ORF307 Optimization Practice Midterm 1
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1 Princeton University Department of Operations Research and inaocial Engineering OR307 Optimization Practice Midterm 1 Closed book. No computers. Calculators allowed (but not needed). You are permined to use a one-page two-sided cheat sheet. Please return the exam questions and your cheat sheet with your exam booklet. (1) (30 pts.) Consider the following problem: maxirnize 2XI X2 6X3 + X4 subject to X l < 4 - X2 + X. :s; 5 -Xl X3 + X. < -1 Xl, X2, X3, X4 2: o. (a) Write the problem in dictionary form. (b) Write down the values of all variables associated with this dictionary. (c) Write down the dual problem as a rninimization problem. (d) Write the dual problem in dictionary form. (e) Write down the values of all variables associated with this dual dictionary. (f) Check whether the primal values from (b) are complementary to the dual values from (e).
2 :1., (C\) ~ = 2. ;>(1._')(. -6't l +)(q WI - 1- 'X I W2. = s;- -I- '><l. - "X.., W 1 = 'X, +~ - x'i (b) ')(, -= "'S. = ')('3 ::: 'X If :::. 0 \}./, = Lj,,' ""'1. - ~ W, -= -I eel t./~, +S-'JL-~J ~I - \~h ~ 2. -\h ~ -\ - ~.J ~ -6 'h. -+ ';)1 ~ Cd) -~ - -4';), - S-'h. -I- ~3 - ~ ;;; I -2..., ';) I - ':13 2 ::: 2- -~~ l3 :: {, -'h 2- '/ ::: -I +~-z. -I- ~:I (e) 'J I ::: ';} 1. ::: ~J :=: 0 } 'l -= -2. I I 2"t -= \ I cl::: 6, c'1 -:; -I (~) ')(, ~I := o (-z.) "'0)?<l.c'l. '" 0 ( I) =0 ) '')(.'3 ~ =- 0-6 =() I )( I' c~ -= () (-I) =' 0 w,,:}, =- 4 ' () -=-0 ) lvl.~l.::: ~ 0 ;0 I tv J 'c), c=. -/- V ~ o,{f;s'
3 2 (2) (14 pts.j Consider!he following four dictionaries: ( = - 2-2Xl 2 + 3w, (b) X, = 4 + 6X2 + W XI X4 = 3-4Wl (c) X3 w, X, (= - 9-3X2 ( 6+ 2X4 + X, + 2W W2 - W3 X2 (d) - - X X4 + W, + 3X, 7W3-1 + W2 + 5W3 + X2 X2-2 X4 + 5WI + Xl + W3-3 - W2-3W3 - X2 W2 - X4-3WI - 2XI + W3 or each of the above dictionaries, identify which of the following statements are true by placing check marks in the following table: The associated primal solution is feasible The associated primal solution is optimal The dictionary is primal degenerate The dictionary shows the primal problem is unbounded Variable X3 is basic The associated dual solution is dual feasible The dictionary shows the primal problem is infeasible (a) (b) (c) (d) X X X X 'j.. )<. 'j. X )< X y.. Be sure to return this page with your exam booklet.
4 3 (3) (18 pts.) Mark the following statements as true (T) or false (): T/ If the current dictionary is degenerate, then the next pivot will not change the objective function. Consider the version of the simplex method in which an artificial variable Xo is introduced in pbase-i. The phase-i problem can be unbounded. After a degenerate pivot, the dictionary must still be degenerate. An optimal solution to a linear programming problem must be a vertex of the set of feasible solutions. No problem with an unbounded feasible region has an optimal solution. Consider a dictionary. The primal and dual solutions associated with this dictionary must satisfy the complementarity relations: x j Zj = 0 for all j and WiYi = 0 for all z- It is possible to move from one vertex of the feasible set to any other vertex in a single pivot. A dual pivot never decreases the value of the primal objective function. A problem has an optimal solution if and only if it is both primal and dual feasible..,- T T NOTE: SAT-style grading scheme: 2 points for a correct answer, 0 points for an incorrect answer, and 1 point for no answer.
