Chapter 7 Test Bank PDF

Preview

Summary

Quantitative Analysis for Management, 11e (Render)Chapter 7 Linear Programming Models: Graphical and ComputerMethods Management resources that need control include machinery usage, labor volume, money spent, time used, warehouse space used, and material usage. Answer: TRUE Diff: 1 Topic: INTRODUCTIO...

Description

Quant i t at i veAnal ys i sf orManag e me nt , 1 1 e( Re nde r ) Cha pt e r7 Li ne a rPr ogr a mmi ngMode l s : Gr a phi c a la ndComput e rMe t hods 1 )Ma na ge me ntr e s our c e st ha tne e dc ont r oli nc l udema c hi ne r yus a ge , l a borvol ume ,mone ys pe nt , t i meus e d, wa r e hous es pac eus e d, andma t e r i a lus a ge . Ans we r :TRUE Di ff: 1 Topi c :I NTRODUCTI ON 2 )I nt het e r ml i ne a rpr ogr a mmi ng,t hewor dpr ogr a mmi ngc ome sf r om t hephr a s e" c omput e rpr ogr a mmi ng. " Ans we r :F ALSE Di ff: 2 Topi c :I NTRODUCTI ON 3 )Oneoft heas s umpt i onsofLPi s" s i mul t a ne i t y . " Ans we r :F ALSE Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 4 )Anyl i ne a rpr ogr a mmi ngpr obl e mc a nbes ol ve dus i ngt hegr a phi c a ls ol ut i onpr oc e dur e . Ans we r :F ALSE Di ff: 1 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 5 )AnLPf or mul a t i ont ypi c a l l yr e qui r e sfindi ngt hema xi mum va l ueofa nobj e c t i vewhi l es i mul t a ne ous l y maxi mi zi ngus a geoft her e s our c ec ons t r ai nt s . Ans we r :F ALSE Di ff: 2 Topi c :FORMULATI NGLPPROBLEMS 6 )The r ea r enol i mi t a t i onsont henumbe rofc ons t r a i nt sorva r i a bl e st ha tc anbegr aphe dt os ol vea nLPpr obl e m. Ans we r :F ALSE Di ff: 1 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 7 )Re s our c er e s t r i c t i onsa r ec a l l e dc ons t r ai nt s . Ans we r :TRUE Di ff: 1 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 8 )Oneoft hea s s umpt i onsofLPi s" pr opor t i onal i t y . " Ans we r :TRUE Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM

1 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

9 )Thes e tofs ol ut i onpoi nt st ha ts a t i s fie sa l lofal i ne arpr ogr a mmi ngpr obl e m' sc ons t r a i nt ss i mul t ane ous l yi s de fine da st hef e as i bl er e gi oni ngr a phi c a ll i ne a rpr ogr a mmi ng . Ans we r :TRUE Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 1 0 )Anobj e c t i vef unc t i oni sne c e s s ar yi nama xi mi z a t i onpr obl e m buti snotr e qui r e di nami ni mi z a t i onpr obl e m. Ans we r :F ALSE Di ff: 1 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 1 1 )I ns omei ns t a nc e s , ani nf e a s i bl es ol ut i onma ybet heopt i mum f oundb yt hec or ne rpoi ntme t hod. Ans we r :F ALSE Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 1 2 )Ther a t i onal i t ya s s umpt i oni mpl i e st ha ts ol ut i onsne e dnotbei nwhol enumbe r s( i nt e ge r s ) . Ans we r :F ALSE Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 1 3 )Thes ol ut i ont oal i ne a rpr ogr a mmi ngpr obl e m mus ta l wa ysl i eonac ons t r a i nt . Ans we r :TRUE Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 1 4 )I nal i ne a rpr ogr a m,t hec ons t r a i nt smus tbel i ne a r , butt heobj e c t i vef unc t i onma ybenonl i ne a r . Ans we r :F ALSE Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 1 5 )Re s our c emi xpr obl e msus eLPt ode c i deho w muc hofe a c hpr oduc tt oma ke , gi ve nas e r i e sofr e s our c e r e s t r i c t i ons . Ans we r :F ALSE Di ff: 2 Topi c :FORMULATI NGLPPROBLEMS 1 6 )Thee xi s t e nc eofnon-ne ga t i vi t yc ons t r ai nt si nat wo-var i abl el i ne a rpr ogr a mi mpl i e st ha twea r ea l wa ys wor ki ngi nt henor t hwe s tqua dr a ntofagr a ph. Ans we r :F ALSE Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 1 7 )I nl i ne arpr ogr a mmi ngt e r mi nol ogy ," dua lpr i c e "a nd" s e ns i t i vi t ypr i c e "ar es ynonyms . Ans we r :F ALSE Di ff: 2 Topi c :SENS I TI VI TYANAL YSI S

