Revisit the scheduling problem with assignable or generalized due dates to minimize total weighted late work

We revisit the single-machine scheduling for minimising the total weighted late work with assignable due dates (ADD-scheduling) and generalised due dates (GDD-scheduling). In particular, we consider the following three problems: (i) the GDD-scheduling problem for minimising the total weighted late w...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of production research 2023-11, Vol.61 (22), p.7630-7648
Hauptverfasser: Chen, Rubing, Gao, Yuan, Geng, Zhichao, Yuan, Jinjiang
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 7648
container_issue 22
container_start_page 7630
container_title International journal of production research
container_volume 61
creator Chen, Rubing
Gao, Yuan
Geng, Zhichao
Yuan, Jinjiang
description We revisit the single-machine scheduling for minimising the total weighted late work with assignable due dates (ADD-scheduling) and generalised due dates (GDD-scheduling). In particular, we consider the following three problems: (i) the GDD-scheduling problem for minimising the total weighted late work, (ii) the ADD-scheduling problem for minimising the total weighted late work, and (iii) the ADD-scheduling problem for minimising the total late work. In the literature, the above three problems are proved to be NP-hard, but their exact complexity (unary NP-hardness or pseudo-polynomial-time solvability) are unknown. In this paper, we address these open problems by showing that the first two problems are unary NP-hard and the third problem admits pseudo-polynomial-time algorithms. For the third problem, we also present a 2-approximation solution and a fully polynomial-time approximation scheme. Computational experiments show that our algorithms and solutions are efficient. When the jobs have identical processing times, we further present more efficient polynomial-time algorithms.
doi_str_mv 10.1080/00207543.2022.2160502
format Article
fullrecord <record><control><sourceid>proquest_econi</sourceid><recordid>TN_cdi_proquest_journals_2869043447</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2869043447</sourcerecordid><originalsourceid>FETCH-LOGICAL-c395t-c3b0cd17b57219a89281610e5f257fa87cde0310cae5ba7db5ab1bc9290aabed3</originalsourceid><addsrcrecordid>eNp9kE1rHDEMhk1JoZu0P6Fg6Hm3smc847m1hH7BQiCk0JvR2Jpdp55xanu7pL--Xjalt-ggCfG8EnoZeytgI0DDewAJvWqbjQQpN1J0oEC-YCvRdN1aaf3jgq1OzPoEvWKXOd9DDaXbFQu39NtnX3jZE892T-4Q_LLjDymOgWZ-9GXPMWe_W7AOeEx8RwslDP4POe4OxB0WyrxEPvvFz3Vc-4KBH8nv9qVCoQL8GNPP1-zlhCHTm6d6xb5__nR3_XW9vfny7frjdm2bQZWaR7BO9KPqpRhQD1KLTgCpSap-Qt1bR9AIsEhqxN6NCkcx2kEOgDiSa67Yu_Pe-sWvA-Vi7uMhLfWkkboboG3atq-UOlM2xZwTTeYh-RnToxFgTsaaf8aak7Hmydiq42cd2bj4_F-lu152Sui2Ih_OiF-mmGaszwdnCj6GmKaEi62y5vkrfwGaCous</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2869043447</pqid></control><display><type>article</type><title>Revisit the scheduling problem with assignable or generalized due dates to minimize total weighted late work</title><source>Taylor &amp; Francis</source><creator>Chen, Rubing ; Gao, Yuan ; Geng, Zhichao ; Yuan, Jinjiang</creator><creatorcontrib>Chen, Rubing ; Gao, Yuan ; Geng, Zhichao ; Yuan, Jinjiang</creatorcontrib><description>We revisit the single-machine scheduling for minimising the total weighted late work with assignable due dates (ADD-scheduling) and generalised due dates (GDD-scheduling). In particular, we consider the following three problems: (i) the GDD-scheduling problem for minimising the total weighted late work, (ii) the ADD-scheduling problem for minimising the total weighted late work, and (iii) the ADD-scheduling problem for minimising the total late work. In the literature, the above three problems are proved to be NP-hard, but their exact complexity (unary NP-hardness or pseudo-polynomial-time solvability) are unknown. In this paper, we address these open problems by showing that the first two problems are unary NP-hard and the third problem admits pseudo-polynomial-time algorithms. For the third problem, we also present a 2-approximation solution and a fully polynomial-time approximation scheme. Computational experiments show that our algorithms and solutions are efficient. When the jobs have identical processing times, we further present more efficient polynomial-time algorithms.