A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA
Identifieur interne : 001303 ( Istex/Corpus ); précédent : 001302; suivant : 001304A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA
Auteurs : Horst TempelmeierSource :
- Production and Operations Management [ 1059-1478 ] ; 2002-12.
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Abstract
In this paper we consider the problem of supplier selection and purchase order sizing for a single item under dynamic demand conditions. Suppliers offer all‐units and/or incremental quantity discounts, which may vary over time. Although the problem refers to a typical planning task of a purchasing agent, which is often solved without algorithmic assistance, in an eBusiness (b2b) environment, the need for the integration of an automatic performance of this planning task into a web‐based procurement process becomes evident. A new model formulation for this problem is developed, and a simple but easily extendible heuristic procedure is presented and tested. The heuristic is implemented as part of the Advanced Planner and Optimizer (apo) software of SAP AG, Walldorf, Germany.
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DOI: 10.1111/j.1937-5956.2002.tb00474.x
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ISTEX:DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331Le document en format XML
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Suppliers offer all‐units and/or incremental quantity discounts, which may vary over time. Although the problem refers to a typical planning task of a purchasing agent, which is often solved without algorithmic assistance, in an eBusiness (b2b) environment, the need for the integration of an automatic performance of this planning task into a web‐based procurement process becomes evident. A new model formulation for this problem is developed, and a simple but easily extendible heuristic procedure is presented and tested. 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Suppliers offer all‐units and/or incremental quantity discounts, which may vary over time. Although the problem refers to a typical planning task of a purchasing agent, which is often solved without algorithmic assistance, in an eBusiness (b2b) environment, the need for the integration of an automatic performance of this planning task into a web‐based procurement process becomes evident. A new model formulation for this problem is developed, and a simple but easily extendible heuristic procedure is presented and tested. The heuristic is implemented as part of the Advanced Planner and Optimizer (apo) software of SAP AG, Walldorf, Germany.</abstract><qualityIndicators><score>6.428</score><pdfVersion>1.3</pdfVersion><pdfPageSize>486 x 720 pts</pdfPageSize><refBibsNative>true</refBibsNative><abstractCharCount>782</abstractCharCount><pdfWordCount>5721</pdfWordCount><pdfCharCount>37484</pdfCharCount><pdfPageCount>17</pdfPageCount><abstractWordCount>119</abstractWordCount></qualityIndicators><title>A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA</title><refBibs><json:item><host><author></author><title>“Supply contracts with quantity commitments and stochastic demand.”Quantitative Models for Supply Chain Management</title></host></json:item><json:item><author><json:item><name>W. C. 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(2000), Foundations of Inventory Management, McGraw‐Hill, Boston, MA.</title></host></json:item></refBibs><genre><json:string>article</json:string></genre><host><volume>11</volume><publisherId><json:string>POMS</json:string></publisherId><pages><total>17</total><last>515</last><first>499</first></pages><issn><json:string>1059-1478</json:string></issn><issue>4</issue><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><eissn><json:string>1937-5956</json:string></eissn><title>Production and Operations Management</title><doi><json:string>10.1111/(ISSN)1937-5956</json:string></doi></host><categories><wos><json:string>science</json:string><json:string>operations research & management science</json:string><json:string>engineering, manufacturing</json:string></wos><scienceMetrix><json:string>applied sciences</json:string><json:string>engineering</json:string><json:string>operations research</json:string></scienceMetrix></categories><publicationDate>2002</publicationDate><copyrightDate>2002</copyrightDate><doi><json:string>10.1111/j.1937-5956.2002.tb00474.x</json:string></doi><id>DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331</id><score>0.019569537</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a" type="main" xml:lang="en">A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>Blackwell