2 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

1 8 )Anyt i met ha tweha vea ni s opr ofitl i net ha ti spa r a l l e lt oac ons t r a i nt , weha vet hepos s i bi l i t yofmul t i pl e s ol ut i ons . Ans we r :TRUE Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 1 9 )I ft hei s opr ofitl i nei snotpar a l l e lt oac ons t r ai nt , t he nt hes ol ut i onmus tbeuni que . Ans we r :TRUE Di ff: 2 Topi c :FOURSPECI ALCASESI N LP AACSB:Re fle c t i veThi nki ng 2 0 )Whe nt woormor ec ons t r ai nt sc onfli c twi t honea not he r , weha veac ondi t i onc al l e dunbounde dne s s . Ans we r :F ALSE Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 2 1 )Thea ddi t i onofar e dunda ntc ons t r ai ntl owe r st hei s opr ofitl i ne . Ans we r :F ALSE Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 2 2 )Se ns i t i vi t ya na l ys i se na bl e sust ol ooka tt hee ffe c t sofc ha ngi ngt hec oe ffic i e nt si nt heobj e c t i vef unc t i on, onea t at i me . Ans we r :TRUE Di ff: 2 Topi c :SENS I TI VI TYANAL YSI S 2 3 )Awi de l yus e dma t he ma t i c a lpr ogr a mmi ngt e c hni quede s i gne dt ohe l pmana ge r sandde c i s i onma ki ngr e l a t i ve t or e s our c eal l oc a t i oni sc al l e d_ _ __ __ _ _. A)l i ne a rpr ogr a mmi ng B)c omput e rpr ogr a mmi ng C)c ons t r a i ntpr ogr a mmi ng D)goa lpr ogr a mmi ng E)Noneoft hea bove Ans we r :A Di ff: 1 Topi c :I NTRODUCTI ON 2 4 )T ypi c a lr e s our c e sofanor gani za t i oni nc l ude_ __ _ __ _ _. A)ma c hi ne r yus a ge B)l aborvol ume C)war e hous es pac eut i l i z a t i on D)r a w ma t e r i a lus a ge E)Al loft heabove Ans we r :E Di ff: 1 Topi c :I NTRODUCTI ON

3 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

2 5 )Whi c hoft hef ol l owi ngi snotapr ope r t yofa l ll i ne a rpr ogr a mmi ngpr obl e ms ? A)t hepr e s e nc eofr e s t r i c t i ons B)opt i mi z a t i onofs omeobj e c t i ve C)ac omput e rpr ogr a m D)a l t e r na t ec our s e sofa c t i ont oc hoos ef r om E)us a geofonl yl i ne are qua t i onsa ndi ne qua l i t i e s Ans we r :C Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 2 6 )Af e as i bl es ol ut i ont oal i ne arpr ogr a mmi ngpr obl e m A)mus tbeac or ne rpoi ntoft hef e as i bl er e gi on. B)mus ts a t i s f ya l loft hepr obl e m' sc ons t r ai nt ss i mul t ane ous l y . C)ne e dnots a t i s f ya l loft hec ons t r a i nt s , onl yt henon-ne ga t i vi t yc ons t r a i nt s . D)mus tgi vet hema xi mum pos s i bl epr ofit . E)mus tgi vet hemi ni mum pos s i bl ec os t . Ans we r :B Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 2 7 )I nf e a s i bi l i t yi nal i ne a rpr ogr a mmi ngpr obl e m oc c ur swhe n A)t he r ei sa ni nfini t es ol ut i on. B)ac ons t r a i nti sr e dunda nt . C)mor et hanones ol ut i oni sopt i ma l . D)t hef e as i bl er e gi oni sunbounde d. E)t he r ei snos ol ut i ont ha ts a t i s fie sa l lt hec ons t r a i nt sgi ve n. Ans we r :E Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 2 8 )I namaxi mi za t i onpr obl e m, whe noneormor eoft hes ol ut i onva r i a bl e sa ndt hepr ofitc a nbema dei nfini t e l y l ar gewi t houtvi ol a t i nganyc ons t r a i nt s ,t hel i ne a rpr ogr a m ha s A)a ni nf e as i bl es ol ut i on. B)a nunbounde ds ol ut i on. C)ar e dunda ntc ons t r a i nt . D)a l t e r na t eopt i ma ls ol ut i ons . E)Noneoft hea bove Ans we r :B Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 2 9 )Whi c hoft hef ol l owi ngi snotapa r tofe ve r yl i ne arpr ogr a mmi ngpr obl e mf or mul a t i on? A)a nobj e c t i vef unc t i on B)as e tofc ons t r ai nt s C)non-ne ga t i vi t yc ons t r a i nt s D)ar e dunda ntc ons t r a i nt E)ma xi mi z a t i onormi ni mi z a t i onofal i ne a rf unc t i on Ans we r :D Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 3 0 )Whe na ppr opr i a t e , t heopt i ma ls ol ut i ont oama xi mi z a t i onl i ne a rpr ogr a mmi ngpr obl e mc a nbef oundby gr a phi ngt hef e as i bl er e gi onand A)findi ngt hepr ofita te ve r yc or ne rpoi ntoft hef e as i bl er e gi ont os e ewhi c honegi ve st hehi ghe s tva l ue . B)movi ngt hei s opr ofitl i ne st owar dst heor i gi ni napa r a l l e lf as hi onunt i lt hel as tpoi nti nt hef e a s i bl er e gi oni s e nc ount e r e d. 4 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

