面向企业决策的线性规划模型参数估计与优化

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1、大连理工大学硕士学位论文coefficientandtheright-handside．First，throughchangingtheobjectivefunctioncoefficient，themethodcalledtheoptimalstructureoftheobjectivefunctioncoef!ficientandthemethodbasedonthedualmodelareproposed．Second，theinverseoptimalvaluemethodiSprovidedtojudgeandsolvetheparadox，includingtheo

2、riginal-dualmodelwhichisconstructedtojudgewhetherthereexiststheparadoxandtwomodels，constructedtosolvetheparadoxbychangingtheobjectivefunctioncoefficientandthetechnologicalcoefficientmatrix．ThentheadvantagesandeconomicsignificanceofthemethodiSdescribed．Lastly，thedualprogrammingconditionandthe

3、D．valueofobjectivefunctionmodelaregiventojudgewhetherthemore—for-lessparadoxOccursintransportationproblems．ThemaximumamountofsupplyanddemandmodeliSconstructedtoachievethemaximumadjustmentschemewhileincreasingthesupplywithnofreightincreasing．Andthereasonablepricingmethodisproposedtosolvethepa

4、radoxbYchangingtheunreasonabletransportationpriceandprovedtobetrue．ItiSfoundthattheproposedmodelandmethodexhibitexcellentfacevalidityforanumericalexample．KeyWords：OperationalResearch；LinearProgrammingSystemIdentification；More。·for·。LessParadox；InverseOptimalValueMethod；ParadoxinTranspotation

5、Problem．．III．．面向企业决策的线性规划模型参数估计与优化目录摘要⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．IAbstract⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．．II1绪论⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯11．1选题背景和意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯11．1．1选题背景⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯11．1．2选题意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯21．2相关文献综述⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯

6、⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯41．2．1线性规划模型参数估计的研究现状⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯41．2．1．1估计目标函数系数的研究⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．41．2．1．2估计技术系数矩阵的研究⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．71．2．1．3同时估计目标函数系数与技术系数矩阵的研究⋯⋯⋯⋯⋯⋯⋯．81．2．2参数优化以解决“多反而少”悖论的研究现状⋯⋯⋯⋯⋯⋯⋯⋯⋯81．2．2．1传统的线性规划“多反而少”悖论的研究现状⋯⋯⋯⋯⋯⋯⋯．91．2．2．2运输问题“多反而少"悖论的研究现状⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯111．3研究内容与论文框架⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯

7、⋯⋯⋯⋯⋯⋯．122线性规划模型参数的估计⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯152．1估计非负技术系数矩阵⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．152．1．1行估计模型⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．．152．1．2改进的行估计模型⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯。162．2估计标准化目标函数系数⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．172．2．1回顾最大决策效率方法⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯。l72．2．2最大决策效率方法的潜在问题⋯⋯⋯⋯⋯⋯⋯