Order acceptance and scheduling with delivery under generalized parameters
Inspired by the concept of generalized due dates introduced by Hall ( IIE Transactions , 18(2), 220–222), in this article we first define four new generalized parameters in machine scheduling: the generalized release dates (GRD), generalized processing times (GPT), generalized rejection costs (GRC),...
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| Veröffentlicht in: | Naval research logistics 2023-12, Vol.70 (8), p.844-857 |
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| creator | Lu, Lingfa Ou, Jinwen Yu, Xue Zhang, Liqi |
| description | Inspired by the concept of generalized due dates introduced by Hall (
IIE Transactions
, 18(2), 220–222), in this article we first define four new generalized parameters in machine scheduling: the generalized release dates (GRD), generalized processing times (GPT), generalized rejection costs (GRC), and generalized delivery times (GDT). We then study order acceptance and scheduling problems with delivery consideration under the generalized parameters of GRD, GPT, GRC, and GDT, respectively. The objective of each scheduling problem in consideration is to minimize the maximum delivery completion time of the accepted jobs plus the total rejection penalty cost of the rejected jobs. We show that two of the six problems studied in this article are weakly NP‐hard while the other four ones can be solved in polynomial time. For each NP‐hard problem, we provide a pseudo‐polynomial time algorithm, a 2‐approximation algorithm and a fully polynomial‐time approximation scheme. |
| doi_str_mv | 10.1002/nav.22135 |
| format | Article |
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IIE Transactions
, 18(2), 220–222), in this article we first define four new generalized parameters in machine scheduling: the generalized release dates (GRD), generalized processing times (GPT), generalized rejection costs (GRC), and generalized delivery times (GDT). We then study order acceptance and scheduling problems with delivery consideration under the generalized parameters of GRD, GPT, GRC, and GDT, respectively. The objective of each scheduling problem in consideration is to minimize the maximum delivery completion time of the accepted jobs plus the total rejection penalty cost of the rejected jobs. We show that two of the six problems studied in this article are weakly NP‐hard while the other four ones can be solved in polynomial time. For each NP‐hard problem, we provide a pseudo‐polynomial time algorithm, a 2‐approximation algorithm and a fully polynomial‐time approximation scheme.</description><identifier>ISSN: 0894-069X</identifier><identifier>EISSN: 1520-6750</identifier><identifier>DOI: 10.1002/nav.22135</identifier><language>eng</language><publisher>New York: Wiley Subscription Services, Inc</publisher><subject>Algorithms ; Approximation ; Completion time ; Delivery scheduling ; Mathematical analysis ; Parameters ; Polynomials ; Rejection</subject><ispartof>Naval research logistics, 2023-12, Vol.70 (8), p.844-857</ispartof><rights>2023 Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c252t-22e9084b97f39c1702323086b72e11d76fd4b855f365d056be787f8a4abe41e43</cites><orcidid>0000-0002-7419-3808</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27915,27916</link.rule.ids></links><search><creatorcontrib>Lu, Lingfa</creatorcontrib><creatorcontrib>Ou, Jinwen</creatorcontrib><creatorcontrib>Yu, Xue</creatorcontrib><creatorcontrib>Zhang, Liqi</creatorcontrib><title>Order acceptance and scheduling with delivery under generalized parameters</title><title>Naval research logistics</title><description>Inspired by the concept of generalized due dates introduced by Hall (
IIE Transactions
, 18(2), 220–222), in this article we first define four new generalized parameters in machine scheduling: the generalized release dates (GRD), generalized processing times (GPT), generalized rejection costs (GRC), and generalized delivery times (GDT). We then study order acceptance and scheduling problems with delivery consideration under the generalized parameters of GRD, GPT, GRC, and GDT, respectively. The objective of each scheduling problem in consideration is to minimize the maximum delivery completion time of the accepted jobs plus the total rejection penalty cost of the rejected jobs. We show that two of the six problems studied in this article are weakly NP‐hard while the other four ones can be solved in polynomial time. For each NP‐hard problem, we provide a pseudo‐polynomial time algorithm, a 2‐approximation algorithm and a fully polynomial‐time approximation scheme.