C)l oc a t i ngt hepoi ntt ha ti shi ghe s tont hegr a ph. D)Noneoft hea bove E)Al loft heabove Ans we r :A Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 3 1 )Thema t he ma t i c a lt he or ybe hi ndl i ne a rpr ogr a mmi ngs t a t e st ha tanopt i ma ls ol ut i ont oanypr obl e m wi l ll i ea t a ( n)__ _ __ _ __oft hef e as i bl er e gi on. A)i nt e r i orpoi ntorc e nt e r B)ma xi mum poi ntormi ni mum poi nt C)c or ne rpoi ntore xt r e mepoi nt D)i nt e r i orpoi ntore xt r e mepoi nt E)Noneoft hea bove Ans we r :C Di ff: 1 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 3 2 )Whi c hoft hef ol l owi ngi snotapr ope r t yofl i ne a rpr ogr a ms ? A)oneobj e c t i vef unc t i on B)a tl e a s tt wos e pa r a t ef e as i bl er e gi ons C)a l t e r na t i vec our s e sofa c t i on D)oneormor ec ons t r ai nt s E)obj e c t i vef unc t i ona ndc ons t r a i nt sa r el i ne ar Ans we r :B Di ff: 1 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 3 3 )Thec or ne rpoi nts ol ut i onme t hod A)wi l lal wa yspr ovi deone , a ndonl yone , opt i mum. B)wi l lyi e l ddi ffe r e ntr e s ul t sf r om t hei s opr ofitl i nes ol ut i onme t hod. C)r e qui r e st ha tt hepr ofitf r om a l lc or ne r soft hef e as i bl er e gi onbec ompar e d. D)r e qui r e st ha ta l lc or ne r sc r e a t e db ya l lc ons t r ai nt sbec ompa r e d. E)wi l lnotpr ovi deas ol ut i ona ta ni nt e r s e c t i onorc or ne rwhe r eanon-ne ga t i vi t yc ons t r a i nti si nvol ve d. Ans we r :C Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM

5 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

3 4 )Whe nac ons t r a i ntl i neboundi ngaf e as i bl er e gi onhast hes ames l opea sa ni s opr ofitl i ne , A)t he r ema ybemor et ha noneopt i mum s ol ut i on. B)t hepr obl e mi nvol ve sr e dunda nc y . C)a ne r r orha sbe e nma dei nt hepr obl e mf or mul a t i on. D)ac ondi t i onofi nf e as i bi l i t ye xi s t s . E)Noneoft hea bove Ans we r :A Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 3 5 )Thes i mul t ane ouse qua t i onme t hodi s A)a nal t e r na t i vet ot hec or ne rpoi ntme t hod. B)us e f ulonl yi nmi ni mi z a t i onme t hods . C)a na l ge br ai cme a nsf ors ol vi ngt hei nt e r s e c t i onoft woormor ec ons t r a i nte qua t i ons . D)us e f ulonl ywhe nmor et hant wopr oduc tva r i a bl e se xi s ti napr oduc tmi xpr obl e m. E)Noneoft hea bove Ans we r :C Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 3 6 )Cons i de rt hef ol l o wi ngl i ne arpr ogr a mmi ngpr obl e m:

