演算法›Ch5 NP Complete Problems
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28. NP-Complete、Polynomial Reduction
#AL-05-028易NP-CompletePolynomial Reduction
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We have the following definitions and theorem related to NP-completeness.

Definition 1. Let X1X_1 and X2X_2 be two problems. X1X_1 polynomially reduces to X2X_2 (written as X1∝X2X_1 \propto X_2) if and only if X1X_1 can be solved in polynomial time, by using a polynomial time algorithm which solves X2X_2.

Definition 2. A problem is said to be a P (resp., NP) problem if it can be solved in polynomial time by a deterministic (resp., non-deterministic) algorithm.

Definition 3. NP (resp., P) is the set of all NP (resp., P) problems.

Definition 4. A problem X is an NP-complete (NPC) problem if X∈NPX \in NP and every NP problem reduces to X.

Cook's Theorem. NP=PNP=P if and only if the satisfiability (SAT) problem is a P problem. (This implies that every NP problem polynomially reduces to SAT.)

(5%) By the above definitions and theorem, show the following statement is true or false. You should also show your reasons. If the reasons are incorrect, then you get no point.

Statement: If an NPC problem can be solved in polynomial time by a deterministic algorithm, then all NP problems can also be solved in polynomial time by a deterministic algorithm.

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