.org/W2046471719","https://openalex.org/W2056273707","https://openalex.org/W2067753820","https://openalex.org/W2081798943","https://openalex.org/W2102201348","https://openalex.org/W2102588682","https://openalex.org/W2104680817","https://openalex.org/W2148204686","https://openalex.org/W2150446509","https://openalex.org/W2170050590","https://openalex.org/W2963832601"],"related_works":["https://openalex.org/W2185409389","https://openalex.org/W2109445739","https://openalex.org/W2515987778","https://openalex.org/W4205854323","https://openalex.org/W2020662107","https://openalex.org/W2507810539","https://openalex.org/W1969256273","https://openalex.org/W3100114454","https://openalex.org/W3127756288","https://openalex.org/W3020502198"],"abstract_inverted_index":{"We":[0,26,61,148],"study":[1],"approximation":[2],"algorithms":[3,28],"for":[4,57,107,119,145],"problems":[5],"of":[6,14,48,67,80,90,98,115],"scheduling":[7,65],"precedence":[8],"constrained":[9],"jobs":[10],"with":[11],"the":[12,46,64,91,108,116,120,146,157],"objective":[13],"minimizing":[15,68],"total":[16,69],"weighted":[17,70],"completion":[18,71],"time,":[19],"in":[20,42,88],"identical":[21],"and":[22,85,138],"related":[23],"machine":[24],"models.":[25],"give":[27],"that":[29,126],"improve":[30],"upon":[31],"many":[32],"previous":[33],"15-":[34],"to":[35],"20-year-old":[36],"state-of-the-art":[37],"results.":[38],"A":[39],"major":[40],"theme":[41],"these":[43],"results":[44],"is":[45,125],"use":[47],"time-indexed":[49,141],"linear":[50,142],"programming":[51,143],"relaxations,":[52],"which":[53],"are":[54],"quite":[55],"natural":[56,137],"their":[58],"respective":[59],"problems.":[60],"also":[62,132],"consider":[63],"problem":[66],"time":[72],"on":[73,96,111],"unrelated":[74],"machines.":[75],"The":[76],"recent":[77],"breakthrough":[78],"result":[79,124],"[N.":[81],"Bansal,":[82],"A.":[83],"Srinivasan,":[84],"O.":[86],"Svensson,":[87],"Proceedings":[89],"48th":[92],"Annual":[93],"ACM":[94],"Symposium":[95],"Theory":[97],"Computing,":[99],"ACM,":[100],"2016,":[101],"pp.":[102],"156--167]":[103],"gave":[104],"a":[105,112,127,136],"(1.5-c)-approximation":[106],"problem,":[109],"based":[110],"two-round":[113],"lift-and-project":[114],"SDP":[117],"relaxation":[118,144,151],"problem.":[121,147,158],"Our":[122],"main":[123],"(1.5":[128],"-":[129],"c)-approximation":[130],"can":[131,152],"be":[133],"achieved":[134],"using":[135],"considerably":[139],"simpler":[140],"hope":[149],"this":[150],"provide":[153],"new":[154],"insights":[155],"into":[156]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