</description><identifier>ISSN: 0020-7543</identifier><identifier>EISSN: 1366-588X</identifier><identifier>DOI: 10.1080/00207543.2022.2160502</identifier><language>eng</language><publisher>London: Taylor &amp; Francis</publisher><subject>Algorithms ; Approximation ; assignable/generalized due dates ; NP-hard ; Polynomials ; Scheduling ; total weighted late work</subject><ispartof>International journal of production research, 2023-11, Vol.61 (22), p.7630-7648</ispartof><rights>2022 Informa UK Limited, trading as Taylor &amp; Francis Group 2022</rights><rights>2022 Informa UK Limited, trading as Taylor &amp; Francis Group</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c395t-c3b0cd17b57219a89281610e5f257fa87cde0310cae5ba7db5ab1bc9290aabed3</citedby><cites>FETCH-LOGICAL-c395t-c3b0cd17b57219a89281610e5f257fa87cde0310cae5ba7db5ab1bc9290aabed3</cites><orcidid>0000-0002-9814-615X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.tandfonline.com/doi/pdf/10.1080/00207543.2022.2160502$$EPDF$$P50$$Ginformaworld$$H</linktopdf><linktohtml>$$Uhttps://www.tandfonline.com/doi/full/10.1080/00207543.2022.2160502$$EHTML$$P50$$Ginformaworld$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,59624,60413</link.rule.ids></links><search><creatorcontrib>Chen, Rubing</creatorcontrib><creatorcontrib>Gao, Yuan</creatorcontrib><creatorcontrib>Geng, Zhichao</creatorcontrib><creatorcontrib>Yuan, Jinjiang</creatorcontrib><title>Revisit the scheduling problem with assignable or generalized due dates to minimize total weighted late work</title><title>International journal of production research</title><description>We revisit the single-machine scheduling for minimising the total weighted late work with assignable due dates (ADD-scheduling) and generalised due dates (GDD-scheduling). In particular, we consider the following three problems: (i) the GDD-scheduling problem for minimising the total weighted late work, (ii) the ADD-scheduling problem for minimising the total weighted late work, and (iii) the ADD-scheduling problem for minimising the total late work. In the literature, the above three problems are proved to be NP-hard, but their exact complexity (unary NP-hardness or pseudo-polynomial-time solvability) are unknown. In this paper, we address these open problems by showing that the first two problems are unary NP-hard and the third problem admits pseudo-polynomial-time algorithms. For the third problem, we also present a 2-approximation solution and a fully polynomial-time approximation scheme. Computational experiments show that our algorithms and solutions are efficient. When the jobs have identical processing times, we further present more efficient polynomial-time algorithms.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>assignable/generalized due dates</subject><subject>NP-hard</subject><subject>Polynomials</subject><subject>Scheduling</subject><subject>total weighted late work</subject><issn>0020-7543</issn><issn>1366-588X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kE1rHDEMhk1JoZu0P6Fg6Hm3smc847m1hH7BQiCk0JvR2Jpdp55xanu7pL--Xjalt-ggCfG8EnoZeytgI0DDewAJvWqbjQQpN1J0oEC-YCvRdN1aaf3jgq1OzPoEvWKXOd9DDaXbFQu39NtnX3jZE892T-4Q_LLjDymOgWZ-9GXPMWe_W7AOeEx8RwslDP4POe4OxB0WyrxEPvvFz3Vc-4KBH8nv9qVCoQL8GNPP1-zlhCHTm6d6xb5__nR3_XW9vfny7frjdm2bQZWaR7BO9KPqpRhQD1KLTgCpSap-Qt1bR9AIsEhqxN6NCkcx2kEOgDiSa67Yu_Pe-sWvA-Vi7uMhLfWkkboboG3atq-UOlM2xZwTTeYh-RnToxFgTsaaf8aak7Hmydiq42cd2bj4_F-lu152Sui2Ih_OiF-mmGaszwdnCj6GmKaEi62y5vkrfwGaCous</recordid><startdate>20231117</startdate><enddate>20231117</enddate><creator>Chen, Rubing</creator><creator>Gao, Yuan</creator><creator>Geng, Zhichao</creator><creator>Yuan, Jinjiang</creator><general>Taylor &amp; Francis</general><general>Taylor &amp; Francis LLC</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-9814-615X</orcidid></search><sort><creationdate>20231117</creationdate><title>Revisit the scheduling problem with assignable or generalized due dates to minimize total weighted late work</title><author>Chen, Rubing ; Gao, Yuan ; Geng, Zhichao ; Yuan, Jinjiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c395t-c3b0cd17b57219a89281610e5f257fa87cde0310cae5ba7db5ab1bc9290aabed3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Approximation</topic><topic>assignable/generalized due dates</topic><topic>NP-hard</topic><topic>Polynomials</topic><topic>Scheduling</topic><topic>total weighted late work</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Rubing</creatorcontrib><creatorcontrib>Gao, Yuan</creatorcontrib><creatorcontrib>Geng, Zhichao</creatorcontrib><creatorcontrib>Yuan, Jinjiang</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of production research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Rubing</au><au>Gao, Yuan</au><au>Geng, Zhichao</au><au>Yuan, Jinjiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Revisit the scheduling problem with assignable or generalized due dates to minimize total weighted late work</atitle><jtitle>International journal of production research</jtitle><date>2023-11-17</date><risdate>2023</risdate><volume>61</volume><issue>22</issue><spage>7630</spage><epage>7648</epage><pages>7630-7648</pages><issn>0020-7543</issn><eissn>1366-588X</eissn><abstract>We revisit the single-machine scheduling for minimising the total weighted late work with assignable due dates (ADD-scheduling) and generalised due dates (GDD-scheduling). In particular, we consider the following three problems: (i) the GDD-scheduling problem for minimising the total weighted late work, (ii) the ADD-scheduling problem for minimising the total weighted late work, and (iii) the ADD-scheduling problem for minimising the total late work. In the literature, the above three problems are proved to be NP-hard, but their exact complexity (unary NP-hardness or pseudo-polynomial-time solvability) are unknown. In this paper, we address these open problems by showing that the first two problems are unary NP-hard and the third problem admits pseudo-polynomial-time algorithms. For the third problem, we also present a 2-approximation solution and a fully polynomial-time approximation scheme. Computational experiments show that our algorithms and solutions are efficient. When the jobs have identical processing times, we further present more efficient polynomial-time algorithms.</abstract><cop>London</cop><pub>Taylor &amp; Francis</pub><doi>10.1080/00207543.2022.2160502</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-9814-615X</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0020-7543
ispartof International journal of production research, 2023-11, Vol.61 (22), p.7630-7648
issn 0020-7543
1366-588X
language eng
recordid cdi_proquest_journals_2869043447
source Taylor & Francis
subjects Algorithms
Approximation
assignable/generalized due dates
NP-hard
Polynomials
Scheduling
total weighted late work
title Revisit the scheduling problem with assignable or generalized due dates to minimize total weighted late work
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T06%3A20%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_econi&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Revisit%20the%20scheduling%20problem%20with%20assignable%20or%20generalized%20due%20dates%20to%20minimize%20total%20weighted%20late%20work&rft.jtitle=International%20journal%20of%20production%20research&rft.au=Chen,%20Rubing&rft.date=2023-11-17&rft.volume=61&rft.issue=22&rft.spage=7630&rft.epage=7648&rft.pages=7630-7648&rft.issn=0020-7543&rft.eissn=1366-588X&rft_id=info:doi/10.1080/00207543.2022.2160502&rft_dat=%3Cproquest_econi%3E2869043447%3C/proquest_econi%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2869043447&rft_id=info:pmid/&rfr_iscdi=true