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INHERENT LIMITATIONS OF COMPUTER PROGRAMS CSci 4011

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Definition: A language B is NP-complete if: 1. B NP 2. Every A in NP is poly-time reducible to B (i.e. B is NP-hard) HARDEST PROBLEMS IN NP 2. A is NP-complete and A · P B If B is NP-Complete and P NP, then There is no fast algorithm for B. Theorem: A language B is NP-complete if:

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3SAT P DSAT, NAESAT, 2CSP… We will use 3SAT to prove other problems are NP-Complete or NP-Hard. Examples include 3SAT P CLIQUE 3SAT P 0/1-ILP 3SAT P HAMPATH 3SAT P 3COLOR 3SAT P GRADUATION 3SAT P VERTEX-COVER

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2SAT 2SAT = { | is in 2cnf and is satisfiable} Theorem. 2SAT P! Idea: a 2SAT clause (x y) is equivalent to (¬x y) and (¬y x). If there is a chain (x z 1 ) (z 1 z 2 ) … (z k ¬x) and (¬xy 1 ) (y 1 y 2 ) … (y j x) then: x ¬x If not, the formula is consistent, so satisfiable. e.g. (x x) (¬x y) (¬y ¬x)

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def is_satisfiable_2cnf(F): V = Ø, E = Ø, G = (V,E) for l literals(F): V = V {l, ¬l} for (x y) clauses(F): E = E {(¬x,y), (¬y,x)} for x vars(F): if has_path(G,x,¬x) and has_path(G,¬x,x): return False return True (xx)(xx̅)(x̅x) x x x x x x

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REDUCTION STRATEGIES A reduction by restriction shows that the source problem is a special case of the target problem. For example, 3SAT P CNF-SAT because every satisfiable 3CNF is also a satisfiable CNF. Example. Prove 3SAT P 4SAT by restriction. A 3CNF can be converted to an equivalent 4CNF by repeating one literal in each clause.

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COLORING b a e c db ac d b a e c d a bd COLOR = { G,k | G is k-colorable } 3COLOR = { G | G is 3-colorable} Prove that 3COLOR P COLOR

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HAMILTONIAN PATHS b a e c d f h i g HAMPATH = { G,s,t | G has a hamiltonian path from s to t }

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Prove that HAMPATH P HAMCYCLE. Let HAMCYCLE = { G | G has a simple directed cycle of length n} Let HAMILTONIAN = { G | s,t such that G has a hamiltonian path from s to t } Prove that HAMPATH P HAMILTONIAN Let LPATH = { G,s,t,k | G has a simple path from s to t of length at least k } Prove that HAMPATH P LPATH

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VERTEX COVER b a e c d b a e c d VERTEX-COVER = { G,k | G has a vertex cover of size at most k }

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INDEPENDENT SET b a e c d b a e c d INDSET = { G,k | G has an independent set of size at least k } Prove that VERTEX-COVER P INDSET.

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SUBSET SUM SUBSET-SUM = { y 1,…, y n,t | S {1,…,n}. Σ j S y j =t } Which of the following are in SUBSET-SUM? 1,3,5,7, 10 19,11,27,4, 13 19,11,27,4, 61 YES NO YES

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KNAPSACK = { (w 1,v 1 )…,(w n,v n ),W, V | S {1…n} so that Σ i S w i W and Σ i S v i V} 15 lbs $500 ½ lb $15 3 lbs $2000 1lb, $20 50 ×

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Theorem. SUBSET-SUM P KNAPSACK Proof. A subset sum instance is a knapsack where the weights are equal to the values: Let ƒ(y 1,…,y n,t) = y 1,y 1 )…(y n,y n ),t,t Then S. Σ i S y i = t iff S. Σ i S y i t and Σ i S y i t, so y 1 …y n,t SUBSET-SUM iff ƒ(y 1 …y n,t) KNAPSACK

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Theorem. VERTEX-COVER P SET-COVER SET-COVER = { S 1,…,S n,k | i,S i U and i[1…k] so that S i[1] S i[2] … S i[k] = U } Which of the following are in SET-COVER? {1}, {1,2}, {2}, {3}, 2 {1,4}, {1,2}, {1,3}, {4}, 2 Proof. A vertex cover instance is just a set cover instance where every node is a set of edges. YES NO {1}, {2}, {1,2}, 2 YES

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REDUCTION STRATEGIES A reduction from A to B by local replacement shows how to translate between units of A and units of B. Example. vertex cover units are vertices and edges; set cover units are elements and sets. Example. CIRCUIT-SAT units are gates, CNFSAT units are clauses, 3SAT units are 3-literal clauses.

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SATISFYING CONSTRAINTS A 2csp is a list of constraints on pairs of variables Each constraint C(x,y) is a list of values for (x,y). An assignment satisfies a constraint if (x,y) C(x,y). An assignment satisfies a 2csp if it satisfies all constraints. e.g. Scheduling a project; seating at a wedding… 2CSP = { C | C is a satisfiable 2csp } Theorem. 2CSP is NP-Complete.