Thema xi mum pos s i bl eva l uef ort heobj e c t i vef unc t i oni s A)3 6 0. B)4 80 . C)1 52 0 . D)1 5 60 . E)Noneoft hea bove Ans we r :C Di ff: 3 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s

6 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

3 7 )Cons i de rt hef ol l o wi ngl i ne arpr ogr a mmi ngpr obl e m:

Thef e as i bl ec or ne rpoi nt sar e( 48 , 8 4 ) , ( 0 , 1 2 0) , ( 0, 0) , ( 9 0 , 0 ) .Wha ti st hema xi mum pos s i bl eva l uef ort heobj e c t i ve f unc t i on? A)1 0 32 B)1 20 0 C)3 60 D)1 6 00 E)Noneoft hea bove Ans we r :B Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s 3 8 )Cons i de rt hef ol l o wi ngl i ne arpr ogr a mmi ngpr obl e m:

Whi c hoft hef ol l owi ngpoi nt s( X, Y)i snotaf e as i bl ec or ne rpoi nt ? A)( 0, 60 ) B)( 1 0 5, 0) C)( 1 2 0, 0) D)( 10 0 , 1 0) E)Noneoft hea bove Ans we r :C Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s

7 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

3 9 )Cons i de rt hef ol l o wi ngl i ne arpr ogr a mmi ngpr obl e m:

Whi c hoft hef ol l owi ngpoi nt s( X, Y)i snotf e as i bl e ? A)( 50 , 4 0 ) B)( 2 0 , 5 0 ) C)( 6 0 , 3 0) D)( 90 , 1 0 ) E)Noneoft hea bove Ans we r :A Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s 4 0 )T womode l sofapr oduc t— Re gul a r( X)andDe l ux e( Y)— a r epr oduc e dbyac ompa ny .Al i ne a rpr ogr a mmi ng mode li sus e dt ode t e r mi net hepr oduc t i ons c he dul e .Thef or mul a t i oni sa sf ol l ows :

Theopt i ma ls ol ut i oni sX= 1 00 , Y= 0. How ma nyuni t soft her e gul armode lwoul dbepr oduc e dba s e dont hi ss ol ut i on? A)0 B)1 00 C)5 0 D)1 2 0 E)Noneoft hea bove Ans we r :B Di ff: 1 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s

8 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

4 1 )T womode l sofapr oduc t— Re gul a r( X)andDe l ux e( Y)— a r epr oduc e dbyac ompa ny .Al i ne a rpr ogr a mmi ng mode li sus e dt ode t e r mi net hepr oduc t i ons c he dul e .Thef or mul a t i oni sa sf ol l ows :

Theopt i ma ls ol ut i oni sX=1 0 0, Y=0. Whi c hoft he s ec ons t r a i nt si sr e dunda nt ? A)t hefir s tc ons t r ai nt B)t hes e c ondc ons t r a i nt C)t het hi r dc ons t r ai nt D)Al loft hea bove E)Noneoft hea bove Ans we r :B Di ff: 3 Topi c :FOURSPECI ALCASESI N LP AACSB:Ana l yt i cSki l l s 4 2 )Cons i de rt hef ol l o wi ngl i ne arpr ogr a mmi ngpr obl e m:

Wha ti st heopt i mum s ol ut i ont ot hi spr obl e m( X, Y) ? A)( 0, 0) B)( 5 0 , 0 ) C)( 0 , 1 0 0) D)( 40 0 , 0 ) E)Noneoft hea bove Ans we r :B Di ff: 3 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s

9 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

4 3 )Cons i de rt hef ol l o wi ngl i ne arpr ogr a mmi ngpr obl e m:

