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Is the MAX-SAT problem NP-hard? From the Wikipedia page:
The MAX-SAT problem is NP-hard, since its solution easily leads to the solution of the boolean satisfiability problem, which is NP-complete
I see that a given SAT problem can be reduced to a MAX-SAT problem: just solve the MAX-SAT problem for the boolean formula to see if all clauses can be satisfied. If yes, the SAT problem has the answer "yes", otherwise "no".
Question 1: What confuses me is that we have an optimization problem here, and no decision problem. So, can also optimization problems be considered as NP-hard? It only needs to be shown that the (optimization) problem can be reduced in polynomial-time to the SAT problem (or another NP-hard problem)?
Question 2: To reduce the SAT problem to MAX-SAT, we have to find a function $f$, which is computable in polynomial time, and with $p \text{ in } \text{SAT} \Leftrightarrow f(p) \text{ in } \text{MAX-SAT}$.
This is the definition I know about reduction. But here, we clearly can not find such a function $f$ since MAX-SAT is not a decision problem. How can a reduction be shown here?
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As Yuval says, the $NP$-hardness of such problems is really a statement about the related decision variant. This relationship between an optimization problem and its decision variant is formalised as $NPO$ ($NP$ optimization). For the problems in $NPO$ the relationship is appropriately bounded (much as you'd expect, with polynomial bounds, PTIME verification etc.) As usual wikipedia is pretty good starting place (http://en.wikipedia.org/wiki/Optimization_problem#NP_optimization_problem)
– Luke Mathieson – 2012-07-31T01:13:09.7031
Regarding the relationship of NP and NPO, see also here and here.
– Raphael – 2012-07-31T07:13:13.177