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Optimal Dynamic Scheduling Policy for a Make-To-Stock Production System
This paper considers the dynamic scheduling problem of a single-server, make-to-stock queue with two products. For the case of Poisson demands and exponential production times, we show that it is optimal to produce the product with the larger b µ index when it is backordered. If the production times...
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Published in: | Operations research 1997-01, Vol.45 (1), p.42-53 |
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container_title | Operations research |
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creator | Ha, Albert Y |
description | This paper considers the dynamic scheduling problem of a single-server, make-to-stock queue with two products. For the case of Poisson demands and exponential production times, we show that it is optimal to produce the product with the larger b µ index when it is backordered. If the production times are identically distributed, the optimal policy can further be characterized by monotone switching curves. We also prove that a base stock policy coupled with a switching curve is optimal for some initial inventory levels. A simple linear switching rule for determining production priority is proposed and compared with other heuristic policies in a computational experiment. |
doi_str_mv | 10.1287/opre.45.1.42 |
format | article |
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A simple linear switching rule for determining production priority is proposed and compared with other heuristic policies in a computational experiment.</description><identifier>ISSN: 0030-364X</identifier><identifier>EISSN: 1526-5463</identifier><identifier>DOI: 10.1287/opre.45.1.42</identifier><identifier>CODEN: OPREAI</identifier><language>eng</language><publisher>Linthicum, MD: INFORMS</publisher><subject>applications ; Applied sciences ; Capital costs ; Cost efficiency ; Cost functions ; Dynamic programming ; dynamic programming/optimal control ; Exact sciences and technology ; Heuristics ; Inventory control, production control. Distribution ; inventory/production ; Make to stock ; Mathematical functions ; Operational research and scientific management ; Operational research. Management science ; Operations research ; optimal control policies ; Optimal policy ; Production costs ; Production scheduling ; Scheduling ; Scheduling, sequencing ; sequencing in a stochastic system ; Stochastic models ; Studies ; Unit costs</subject><ispartof>Operations research, 1997-01, Vol.45 (1), p.42-53</ispartof><rights>Copyright 1997 The Institute for Operations Research and the Management Sciences</rights><rights>1997 INIST-CNRS</rights><rights>Copyright Institute for Operations Research and the Management Sciences Jan/Feb 1997</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-e479af49ec5fa57efed9f34f69a02cdf45a9ebd2dc014e3d496c4a399b3c803d3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/171924$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://pubsonline.informs.org/doi/full/10.1287/opre.45.1.42$$EHTML$$P50$$Ginforms$$H</linktohtml><link.rule.ids>314,780,784,3692,27924,27925,58238,58471,62616</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=2624796$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Ha, Albert Y</creatorcontrib><title>Optimal Dynamic Scheduling Policy for a Make-To-Stock Production System</title><title>Operations research</title><description>This paper considers the dynamic scheduling problem of a single-server, make-to-stock queue with two products. For the case of Poisson demands and exponential production times, we show that it is optimal to produce the product with the larger b µ index when it is backordered. If the production times are identically distributed, the optimal policy can further be characterized by monotone switching curves. We also prove that a base stock policy coupled with a switching curve is optimal for some initial inventory levels. A simple linear switching rule for determining production priority is proposed and compared with other heuristic policies in a computational experiment.</description><subject>applications</subject><subject>Applied sciences</subject><subject>Capital costs</subject><subject>Cost efficiency</subject><subject>Cost functions</subject><subject>Dynamic programming</subject><subject>dynamic programming/optimal control</subject><subject>Exact sciences and technology</subject><subject>Heuristics</subject><subject>Inventory control, production control. Distribution</subject><subject>inventory/production</subject><subject>Make to stock</subject><subject>Mathematical functions</subject><subject>Operational research and scientific management</subject><subject>Operational research. Management science</subject><subject>Operations research</subject><subject>optimal control policies</subject><subject>Optimal policy</subject><subject>Production costs</subject><subject>Production scheduling</subject><subject>Scheduling</subject><subject>Scheduling, sequencing</subject><subject>sequencing