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>Completion time</subject><subject>Delivery scheduling</subject><subject>Mathematical analysis</subject><subject>Parameters</subject><subject>Polynomials</subject><subject>Rejection</subject><issn>0894-069X</issn><issn>1520-6750</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNotkE9LwzAYh4MoOKcHv0HAk4fON0nzp0cZOpXBLgreQpq83Tq6ribtZH56N-fpd3n4PfAQcstgwgD4Q-t2E86ZkGdkxCSHTGkJ52QEpsgzUMXnJblKaQ0AKgc5Im-LGDBS5z12vWs9UtcGmvwKw9DU7ZJ-1_2KBmzqHcY9HdojvcQWo2vqHwy0c9FtsMeYrslF5ZqEN_87Jh_PT-_Tl2y-mL1OH-eZ55L3GedYgMnLQlei8EwDF1yAUaXmyFjQqgp5aaSshJIBpCpRG10Zl7sSc4a5GJO7028Xt18Dpt6ut0NsD0rLjVHAjC7Egbo_UT5uU4pY2S7WGxf3loE9prKHVPYvlfgFOxRbpw</recordid><startdate>202312</startdate><enddate>202312</enddate><creator>Lu, Lingfa</creator><creator>Ou, Jinwen</creator><creator>Yu, Xue</creator><creator>Zhang, Liqi</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>7TN</scope><scope>8FD</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>JQ2</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-7419-3808</orcidid></search><sort><creationdate>202312</creationdate><title>Order acceptance and scheduling with delivery under generalized parameters</title><author>Lu, Lingfa ; Ou, Jinwen ; Yu, Xue ; Zhang, Liqi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c252t-22e9084b97f39c1702323086b72e11d76fd4b855f365d056be787f8a4abe41e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Approximation</topic><topic>Completion time</topic><topic>Delivery scheduling</topic><topic>Mathematical analysis</topic><topic>Parameters</topic><topic>Polynomials</topic><topic>Rejection</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lu, Lingfa</creatorcontrib><creatorcontrib>Ou, Jinwen</creatorcontrib><creatorcontrib>Yu, Xue</creatorcontrib><creatorcontrib>Zhang, Liqi</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Technology Research Database</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</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>Naval research logistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lu, Lingfa</au><au>Ou, Jinwen</au><au>Yu, Xue</au><au>Zhang, Liqi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Order acceptance and scheduling with delivery under generalized parameters</atitle><jtitle>Naval research logistics</jtitle><date>2023-12</date><risdate>2023</risdate><volume>70</volume><issue>8</issue><spage>844</spage><epage>857</epage><pages>844-857</pages><issn>0894-069X</issn><eissn>1520-6750</eissn><abstract>Inspired by the concept of generalized due dates introduced by Hall (
IIE Transactions
, 18(2), 220–222), in this article we first define four new generalized parameters in machine scheduling: the generalized release dates (GRD), generalized processing times (GPT), generalized rejection costs (GRC), and generalized delivery times (GDT). We then study order acceptance and scheduling problems with delivery consideration under the generalized parameters of GRD, GPT, GRC, and GDT, respectively. The objective of each scheduling problem in consideration is to minimize the maximum delivery completion time of the accepted jobs plus the total rejection penalty cost of the rejected jobs. We show that two of the six problems studied in this article are weakly NP‐hard while the other four ones can be solved in polynomial time. For each NP‐hard problem, we provide a pseudo‐polynomial time algorithm, a 2‐approximation algorithm and a fully polynomial‐time approximation scheme.</abstract><cop>New York</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/nav.22135</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-7419-3808</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Naval research logistics, 2023-12, Vol.70 (8), p.844-857 |
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| language | eng |
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| source | Wiley Online Library Journals; Business Source Complete |
| subjects | Algorithms Approximation Completion time Delivery scheduling Mathematical analysis Parameters Polynomials Rejection |
| title | Order acceptance and scheduling with delivery under generalized parameters |
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