Thi si sas pe c i a lc as eofal i ne arpr ogr ammi ngpr obl e mi nwhi c h A)t he r ei snof e as i bl es ol ut i on. B)t he r ei sar e dunda ntc ons t r a i nt . C)t he r ea r emul t i pl eopt i ma ls ol ut i ons . D)t hi sc a nnotbes ol ve dgr aphi c a l l y . E)Noneoft hea bove Ans we r :E Di ff: 3 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s 4 4 )Cons i de rt hef ol l o wi ngl i ne arpr ogr a mmi ngpr obl e m:

Thi si sas pe c i a lc as eofal i ne arpr ogr ammi ngpr obl e mi nwhi c h A)t he r ei snof e as i bl es ol ut i on. B)t he r ei sar e dunda ntc ons t r a i nt . C)t he r ea r emul t i pl eopt i ma ls ol ut i ons . D)t hi sc a nnotbes ol ve dgr aphi c a l l y . E)Noneoft hea bove Ans we r :A Di ff: 3 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM AACSB:Ana l yt i cSki l l s

1 0 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

4 5 )Whi c hoft hef ol l owi ngi snotac c e pt a bl ea sac ons t r ai nti nal i ne a rpr ogr a mmi ngpr obl e m( maxi mi z a t i on) ?

A)Cons t r a i nt1 B)Cons t r a i nt2 C)Cons t r a i nt3 D)Cons t r a i nt4 E)Noneoft hea bove Ans we r :A Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 4 6 )I fonec ha nge st hec ont r i but i onr a t e si nt heobj e c t i vef unc t i onofa nLP , A)t hef e as i bl er e gi onwi l lc ha nge . B)t hes l opeoft hei s opr ofitori s oc os tl i newi l lc ha nge . C)t heopt i ma ls ol ut i ont ot heLPi ss ur et onol onge rbeopt i mal . D)Al loft hea bove E)Noneoft hea bove Ans we r :B Di ff: 2 Topi c :SENS I TI VI TYANAL YSI S 4 7 )Se ns i t i vi t ya na l ys i sma yal s obec a l l e d A)pos t opt i ma l i t yana l ys i s . B)pa r a me t r i cpr ogr a mmi ng. C)opt i mal i t ya na l ys i s . D)Al loft hea bove E)Noneoft hea bove Ans we r :D Di ff: 2 Topi c :SENS I TI VI TYANAL YSI S 4 8 )Se ns i t i vi t ya na l ys e sa r eus e dt oe xa mi net hee ffe c t sofc ha nge si n A)c ont r i but i onr a t e sf ore a c hva r i a bl e . B)t e c hnol ogi c alc oe ffic i e nt s . C)a vai l a bl er e s our c e s . D)Al loft hea bove E)Noneoft hea bove Ans we r :D Di ff: 2 Topi c :SENS I TI VI TYANAL YSI S

1 1 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

4 9 )Whi c hoft hef ol l owi ngi sabas i ca s s umpt i onofl i ne arpr ogr a mmi ng? A)Thec ondi t i onofunc e r t a i nt ye xi s t s . B)I nde pe nde nc ee xi s t sf ort hea c t i vi t i e s . C)Pr opor t i ona l i t ye xi s t si nt heobj e c t i vef unc t i ona ndc ons t r a i nt s . D)Di vi s i bi l i t ydoe snote xi s t , a l l owi ngonl yi nt e ge rs ol ut i ons . E)Sol ut i onsorva r i a bl e sma yt a keval ue sf r om -∞ t o+∞. Ans we r :C Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM 5 0 )Thec ondi t i onwhe nt he r ei snos ol ut i ont ha ts a t i s fie sal lt hec ons t r a i nt ss i mul t ane ous l yi sc a l l e d A)bounde dne s s . B)r e dunda nc y . C)opt i mal i t y . D)de pe nde nc y . E)Noneoft hea bove Ans we r :E Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 5 1 )I ft headdi t i onofac ons t r ai ntt oal i ne a rpr ogr a mmi ngpr obl e m doe snotc ha nget hes ol ut i on, t hec ons t r a i nti s s ai dt obe A)unbounde d. B)non-ne ga t i ve . C)i nf e a s i bl e . D)r e dunda nt . E)bounde d. Ans we r :D Di ff: 2 Topi c :FOURSPECI ALCASESI N LP 5 2 )Whi c hoft hef ol l owi ngi snotana s s umpt i onofLP? A)s i mul t a ne i t y B)c e r t a i nt y C)pr opor t i ona l i t y D)di vi s i bi l i t y E)a ddi t i vi t y Ans we r :A Di ff: 2 Topi c :REQUI REMENTSOFALI NEARPROGRAMMI NGPROBLEM