Publishing Ltd</publisher><pubPlace>Oxford, UK</pubPlace><availability><p>© 2002 Production and Operations Management Society</p></availability><date>2002</date></publicationStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA</title><author xml:id="author-1"><persName><forename type="first">HORST</forename><surname>TEMPELMEIER</surname></persName><note type="biography">Horst Tempelmeier is Professor of Productions Management at the University of Cologne, Germany. He holds a Diploma in Business Management from the University of Giessen and Dr. rer. pol. and Dr. habil. degrees from the University of Trier. Prior to his current position, he held faculty positions at the Technical University Darmstadt and the Technical University Braunschweig. Dr. Tempelmeier is co‐author of an English monography on “Flexible Manufacturing Systems (published by Wiley) and of several German text books on operations management and logistics. His research interests include supply chain management, dynamic lot‐sizing under capacity constraints, stochastic modeling of production systems, and performance evaluation and design of flexible production systems. His work has been published in a number of journals, including OR Spektrum, European Journal of Operational Research, International Journal of Production Research, IIE Transactions, and Management Science. He serves as a consultant to numerous German companies.</note><affiliation>Horst Tempelmeier is Professor of Productions Management at the University of Cologne, Germany. He holds a Diploma in Business Management from the University of Giessen and Dr. rer. pol. and Dr. habil. degrees from the University of Trier. Prior to his current position, he held faculty positions at the Technical University Darmstadt and the Technical University Braunschweig. Dr. Tempelmeier is co‐author of an English monography on “Flexible Manufacturing Systems (published by Wiley) and of several German text books on operations management and logistics. His research interests include supply chain management, dynamic lot‐sizing under capacity constraints, stochastic modeling of production systems, and performance evaluation and design of flexible production systems. His work has been published in a number of journals, including OR Spektrum, European Journal of Operational Research, International Journal of Production Research, IIE Transactions, and Management Science. He serves as a consultant to numerous German companies.</affiliation><affiliation>Universität zu Köln, Seminar für Produktionswirtschaft, Albertus‐Magnus‐Platz, D‐50923 Köln, Germany</affiliation></author></analytic><monogr><title level="j">Production and Operations Management</title><idno type="pISSN">1059-1478</idno><idno type="eISSN">1937-5956</idno><idno type="DOI">10.1111/(ISSN)1937-5956</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><pubPlace>Oxford, UK</pubPlace><date type="published" when="2002-12"></date><biblScope unit="volume">11</biblScope><biblScope unit="issue">4</biblScope><biblScope unit="page" from="499">499</biblScope><biblScope unit="page" to="515">515</biblScope></imprint></monogr><idno type="istex">DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331</idno><idno type="DOI">10.1111/j.1937-5956.2002.tb00474.x</idno><idno type="ArticleID">POMS499</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2002</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>In this paper we consider the problem of supplier selection and purchase order sizing for a single item under dynamic demand conditions. Suppliers offer all‐units and/or incremental quantity discounts, which may vary over time. Although the problem refers to a typical planning task of a purchasing agent, which is often solved without algorithmic assistance, in an eBusiness (b2b) environment, the need for the integration of an automatic performance of this planning task into a web‐based procurement process becomes evident. A new model formulation for this problem is developed, and a simple but easily extendible heuristic procedure is presented and tested. The heuristic is implemented as part of the Advanced Planner and Optimizer (apo) software of SAP AG, Walldorf, Germany.