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Lecture  LP Duality In Lecture  we saw the Maxow Mincut Theorem which stated that the Lecture  LP Duality In Lecture  we saw the Maxow Mincut Theorem which stated that the

Lecture LP Duality In Lecture we saw the Maxow Mincut Theorem which stated that the - PDF document

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Lecture LP Duality In Lecture we saw the Maxow Mincut Theorem which stated that the - PPT Presentation

This theorem gave us a method to prove that a given 64258ow is optimal simply exhibit a cut with the same value This theorem for 64258ows and cuts in a graph is a speci64257c instance of the LP Duality Theorem which relates the optimal values of LP ID: 23918

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LECTURE5.LPDUALITY2this,lettingy1;y2;y3bethecoecientsofourlinearcombination.Thenwemusthave4y1+2y2+3y228y1+y2+2y33y1;y2;y30andweseekmin(12y1+3y2+4y3)ThistooisanLP!WerefertothisLPasthedualandtheoriginalLPastheprimal.Theactualchoiceofwhichproblemistheprimalandwhichisthedualisnotimportantsincethedualofthedualisequaltotheprimal.Wedesignedthedualtoserveasamethodofconstructinganupperboundontheoptimalvalueoftheprimal,soifyisafeasiblesolutionforthedualandxisafeasiblesolutionfortheprimal,then2x1+3x212y1+3y2+4y3.Ifwecan ndtwofeasiblesolutionsthatmaketheseequal,thenweknowwehavefoundtheoptimalvaluesoftheseLP.Inthiscasethefeasiblesolutionsx1=1 2;x2=5 4andy1=5 16;y2=0;y3=1 4givethesamevalue4.75,whichthereforemustbetheoptimalvalue.5.1.1GeneralizationIngeneral,theprimalLPP=max(c�xjAxb;x0;x2Rn)correspondstothedualLP,D=min(b�yjA�yc;y0;y2Rm)whereAisanmnmatrix.Whenthereareequalityconstraintsorvariablesthatmaybenegative,theprimalLPP=max(c�x)s.t.aixbifori2I1aix=bifori2I2xj0forj2J1xj2Rforj2J2correspondstothedualLPD=min(b�y)s.t.yi0fori2I1yi2Rfori2I2Ajycjforj2J1Ajy=cjforj2J2 LECTURE5.LPDUALITY4 Figure5.1:TheobjectivevectorliesintheconespannedbytheconstraintvectorsSupposeforcontradictionthatcdoesnotlieinthiscone.ThentheremustexistaseparatinghyperplanebetweencandK:i.e.,thereexistsavectord2Rnsuchthata�id0foralli2I,butc�d�0.Nowconsiderthepointz=x+dforsometiny�0.Notethefollowing:Forsmallenough,thepointzsatisifestheconstraintsAzb.Considera�jzbforj62I:sincethisconstraintwasnottightforx,wewon'tviolateitifissmallenough.Andfora�jzbwithj2Iwehavea�jz=a�jx+a�jd=b+a�jdbsince�0anda�jd0.Theobjectivefunctionvalueincreasessincec�z=c�x+c�d�c�x.Thiscontradictsthefactthatxwasoptimal.Thereforethevectorclieswithintheconemadeofthenormalstotheconstraints,socisapositivelinearcombinationofthesenormals.Chooseifori2Isothatc=Pi2Iiai;0andsetj=0forj62I.Weknow0.A�=Pi2[m]iai=Pi2Iiai=c.b�=Pi2Ibii=Pi2I(aix)i=Pi2Iiaix=c�x.Thereforeisasolutiontothedualwithc�x=b�,sobyTheWeakDualityTheorem,OPT(P)=OPT(D). AsomewhatmorerigorousproofnotrelyingonourgeometricintuitionthatthereshouldbeaseparatinghyperplanebetweenaconeandavectornotspannedbytheconereliesonalemmabyFarkasthatoftencomesinseveralforms.TheformsweshalluseareasfollowsTheorem5.3(Farkas'Lemma(1894)-Form1).GivenA2Rmnandb2Rm,exactlyoneofthefollowingstatementsistrue.