1 2 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

5 3 )Thedi ffe r e nc ebe t we e nt hel e f t -ha nds i dea ndr i ght -ha nds i deofal e s s -t ha n-or -e qua l -t oc ons t r a i nti sr e f e r r e d t oa s A)s ur pl us . B)c ons t r a i nt . C)s l a c k. D)s ha dow pr i c e . E)Noneoft hea bove Ans we r :C Di ff: 2 Topi c :LI NEARPROGRAMMI NGMODELS: GRAPHI CALANDCOMPUTERMETHODS 5 4 )Thedi ffe r e nc ebe t we e nt hel e f t -ha nds i dea ndr i ght -ha nds i deofagr e a t e r -t ha n-or -e qua l -t oc ons t r a i nti s r e f e r r e dt oas A)s ur pl us . B)c ons t r a i nt . C)s l a c k. D)s ha dow pr i c e . E)Noneoft hea bove Ans we r :A Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 5 5 )Ac ons t r a i ntwi t hz e r os l a c kors ur pl usi sc al l e da A)nonbi ndi ngc ons t r a i nt . B)r e s our c ec ons t r a i nt . C)bi ndi ngc ons t r a i nt . D)nonl i ne arc ons t r a i nt . E)l i ne a rc ons t r a i nt . Ans we r :C Di ff: 1 Topi c :SOL VI NGFLAI RFURNI TURE’ SLPPROBLEM USI NGQM FORWI NDOWSANDEXCEL 5 6 )Ac ons t r a i ntwi t hpos i t i ves l a c kors ur pl usi sc a l l e da A)nonbi ndi ngc ons t r a i nt . B)r e s our c ec ons t r a i nt . C)bi ndi ngc ons t r a i nt . D)nonl i ne arc ons t r a i nt . E)l i ne a rc ons t r a i nt . Ans we r :A Di ff: 1 Topi c :SOL VI NGFLAI RFURNI TURE’ SLPPROBLEM USI NGQM FORWI NDOWSANDEXCEL

1 3 Copyr i ght©2 0 12Pe ar s onEduc a t i on, I nc . publ i s hi nga sPr e nt i c eHa l l

5 7 )Thei nc r e a s ei nt heobj e c t i vef unc t i onva l uet ha tr e s ul t sf r om aone -uni ti nc r e a s ei nt her i ght -ha nds i deoft ha t c ons t r a i nti sc a l l e d A)s ur pl us . B)s hadow pr i c e . C)s l a c k. D)dualpr i c e . E)Noneoft hea bove Ans we r :B Di ff: 2 Topi c :SENS I TI VI TYANAL YSI S 5 8 )As t r ai ghtl i ner e pr e s e nt i nga l lnon-ne ga t i vec ombi na t i onsofX1andX2f orapa r t i c ul arpr ofitl e ve li sc a l l e d a ( n) A)c ons t r a i ntl i ne . B)obj e c t i vel i ne . C)s e ns i t i vi t yl i ne . D)pr ofitl i ne . E)i s opr ofitl i ne . Ans we r :E Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 5 9 )I nor de rf oral i ne a rpr ogr a mmi ngpr obl e mt oha veauni ques ol ut i on, t hes ol ut i onmus te xi s t A)a tt hei nt e r s e c t i onoft henon-ne ga t i vi t yc ons t r a i nt s . B)a tt hei nt e r s e c t i onofanon-ne ga t i vi t yc ons t r a i nta ndar e s our c ec ons t r a i nt . C)a tt hei nt e r s e c t i onoft heobj e c t i vef unc t i onandac ons t r a i nt . D)a tt hei nt e r s e c t i onoft woormor ec ons t r a i nt s . E)Noneoft hea bove Ans we r :D Di ff: 2 Topi c :GRAPHI CALSOLUTI ON TO AN LPPROBLEM 6 0 )I nor de rf oral i ne a rpr ogr a mmi ngpr obl e mt oha vemul t i pl es ol ut i ons , t hes ol ut i onmus te xi s t A)a tt hei nt e r s e c t i onoft henon-ne ga t i vi t yc ons t r a i nt s . B)onanon-r e dundantc ons t r a i ntpa r a l l e lt ot heobj e...