




文档简介
CORRESPONDINGAUTHORTEL3031498143FAX3031498180EMAILADDRESSGEORGIADCPERICERTHGRMCGEORGIADISCOMPUTERSRECEIVEDINREVISEDFORM1SEPTEMBER2000ACCEPTED1OCTOBER2000ABSTRACTTHISPAPERPRESENTSANEWMATHEMATICALPROGRAMMINGFORMULATIONFORTHEPROBLEMOFDETERMININGTHEOPTIMALMANNERINWHICHSEVERALPRODUCTROLLSOFGIVENSIZESARETOBECUTOUTOFRAWROLLSOFONEORMORESTANDARDTYPESTHEOBJECTIVEISTOPERFORMTHISTASKSOASTOMAXIMIZETHEPRO“TTAKINGACCOUNTOFTHEREVENUEFROMTHESALES,THECOSTSOFTHEORIGINALROLLS,THECOSTSOFCHANGINGTHECUTTINGPATTERNANDTHECOSTSOFDISPOSALOFTHETRIMAMIXEDINTEGERLINEARPROGRAMMINGMILPMODELISPROPOSEDWHICHISSOLVEDTOGLOBALOPTIMALITYUSINGSTANDARDTECHNIQUESANUMBEROFEXAMPLEPROBLEMS,INCLUDINGANINDUSTRIALCASESTUDY,AREPRESENTEDTOILLUSTRATETHEECIENCYANDAPPLICABILITYOFTHEPROPOSEDMODELSCOPEANDPURPOSEONEDIMENSIONALCUTTINGSTOCKTRIMLOSSPROBLEMSARISEWHENPRODUCTIONITEMSMUSTBEPHYSICALLYDIVIDEDINTOPIECESWITHADIVERSITYOFSIZESINONEDIMENSIONEGWHENSLITTINGMASTERROLLSOFPAPERINTONARROWERWIDTHROLLSSUCHPROBLEMSOCCURWHENTHEREARENOECONOMIESOFSCALEASSOCIATEDWITHTHEPRODUCTIONOFTHELARGERRAWMASTERROLLSINGENERAL,THEOBJECTIVESINSOLVINGSUCHPROBLEMSARETO5P69MINIMIZETRIMLOSSP69AVOIDPRODUCTIONOVERRUNSAND/ORP69AVOIDUNNECESSARYSLITTERSETUPSTHEABOVEPROBLEMISPARTICULARLYIMPORTANTINTHEPAPERCONVERTINGINDUSTRYWHENASETOFPAPERROLLSNEEDTOBECUTFROMRAWPAPERROLLSSINCETHEWIDTHOFAPRODUCTISFULLYINDEPENDENTOFTHEWIDTHOFTHERAWPAPERAHIGHLYCOMBINATORIALPROBLEMARISESINGENERAL,THECUTTINGPROCESSALWAYSPRODUCESINEVITABLETRIMLOSSWHICHHASTOBEBURNEDORPROCESSEDINSOMEWASTETREATMENTPLANTTRIMLOSSPROBLEMSINTHEPAPERINDUSTRYHAVE,INRECENTYEARS,MAINLYBEENSOLVEDUSINGHEURISTICRULESTHEPRACTICALPROBLEMFORMULATIONHAS,THEREFORE,INMOSTCASESBEENRESTRICTEDBYTHEFACTTHATTHESOLUTIONMETHODSOUGHTTOBEABLETOHANDLETHEENTIREPROBLEMCONSEQUENTLY,ONLYASUBOPTIMALSOLUTIONTOTHEORIGINALPROBLEMHASBEENOBTAINEDAND03050548/02/SEEFRONTMATTERP72002ELSEVIERSCIENCELTDALLRIGHTSRESERVEDPIIS0305054800001027VERYOFTENTHISRATHERSIGNI“CANTECONOMICPROBLEMHASBEENLEFTTOAMANUALSTAGETHISWORKPRESENTSANOVELALGORITHMFORECIENTLYDETERMININGOPTIMALCUTTINGPATTERNSINTHEPAPERCONVERTINGPROCESSAMIXEDINTEGERLINEARPROGRAMMINGMODELISPROPOSEDWHICHISSOLVEDTOGLOBALOPTIMALITYUSINGAVAILABLECOMPUTERTOOLSANUMBEROFEXAMPLEPROBLEMSINCLUDINGANINDUSTRIALCASESTUDYAREPRESENTEDTOILLUSTRATETHEAPPLICABILITYOFTHEPROPOSEDALGORITHMP72002ELSEVIERSCIENCELTDALLRIGHTSRESERVEDKEYWORDSINTEGERPROGRAMMINGOPTIMIZATIONTRIMLOSSPROBLEMSPAPERCONVERTINGINDUSTRY1INTRODUCTIONANIMPORTANTPROBLEMWHICHISFREQUENTLYENCOUNTEREDININDUSTRIESSUCHASPAPERISRELATEDWITHTHEMOSTECONOMICMANNERINWHICHSEVERALPRODUCTROLLOFGIVENSIZESARETOBEPRODUCEDBYCUTTINGONEORMOREWIDERRAWROLLSAVAILABLEINONEORMORESTANDARDWIDTHSTHESOLUTIONOFTHISPROBLEMINVOLVESSEVERALINTERACTINGDECISIONSP69THENUMBEROFPRODUCTROLLSOFEACHSIZETOBEPRODUCEDTHISMAYBEALLOWEDTOVARYBETWEENGIVENLOWERANDUPPERBOUNDSTHEFORMERNORMALLYREECTTHE“RMORDERSTHATARECURRENTLYOUTSTANDING,WHILETHELATTERCORRESPONDTOTHEMAXIMUMCAPACITYOFTHEMARKETHOWEVER,CERTAINDISCOUNTSMAYHAVETOBEOEREDTOSELLSHEETSOVERANDABOVETHEQUANTITIESFORWHICH“RMORDERSAREAVAILABLEP69THENUMBEROFRAWROLLSOFEACHSTANDARDWIDTHTOBECUTROLLSMAYBEAVAILABLEINONEORMORESTANDARDWIDTHS,EACHOFADIERENTUNITPRICEP69THECUTTINGPATTERNFOREACHRAWROLLCUTTINGTAKESPLACEONAMACHINEEMPLOYINGANUMBEROFKNIVESOPERATINGINPARALLELONAROLLOFSTANDARDWIDTHWHILETHEPOSITIONOFTHEKNIVESMAYBECHANGEDFROMONEROLLTOTHENEXT,SUCHCHANGESMAYINCURCERTAINCOSTSFURTHERMORE,THEREMAYBECERTAINTECHNOLOGICALLIMITATIONSONTHEKNIFEPOSITIONSTHATMAYBEREALIZEDBYANYGIVENCUTTINGMACHINETHEOPTIMALSOLUTIONOFTHEABOVEPROBLEMISOFTENASSOCIATEDWITHTHEMINIMIZATIONOFTHETRIMAWASTETHATISGENERALLYUNAVOIDABLESINCEROLLSOFSTANDARDWIDTHSAREUSEDHOWEVER,TRIMLOSSMINIMIZATIONDOESNOTNECESSARILYIMPLYMINIMIZATIONOFTHECOSTOFTHERAWMATERIALSROLLSBEINGUSEDESPECIALLYIFSEVERALSTANDARDROLLSIZESAREAVAILABLEAMOREDIRECTECONOMICCRITERIONISTHEMAXIMIZATIONOFTHEPRO“TOFTHEOPERATIONTAKINGACCOUNTOFP69THEREVENUEFROMPRODUCTROLLSSALES,INCLUDINGTHEEECTSOFANYBULKDISCOUNTSP69THECOSTOFTHEROLLSTHATAREACTUALLYUSEDP69THECOSTS,IFANY,OFCHANGINGTHEKNIFEPOSITIONSONTHECUTTINGMACHINEP69THECOSTOFDISPOSINGOFTRIMWASTETHEABOVECONSTITUTESAHIGHLYCOMBINATORIALPROBLEMANDITISNOTSURPRISINGTHATTRADITIONALLYITSSOLUTIONHASOFTENBEENCARRIEDOUTMANUALLYBASEDONHUMANEXPERTISETHESIMPLI“EDVERSIONOFTHISPROBLEMISSIMILARTOTHECUTTINGSTOCKPROBLEMKNOWNINTHEOPERATIONRESEARCHLITERATURE,WHEREANUMBEROFORDEREDPIECESNEEDTOBECUTOBIGGERSTOREDPIECESINTHEMOSTECONOMICFASHIONINTHE1960SANDTHE1970S,SEVERALSCIENTI“CARTICLESWEREPUBLISHEDONTHEPROBLEMOF1042GSCHILLING,MCGEORGIADIS/COMPUTERSTHATRAWROLLSOFTHETYPETTHATPERMITSTHESMALLESTMINIMUM1044GSCHILLING,MCGEORGIADIS/COMPUTERSANDTHATEACHRAWROLLWILLBEUSEDTOPRODUCEPRODUCTROLLSOFASINGLETYPEONLYOVERALL,THISLEADSTOTHEFOLLOWINGUPPERBOUNDONTHENUMBEROFRAWROLLSTHATMAYBEREQUIREDJP13P0P24“P39P9P71P14P16NP13P0P24P71P87MINP82BP13P9P14P82/BP71P881WECANALSOCALCULATEALOWERBOUNDJP13P9P14ONTHEMINIMUMNUMBEROFRAWROLLSTHATARENECESSARYTOSATISFYTHEMINIMUMDEMANDFORTHEEXISTINGORDERSWEDOTHISBYASSUMINGTHATROLLSOFTHETYPETALLOWINGTHEMAXIMUMPOSSIBLEENGAGEMENTBP13P0P24P82AREUSED,ANDTHATNOTRIMISPRODUCEDHOWEVER,WEMUSTALSOTAKEACCOUNTOFPOSSIBLELIMITATIONSONTHENUMBEROFAVAILABLEKNIVESOVERALL,THISLEADSTOTHEFOLLOWINGLOWERBOUNDONTHENUMBEROFROLLSTHATMAYBEREQUIREDJP13P9P14“MAXP7P9P39P71P14P16NP13P9P14P71BP71MAXP82BP13P0P24P82,P9P39P71P14P16NP13P9P14P71MAXP82NP13P0P24P82P823MATHEMATICALFORMULATIONTHEAIMOFTHEMATHEMATICALFORMULATIONISTODETERMINETHETYPETOFEACHRAWROLLJTOBECUTANDTHENUMBEROFPRODUCTROLLSOFEACHTYPEITOBEPRODUCEDFROMIT31KEYVARIABLESTHEFOLLOWINGINTEGERVARIABLESAREINTRODUCEDNP71P72NUMBEROFPRODUCTROLLSOFTYPEITOBECUTOUTOFRAWROLLJAFII9773P71NUMBEROFPRODUCTROLLSOFTYPEIPRODUCEDOVERANDABOVETHEMINIMUMNUMBERORDEREDWENOTETHATNP71P72CANNOTEXCEEDP69THEMAXIMUMNUMBERNP13P0P24P71OFPRODUCTROLLSOFTYPEITHATCANBESOLDP69THEMAXIMUMNUMBEROFPRODUCTROLLSOFWIDTHBP71THATCANBEACCOMMODATEDWITHINAMAXIMUMENGAGEMENTBP13P0P24P82FORARAWROLLOFTYPETP69THEMAXIMUMNUMBERNP13P0P24P82OFKNIVESTHATCANBEAPPLIEDTOARAWROLLOFTYPETTHISLEADSTOTHEFOLLOWINGBOUNDSFORNP71P720NP71P72MINP1NP13P0P24P71,MAXP16P87P82P87P50BP13P0P24P82BP71,MAXP16P87P82P87P50NP13P0P24P82P2I“1,2,I,J“1,2,JP13P0P243ALSO0AFII9773P71NP13