</p></abstract><textClass xml:lang="en"><keywords scheme="keyword"><list><head>keywords</head><item><term>PURCHASING</term></item><item><term>ORDER SIZING</term></item><item><term>SUPPLIER SELECTION</term></item><item><term>HEURISTIC</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2002-12">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Wiley, elements deleted: body"><istex:xmlDeclaration>version="1.0" encoding="UTF-8" standalone="yes"</istex:xmlDeclaration><istex:document><component version="2.0" type="serialArticle" xml:lang="en"><header><publicationMeta level="product"><publisherInfo><publisherName>Blackwell Publishing Ltd</publisherName><publisherLoc>Oxford, UK</publisherLoc></publisherInfo><doi origin="wiley" registered="yes">10.1111/(ISSN)1937-5956</doi><issn type="print">1059-1478</issn><issn type="electronic">1937-5956</issn><idGroup><id type="product" value="POMS"></id><id type="publisherDivision" value="ST"></id></idGroup><titleGroup><title type="main" sort="PRODUCTION AND OPERATIONS MANAGEMENT">Production and Operations Management</title></titleGroup></publicationMeta><publicationMeta level="part" position="12004"><doi origin="wiley">10.1111/poms.2002.11.issue-4</doi><numberingGroup><numbering type="journalVolume" number="11">11</numbering><numbering type="journalIssue" number="4">4</numbering></numberingGroup><coverDate startDate="2002-12">December 2002</coverDate></publicationMeta><publicationMeta level="unit" type="article" position="7" status="forIssue"><doi origin="wiley">10.1111/j.1937-5956.2002.tb00474.x</doi><idGroup><id type="unit" value="POMS499"></id></idGroup><countGroup><count type="pageTotal" number="17"></count></countGroup><titleGroup><title type="tocHeading1">Original Article</title></titleGroup><copyright>© 2002 Production and Operations Management Society</copyright><eventGroup><event type="firstOnline" date="2009-01-05"></event><event type="publishedOnlineFinalForm" date="2009-01-05"></event><event type="xmlConverted" agent="Converter:BPG_TO_WML3G version:2.3.2 mode:FullText source:HeaderRef result:HeaderRef" date="2010-03-04"></event><event type="xmlConverted" agent="Converter:WILEY_ML3G_TO_WILEY_ML3GV2 version:3.8.8" date="2014-02-07"></event><event type="xmlConverted" agent="Converter:WML3G_To_WML3G version:4.1.7 mode:FullText,remove_FC" date="2014-11-03"></event></eventGroup><numberingGroup><numbering type="pageFirst" number="499">499</numbering><numbering type="pageLast" number="515">515</numbering></numberingGroup><linkGroup><link type="toTypesetVersion" href="file:POMS.POMS499.pdf"></link></linkGroup></publicationMeta><contentMeta><unparsedEditorialHistory>Received January 2000, revision received January 2002, accepted June 2002.</unparsedEditorialHistory><countGroup><count type="referenceTotal" number="25"></count><count type="linksCrossRef" number="2"></count></countGroup><titleGroup><title type="main">A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA</title></titleGroup><creators><creator creatorRole="author" xml:id="cr1" affiliationRef="#a1" noteRef="#fn1"><personName><givenNames>HORST</givenNames><familyName>TEMPELMEIER</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="a1" countryCode="DE"><unparsedAffiliation>Universität zu Köln, Seminar für Produktionswirtschaft, Albertus‐Magnus‐Platz, D‐50923 Köln, Germany</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en"><keyword xml:id="k1">PURCHASING</keyword><keyword xml:id="k2">ORDER SIZING</keyword><keyword xml:id="k3">SUPPLIER SELECTION</keyword><keyword xml:id="k4">HEURISTIC</keyword></keywordGroup><abstractGroup><abstract type="main" xml:lang="en"><p>In this paper we consider the problem of supplier selection and purchase order sizing for a single item under dynamic demand conditions. Suppliers offer all‐units and/or incremental quantity discounts, which may vary over time. Although the problem refers to a typical planning task of a purchasing agent, which is often solved without algorithmic assistance, in an eBusiness (b2b) environment, the need for the integration of an automatic performance of this planning task into a web‐based procurement process becomes evident. A new model formulation for this problem is developed, and a simple but easily extendible heuristic procedure is presented and tested. The heuristic is implemented as part of the Advanced Planner and Optimizer (apo) software of SAP AG, Walldorf, Germany.