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Proof. 1. 2CSP NP. Given an assignment to the variables we can check that all constraints are satisfied in linear time. 2. 3SAT P 2CSP. Idea: the main difference is that a 2csp constraint should have only two variables. Add variables to the 2csp that represent pairs of variables in the 3cnf, and constraints to enforce consistency with the 3cnf variables.

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Map 3cnf ϕ with n variables and m clauses to a 2csp C ϕ with 2n+m variables and 3m+n constraints: for each variable x ϕ : add (v x,v ¬x ) {(0,1),(1,0)} for each clause (x y z) ϕ : add v xy {00,01,10,11} add (v xy,v z ) (00,0) add (v xy,v x ) {(00,0), (01,0), (10,1), (11,1)} add (v xy,v y ) {(00,0), (01,1), (10,0), (11,1)} Claim. C ϕ 2CSP ϕ 3SAT: Proof. A satisfying assignment to ϕ can be mapped to a satisfying assignment to C ϕ by assigning each v x = x and each v xy = 2v x +v y because… An assignment to C ϕ maps to an assignment to ϕ by setting each x = v x, because…

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GRADUATION A transcript is a set of course numbers a student has taken A major consists of: Pairs: exactly one of which must be taken Lists: at least one course of which must be taken GRADUATION = { T,M | a subset of T satisfies M} For example: T = {1901A, 1902B, 1902A, 2011, 4041A, 4061, 4211} M = [1901A,1901B], [1902A,1902B] (4011,4041A,4041B), (4211,4707), (4061)

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GRADUATION NP: The subset is a proof that (T,M) GRADUATION. 3SAT P GRADUATION: (x 1 x 2 ¬x 3 ) (¬x 1 x 2 x 2 ) (¬x 2 x 3 x 1 ) T = {101, 102, 201, 202, 301, 302} M = [101, 102], [201, 202], [301, 302] (101,201,302), (101,201,201), (101,202,301)

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GRADUATION NP: The subset is a proof that (T,M) GRADUATION. 3SAT P GRADUATION: Let = C 1 C 2 … C m have variables x 1 …x k For each x i : add classes i01 and i02 to T. add pair (i01,i02) to M. For each C j, we add a triple to M: if x i is a literal in C j, the triple includes i01. if ¬x i is a literal in C j, the triple includes i02.

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UHAMPATH A B CD EF No HAM PATH A B CD EF Undirected HAM PATH UHAMPATH = { G,s,t | G is an undirected graph with a Hamiltonian path from s to t}

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HAMPATH P UHAMPATH A B CD EF A in A mid A out

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HAMPATH P UHAMPATH A B CD EF

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f(G,s,t) = (G,s,t) where: For each node u G: add nodes u in, u out, u mid to G. add edges {u in,u mid } and {u mid,u out } to G For each edge (u,v) G, add {u out,v in } to G s = s in, t = t out. If G,s,t HAMPATH, then G,s,t UHAMPATH: (s,u,v,..,t) (s in,s mid,s out,u in,u mid,u out,v in,v mid,v out,…t out )

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HAMPATH P UHAMPATH If G,s,t UHAMPATH, then G,s,t HAMPATH: Let (s in =v 1,v 2,…,v 3n =t out ) be the undirected path. i=0: Induction: if v 3i = u out, then v 3i+1 =u in, so v 3i+2 =u mid. Claim: for all i0, there exists u G so that: v 3i+1 =u in, v 3i+2 =u mid, v 3i+3 =u out. The directed Hamiltonian path is (u 1, u 2, …, u n ) If v 2 s mid, then no v i =s mid. So v 2 =s mid, v 3 =s out

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3SAT P SUBSET-SUM We transform a 3-cnf formula into y 1 …y n, t : 3SAT y 1 …y n,t SUBSET-SUM The transformation can be done in time polynomial in the length of

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(x 1 x 2 x 2 ) (¬x 1 x 2 x 2 ) (x 1 ¬x 2 x 2 ) Each variable and each clause result in two y is. Each y i will have a digit for each clause and variable. C1C1 C2C2 C3C3 y1y1 1101 y2y2 1010 y3y3 10111 y4y4 10100 y5y5 100 y6y6 100 y7y7 10 y8y8 10 y9y9 1 y 10 1 t11333 x1x1 x2x2 x1x1 x2x2 C1C1 C2C2 C3C3

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3SAT P SUBSET-SUM Let = C 1 C 2 … C m have k variables x 1 …x k. We output y 1 … y 2k + 2m, each a k+m-digit number. for each 1 j k: for each 1 I m: the i th digit of y 2j-1 is 1 if x j C i, else 0 the i th digit of y 2j is 1 if ¬x j C i, else 0. digit j+m of y 2j, y 2j-1 is 1. For each 1 j m: y 2k+2j = y 2k+2j-1 = 10 j-1 Output t = 11..1133..3

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INHERENT LIMITATIONS OF COMPUTER PROGRAMS CSci 4011.

INHERENT LIMITATIONS OF COMPUTER PROGRAMS CSci 4011.

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