P0P24P71NP13P9P14P71,I“1,2,I4GSCHILLING,MCGEORGIADIS/COMPUTERSTHISSIMPLYIMPLIESTHATITISNOTNECESSARYTOCUTROLLJFURTHERMORE,THELIMITEDAVAILABILITYOFRAWROLLSOFAGIVENTYPETMAYBEEXPRESSEDINTERMSOFTHECONSTRAINTP40P13P0P24P9P72P14P16YP82P72JHP82,T“1,2,633CUTTINGCONSTRAINTSWENEEDTOENSURETHAT,IFAROLLJISTOBECUT,THENTHELIMITATIONSONTHEMINIMUMANDMAXIMUMENGAGEMENTAREOBSERVEDTHISISACHIEVEDVIATHECONSTRAINTSP50P9P82P14P16BP13P9P14P82YP82P72P39P9P71P14P16BP71NP71P72P50P9P82P14P16BP13P0P24P82YP82P72,J“1,2,JP13P0P247WENOTETHATTHEQUANTITYP9P39P71P14P16BP71NP71P72REPRESENTSTHETOTALWIDTHOFALLPRODUCTROLLSTOBECUTOUTOFRAWROLLJIFYP82P72“1FORSOMEROLLTYPET,THENCONSTRAINT7ENSURESTHATBP13P9P14P82P39P9P71P14P16BP71NP71P72BP13P0P24P821046GSCHILLING,MCGEORGIADIS/COMPUTERSONCEAGAIN,ATMOSTONEOFTHETERMSINTHISSUMMATIONCANBENONZEROCFCONSTRAINTS5AAND5BTHELATTERQUANTITYISGIVENBYP9P39P71P14P16BP71NP71P72OVERALL,TRIMDISPOSALRESULTSINTHEFOLLOWINGCOSTTERMCP3P9P19P16P40P13P0P24P9P72P14P16P1P50P9P82P14P16BP18P15P12P12P82YP82P72P39P9P71P14P16BP71NP71P72P2THEABOVETERMSCANNOWBECOLLECTEDINTHEFOLLOWINGOBJECTIVEFUNCTIONMAXP3P39P9P71P14P16PP71NP13P9P14P71AFII9773P71PP71CP3P9P19P2P71P40P13P0P24P9P72P14P16P9P82P14P16CP18P15P12P12P82YP82P72CP2P8P0P14P6P4P40P13P0P24P9P72P14P17ZP72CP3P9P19P16P40P13P0P24P9P72P14P16P1P50P9P82P14P16BP18P15P12P12P82YP82P72P39P9P71P14P16BP71NP71P72P2P411NOTETHATTHE“RSTTERMINTHEABOVEOBJECTIVEFUNCTIONIEP9P39P71P14P16PP71NP13P9P14P71ISACTUALLYACONSTANTANDDOESNOTAECTTHEOPTIMALSOLUTIONOBTAINED37DEGENERACYREDUCTIONANDCONSTRAINTTIGHTENINGINGENERAL,THEBASICFORMULATIONPRESENTEDABOVEISHIGHLYDEGENERATEGIVENANYFEASIBLEPOINT,ONECANGENERATEMANYOTHERSSIMPLYBYFORMINGALLPOSSIBLEORDERINGOFTHEROLLSSELECTEDTOBECUTMOREOVER,PROVIDEDALLRAWROLLSOFTHESAMETYPEARECUTCONSECUTIVELY,ALLTHESEFEASIBLEPOINTSWILLCORRESPONDTOEXACTLYTHESAMEVALUEOFTHEOBJECTIVEFUNCTIONTHEABOVEPROPERTYMAYHAVEADVERSEEECTSONTHEECIENCYOFTHESEARCHPROCEDURETHEREFORE,INORDERTOREDUCETHESOLUTIONDEGENERACYWITHOUTANYLOSSOFOPTIMALITY,WEINTRODUCETHEFOLLOWINGORDERINGCONSTRAINTSP39P9P71P14P16NP71P11P