</p></abstract></abstractGroup></contentMeta><noteGroup><note xml:id="fn1"><label>2</label><p>Horst Tempelmeier is Professor of Productions Management at the University of Cologne, Germany. He holds a Diploma in Business Management from the University of Giessen and Dr. rer. pol. and Dr. habil. degrees from the University of Trier. Prior to his current position, he held faculty positions at the Technical University Darmstadt and the Technical University Braunschweig. Dr. Tempelmeier is co‐author of an English monography on “Flexible Manufacturing Systems (published by Wiley) and of several German text books on operations management and logistics. His research interests include supply chain management, dynamic lot‐sizing under capacity constraints, stochastic modeling of production systems, and performance evaluation and design of flexible production systems. His work has been published in a number of journals, including OR Spektrum, European Journal of Operational Research, International Journal of Production Research, IIE Transactions, and Management Science. He serves as a consultant to numerous German companies.</p></note></noteGroup></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>A SIMPLE HEURISTIC FOR DYNAMIC ORDER SIZING AND SUPPLIER SELECTION WITH TIME‐VARYING DATA</title></titleInfo><name type="personal"><namePart type="given">HORST</namePart><namePart type="family">TEMPELMEIER</namePart><affiliation>Universität zu Köln, Seminar für Produktionswirtschaft, Albertus‐Magnus‐Platz, D‐50923 Köln, Germany</affiliation><description>Horst Tempelmeier is Professor of Productions Management at the University of Cologne, Germany. He holds a Diploma in Business Management from the University of Giessen and Dr. rer. pol. and Dr. habil. degrees from the University of Trier. Prior to his current position, he held faculty positions at the Technical University Darmstadt and the Technical University Braunschweig. Dr. Tempelmeier is co‐author of an English monography on “Flexible Manufacturing Systems (published by Wiley) and of several German text books on operations management and logistics. His research interests include supply chain management, dynamic lot‐sizing under capacity constraints, stochastic modeling of production systems, and performance evaluation and design of flexible production systems. His work has been published in a number of journals, including OR Spektrum, European Journal of Operational Research, International Journal of Production Research, IIE Transactions, and Management Science. He serves as a consultant to numerous German companies.</description><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>Blackwell Publishing Ltd</publisher><place><placeTerm type="text">Oxford, UK</placeTerm></place><dateIssued encoding="w3cdtf">2002-12</dateIssued><edition>Received January 2000, revision received January 2002, accepted June 2002.</edition><copyrightDate encoding="w3cdtf">2002</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="references">25</extent></physicalDescription><abstract lang="en">In this paper we consider the problem of supplier selection and purchase order sizing for a single item under dynamic demand conditions. Suppliers offer all‐units and/or incremental quantity discounts, which may vary over time. Although the problem refers to a typical planning task of a purchasing agent, which is often solved without algorithmic assistance, in an eBusiness (b2b) environment, the need for the integration of an automatic performance of this planning task into a web‐based procurement process becomes evident. A new model formulation for this problem is developed, and a simple but easily extendible heuristic procedure is presented and tested. The heuristic is implemented as part of the Advanced Planner and Optimizer (apo) software of SAP AG, Walldorf, Germany.</abstract><subject lang="en"><genre>keywords</genre><topic>PURCHASING</topic><topic>ORDER SIZING</topic><topic>SUPPLIER SELECTION</topic><topic>HEURISTIC</topic></subject><relatedItem type="host"><titleInfo><title>Production and Operations Management</title></titleInfo><genre type="journal">journal</genre><identifier type="ISSN">1059-1478</identifier><identifier type="eISSN">1937-5956</identifier><identifier type="DOI">10.1111/(ISSN)1937-5956</identifier><identifier type="PublisherID">POMS</identifier><part><date>2002</date><detail type="volume"><caption>vol.</caption><number>11</number></detail><detail type="issue"><caption>no.</caption><number>4</number></detail><extent unit="pages"><start>499</start><end>515</end><total>17</total></extent></part></relatedItem><identifier type="istex">DBAEAC694D1ED9D5DB0201D262F1F98DC3D45331</identifier><identifier type="DOI">10.1111/j.1937-5956.2002.tb00474.x</identifier><identifier type="ArticleID">POMS499</identifier><accessCondition type="use and reproduction" contentType="copyright">© 2002 Production and Operations Management Society</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource><recordOrigin>Blackwell Publishing Ltd</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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