in a stochastic system</subject><subject>Stochastic models</subject><subject>Studies</subject><subject>Unit costs</subject><issn>0030-364X</issn><issn>1526-5463</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1997</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNqFkM1PAjEQxRujiYjevHnZGD3pYj936dGgogkGEjDx1pRuC4Vli-0Sw39vySIePc3h_d6bmQfAJYIdhLv5g1t73aGsgzoUH4EWYjhLGc3IMWhBSGBKMvp5Cs5CWEAIOctYC_SH69quZJk8bSu5sioZq7kuNqWtZsnIlVZtE-N8IpN3udTpxKXj2qllMvKu2KjauioZb0OtV-fgxMgy6Iv9bIOPl-dJ7zUdDPtvvcdBqkjO6lTTnEtDuVbMSJZrowtuCDUZlxCrwlAmuZ4WuFAQUU0KyjNFJeF8SlQXkoK0wXWTu_bua6NDLRZu46u4UmDEEYM56UbovoGUdyF4bcTaxyf9ViAodk2JXVOCMoEExRG_2WfKoGRpvKyUDQcPznC8OovYVYMtQu38X2SOOKZRvWtUW8XCVuG_lbcNPbez-beNyq9th4UD9wMJHI6b</recordid><startdate>19970101</startdate><enddate>19970101</enddate><creator>Ha, Albert Y</creator><general>INFORMS</general><general>Operations Research Society of America</general><general>Institute for Operations Research and the Management Sciences</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88E</scope><scope>88F</scope><scope>8AL</scope><scope>8AO</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>K9.</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M1Q</scope><scope>M2O</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>19970101</creationdate><title>Optimal Dynamic Scheduling Policy for a Make-To-Stock Production System</title><author>Ha, Albert Y</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-e479af49ec5fa57efed9f34f69a02cdf45a9ebd2dc014e3d496c4a399b3c803d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1997</creationdate><topic>applications</topic><topic>Applied sciences</topic><topic>Capital costs</topic><topic>Cost efficiency</topic><topic>Cost functions</topic><topic>Dynamic programming</topic><topic>dynamic programming/optimal control</topic><topic>Exact sciences and technology</topic><topic>Heuristics</topic><topic>Inventory control, production control. Distribution</topic><topic>inventory/production</topic><topic>Make to stock</topic><topic>Mathematical functions</topic><topic>Operational research and scientific management</topic><topic>Operational research. Management science</topic><topic>Operations research</topic><topic>optimal control policies</topic><topic>Optimal policy</topic><topic>Production costs</topic><topic>Production scheduling</topic><topic>Scheduling</topic><topic>Scheduling, sequencing</topic><topic>sequencing in a stochastic system</topic><topic>Stochastic models</topic><topic>Studies</topic><topic>Unit costs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ha, Albert Y</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Military Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer science database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>ABI/INFORM global</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Military Database</collection><collection>ProQuest research library</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>ProQuest Central Basic</collection><jtitle>Operations research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ha, Albert Y</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal Dynamic Scheduling Policy for a Make-To-Stock Production System</atitle><jtitle>Operations research</jtitle><date>1997-01-01</date><risdate>1997</risdate><volume>45</volume><issue>1</issue><spage>42</spage><epage>53</epage><pages>42-53</pages><issn>0030-364X</issn><eissn>1526-5463</eissn><coden>OPREAI</coden><abstract>This paper considers the dynamic scheduling problem of a single-server, make-to-stock queue with two products. For the case of Poisson demands and exponential production times, we show that it is optimal to produce the product with the larger b µ index when it is backordered. If the production times are identically distributed, the optimal policy can further be characterized by monotone switching curves. We also prove that a base stock policy coupled with a switching curve is optimal for some initial inventory levels. A simple linear switching rule for determining production priority is proposed and compared with other heuristic policies in a computational experiment.</abstract><cop>Linthicum, MD</cop><pub>INFORMS</pub><doi>10.1287/opre.45.1.42</doi><tpages>12</tpages></addata></record> |
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subjects | applications Applied sciences Capital costs Cost efficiency Cost functions Dynamic programming dynamic programming/optimal control Exact sciences and technology Heuristics Inventory control, production control. Distribution inventory/production Make to stock Mathematical functions Operational research and scientific management Operational research. Management science Operations research optimal control policies Optimal policy Production costs Production scheduling Scheduling Scheduling, sequencing sequencing in a stochastic system Stochastic models Studies Unit costs |
title | Optimal Dynamic Scheduling Policy for a Make-To-Stock Production System |
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