72P92P16P39P9P71P14P16NP71P72,J“2,2,JP13P0P2412THISENSURESTHATTHETOTALNUMBEROFPRODUCTROLLSCUTOUTOFRAWROLLJ1ISNEVERLOWERTHANTHECORRESPONDINGNUMBERFORROLLJALLCOMPLETELYUNUSEDRAWROLLSARELEFTLASTINTHISORDERING1048GSCHILLING,MCGEORGIADIS/COMPUTERSBP13P0P24P82BP13P9P14P82,WHICHRESULTSINONELESSCONSTRAINTFOREACHROLLJ4EXAMPLEPROBLEMSINTHISSECTION,WECONSIDERFOUREXAMPLEPROBLEMSOFINCREASINGCOMPLEXITYINORDERTOINVESTIGATETHECOMPUTATIONALBEHAVIOROFOURFORMULATIONFURTHERMOREANINDUSTRIALCASESTUDYISALSOPRESENTEDINALLCASES,WEASSUMETHATTHEMAXIMUMRAWROLLENGAGEMENTBP13P0P24P82ISEQUALTOTHECORRESPONDINGROLLWIDTHBP18P15P12P12P82THEGAMS/CPLEXVS60SOLVERHASBEENUSEDFORTHESOLUTION15ANDALLCOMPUTATIONSWERECARRIEDOUTONAALPHASERVER4100ANINTEGRALITYGAPOF01WASASSUMEDFORTHESOLUTIONOFALLPROBLEMS41EXAMPLE1OUR“RSTEXAMPLEISBASEDONTHATGIVENBYHARJUNKOSKI9SOMETRANSLATIONOFTHEVARIOUSCOSTCOECIENTSWASNECESSARYTOACCOUNTFORSLIGHTDIERENCESINTHEOBJECTIVEFUNCTIONSUSEDBYTHETWOFORMULATIONSALSONOTETHATTHEOBJECTIVEUSEDBYTHOSEAUTHORSISTHEMINIMIZATIONOFCOSTASOPPOSEDTOTHEMAXIMIZATIONOFPRO“TTHEREFORE,THESIGNOFTHEIROBJECTIVEFUNCTIONISOPPOSITETOTHATOFOURSGSCHILLING,MCGEORGIADIS/COMPUTERSTHUS,WITHTHEGIVENECONOMICDATATHEOPERATIONINCURSALOSSTHEOPTIMALSOLUTIONWITHINAMARGINOFOPTIMALITYOF01ISFOUNDWITHINLESSTHAN1CPUSATNODE49OFTHEBRANCHANDBOUNDALGORITHMUSINGABREADTH“RSTSEARCHSTRATEGYITMUSTBENOTEDTHATTHEINTEGRALITYGAPOFOURFORMULATIONISCOMPARABLETOTHATFORONEOFTHEFORMULATIONSPRESENTEDBYHARJUNKOSKI9DESPITETHEFACTTHATITDOESNOTEMPLOYANYAPRIORIENUMERATIONOFTHECUTTINGPATTERNSOURFORMULATIONALSOEXAMINESASMALLNUMBEROFNODESINORDERTODETECTTHEOPTIMALPOINTTABLE31050GSCHILLING,MCGEORGIADIS/COMPUTERS9849592GILMOREPC,GOMORYREALINEARPROGRAMMINGAPPROACHTOTHECUTTINGSTOCKPROBLEMPARTIIOPERATIONSRESEARCH196311863883HINXMANAITHETRIMLOSSANDASSORTMENTPROBLEMSASURVEYEUROPEANJOURNALOFOPERATIONALRESEARCH19805818GSCHILLING,MCGEORGIADIS/COMPUTERS44175845SWEENEYPE,HAESSLERRWONEDIMENSIONALCUTTINGSTOCKDECISIONSFORROLLSWITHMULTIPLEQUALITYGRADESEUROPEANJOURNALOFOPERATIONALRESEARCH199044224316FERREIRAJS,NEVESMA,FONSECAECASTROPATWOPHASEROLLCUTTINGPROBLEMEUROPEANJOURNALOFOPERATIONALRESEARCH199044185967GRADISARM,JESENKOJ,RESINOVICGOPTIMIZATIONOFROLLCUTTINGINCLOTHINGINDUSTRYCOMPUTERS10S945538GRADISARM,KLJAJICM,RESINOVICG,JESENKOJASEQUENTIALHEURISTICPROCEDUREFORONEDIMENSIONALCUTTINGEUROPEANJOURNALOFOPERATIONALRESEARCH1999114557689HARJUNKOSKII,WESTERLUNDT,ISAKSSONJ,SKRIFVARSHDIERENTFORMULATIONSFORSOLVINGTRIMLOSSPROBLEMSINAPAPERCONVERTINGMILLWITHILPCOMPUTERSANDCHEMICALENGINEERING199620S121610HARJUNKOSKII,WESTERLUNDT,PORNRDIERENTTRANSFORMATIONSFORSOLVINGNONCONVEXTRIMLOSSPROBLEMSBYMINLPEUROPEANJOURNALOFOPERATIONALRESEARCH199810559460311WESTERLUNDT,ISAKSSONJ,HARJUNKOSKIISOLVINGATWODIMENSIONALTRIMLOSSPROBLEMWITHMILPEUROPEANJOURNALOFOPERATIONALRESEARCH19981045728112WESTERLUNDT,HARJUNKOSKII,ISAKSSONJSOLVINGAPRODUCTIONOPTIMISATIONPROBLEMINAPAPERCONVERTINGMILLWITHMILPCOMPUTERSANDCHEMICALENGINEERING1998225637013WESTERLUNDT,IS
温馨提示
- 1. 本站所有资源如无特殊说明,都需要本地电脑安装OFFICE2007和PDF阅读器。图纸软件为CAD,CAXA,PROE,UG,SolidWorks等.压缩文件请下载最新的WinRAR软件解压。
- 2. 本站的文档不包含任何第三方提供的附件图纸等,如果需要附件,请联系上传者。文件的所有权益归上传用户所有。
- 3. 本站RAR压缩包中若带图纸,网页内容里面会有图纸预览,若没有图纸预览就没有图纸。
- 4. 未经权益所有人同意不得将文件中的内容挪作商业或盈利用途。
- 5. 人人文库网仅提供信息存储空间,仅对用户上传内容的表现方式做保护处理,对用户上传分享的文档内容本身不做任何修改或编辑,并不能对任何下载内容负责。
- 6. 下载文件中如有侵权或不适当内容,请与我们联系,我们立即纠正。
- 7. 本站不保证下载资源的准确性、安全性和完整性, 同时也不承担用户因使用这些下载资源对自己和他人造成任何形式的伤害或损失。
最新文档
- 2025年哈尔滨市工人文化宫工作人员招聘7人模拟试卷及1套参考答案详解
- 2025江西赣州市第五人民医院劳务派遣招聘精神科助理医师1名模拟试卷完整答案详解
- 2025福建福州市仓山区司法局一名编外人员情况模拟试卷及答案详解(夺冠系列)
- 2025年合肥巢湖学院招聘专职辅导员6人考前自测高频考点模拟试题(含答案详解)
- 2025黑龙江东北林业大学土木与交通学院派遣人才招聘1人模拟试卷及答案详解(全优)
- 2025广西来宾市政协办公室商调所属事业单位工作人员1人考前自测高频考点模拟试题及答案详解(考点梳理)
- 2025甘肃平凉市崆峒区第一批公益性岗位工作人员招聘58人模拟试卷(含答案详解)
- 2025甘肃金昌市市直和县直教育系统引进高层次和急需紧缺人才招聘35人(第二批)模拟试卷附答案详解
- 2025年哈尔滨道里区工程社区卫生服务中心招聘若干名模拟试卷及参考答案详解1套
- 2025年福建省漳州市圆山劳务派遣服务有限公司招聘若干人考前自测高频考点模拟试题附答案详解(突破训练)
- 硫酸安全培训与防范课件
- BIM概述课件教学课件
- 农作物施肥精准手册
- 医疗机构医疗质量安全专项整治行动自查自纠报告
- 中建土建劳务招标标准清单编制参考
- 待灭菌物品的装载
- 2025年职业病诊断医师考核试题(答案)
- 中学窗帘采购项目方案投标文件(技术文件)
- 湖北省老年教育管理办法
- 人教新版(PEP)四年级上册单元测试卷 Unit1 Helping at home (含听力音频听力原文及答案)
- 渔政执法快艇管理办法
评论
0/150
提交评论