5 4 (4) ( 7 pts.) The CEO of a large colporation needs the solution to the following linear programming problem: maximize - 2Xl - 2X2 6X3 subject to Xl 2X2 2X3 < -15-2XI + X2 X3 < - 30 X}, X2, X3 > O. Because the numbers represent millions of dollars, an error would be very costly. Hence, he's independently delegated the task of computing the solution to two subordinates: Alice and Brad. Alice carne back with the following values for the priulal and, by the way, for the associated dual values: xi = 25, x; = 20, x; = 0 and y; = 2, y; = 2 Brad provided the following values, which are different from Alice's: xi = 9, x; = 0, xi = 12 Since the two solutions disagree, you're being asked to determine who, if anyone, is correct. So, who is? Explain. (5) (7 pts.) Given n girls and m boys, you, the matchmaker, are to determine how to pairwise match the girls with the boys so as to maxinlize some overall desirability index. This problem can be set up as follows. Let Xgb be a decision variable that is 1 if girl g gets matched to boy b and is zero otherwise. Suppose that there is a desirability index d gb associated with matching girl g with boy b. The problem is to maxinlize the overall desirability of all of the matches subject to the constraints that each girl gets matched with one boy and each boy gets matched with at most one girl. ormulate this problem as a linear programming problem. Notes: (I) don 't worry about specific data, just describe the problem; (2) you can write it either in AMPL or just in common mathematical notation; (3) don't worry that the solution might involve fractions.
6 'X~ -2)( - _Zy.l = v; :: -6s- ~ -/& I '!. :I - 2'f.~ -+ '(.1* - "'t '" -~() ':: -3D ~ - S 0.././ ':)~-z"a~ ':: 2-Lf ::: -2 ~ -z./ -7..~( -t 'j~ = -'-/+2. -= -2 ~ -2./ -2':)~_ ':1': = -L/_2 ~-6 >, -6,/ ~ ti5;\a~ /:)trfjc-c-h.. _ O~. vk: -2)(~ - '2-)(; - 6"'J.* =- -I~ = -'To?~ ~Ii<>: ~ -zi; -2~~ = 9-2.</ == -I> ~ -J),./ = -I~ -1<.:= -30 :!: -30 /'
7 ~ ')('~b :: ~ ~'" ~ ~.:Q ::3 Z 'X~ b ~ -'\ ~tf) ~ ~ b ~ 'X:>b ~O -P<I1 ~ f'~ (~,b)
8 5 (6) ( 8 pts.) The solution associated with the following dictionary is optimal: (=5 2W2 X l = 6 + 5Wl + w2 X2 = 0 - WI - 7W2 ea) Write down the optimal values for all of the variables in tbis problem. (b) If there are other optimal solutions, find one. If there are none, say how you know this to be the case. (7) ( 6 pts.) Consider the following linear programming problem in 2 variables: maximize 3Xl + 2X2 subject to -Xl + 3 X 2 < 12 Xl + X2 < 8 2XI - X2 < 10 X I l X2 > O. Here is a graph of the feasible region shown together with two level sets of the objective function: Using the primal simplex method, one can pivot from the vertex labeled A to the vertex labeled B. Consider this pivot. ea) What is the entering variable? -,c.,. (b) What is the leaving variable? W Explain.!!. -r1.a.. M~~ v~um, «4- -1"ila. ""'~v~~~ is ~ A ~ '
9 G, C"'\ "\(, = b I ')<2. = 0 (~9. W,::oO W = 0) ) 1- ' (b).~~.:-o ~~.R..., c.. M~ v~m wjl. 0- ~ c.~1~ ~ Ow". )~ ~ f~ WI ~ ~ ~~' 1I1l.iM) f~"i~ w-e c.a,..., Jo ~ Md"YI-~..:& pwvt J~~J ~ ~,J) /.)~. --ld0~, ol,j,~ rjl ~~ flo c0~~ <t.ad f:h. J1~~ \}CtM~ \0 'X2. ;\R-O~j ~ 0.. ~~~ p~... ~ -= ::> +0 Xl.. - 2w1. y.., =c b - S-lC t ~11Wl. W := C> - Xl. - fjwz. I ') '{.... = 6 )( =-0 ~ I 2..,, A~r~ f C~ ~ ~~? \AJJQ J LM2..d ~ Al""-t. ~"-I wt ~.P.Q# '/.l. ~ ~ w, J&<L\K. I\SJ-~ b~~ ~ W ~ Jw. we ~d~. ~) ~ ~!~6W() or ~u-9,<)~,
10 6 (8) ( 5 pts.) Consider a problem whose constraints are as shown here: c Suppose that the objective is to minimize Xl. Clearly, the optimal solution is at vertex E. It is not possible for the dual simplex method starting at vertex H to visit n vertices G then E? Explain why. -ra ~0.2 pf",,~ ~J2 ~ ~Q ~ 0.. M-"""'dR>~ :.:. ~J' ~~""~. As /)otn-cm ~...(J.f-lVJ~ ~ (9) ( 5 pts.) Using the largest coefficient rule to choose the entering variable in the ~.e following primal feasible dictionary, compute the dictionary after one iteration of ) the simplex method..j,. ~ IW. - X3 ~~. W, = I -+ ',(, -+ 2W"t - 2 ')(3 - W1. - "LX J ~ ~ J ~ ca.ll~ c;.. #cvl ~C/W'!ll C ;,., i~i JJa) ~~ ~ ~/ -t;;.,.~,
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