Examples of NP-complete problem
In computational complexity theory, a problem is NP-complete when: It is a decision problem, meaning that for any input to the problem, the output is either "yes" or "no".
When the answer is "yes", this can be demonstrated through the existence of a short (polynomial length) solution..
Examples of NP-complete problem
In simple terms, a problem is NP Complete if a non-deterministic algorithm that be designed for the problem to solve it in polynomial time O(N^K) and it is the closest thing in NP to P.
All problems cannot be solved in polynomial time complexity (like O(N^2))..
Examples of NP-complete problem
It is easy to see that the complexity class P (all problems solvable, deterministically, in polynomial time) is contained in NP (problems where solutions can be verified in polynomial time), because if a problem is solvable in polynomial time, then a solution is also verifiable in polynomial time by simply solving the .
Examples of NP-complete problem
The “P versus NP problem” asks whether these two classes are actually identical; that is, whether every NP problem is also a P problem.
If P equals NP, every NP problem would contain a hidden shortcut, allowing computers to quickly find perfect solutions to them..
Has P vs NP been solved?
The thing is, we haven't been able to find an NP-complete problem that's also in P, which would mean that all NP problems could be solved quickly and easily.
Computer scientists have been trying to solve this problem for decades, but we still don't have a definite answer..
What does NP mean in complexity theory?
In computational complexity theory, NP (nondeterministic polynomial time) is a complexity class used to classify decision problems..
What is computational complexity P and NP?
It is easy to see that the complexity class P (all problems solvable, deterministically, in polynomial time) is contained in NP (problems where solutions can be verified in polynomial time), because if a problem is solvable in polynomial time, then a solution is also verifiable in polynomial time by simply solving the .
What is P vs NP complexity theory?
Roughly speaking, P is a set of relatively easy problems, and NP is a set that includes what seem to be very, very hard problems, so P = NP would imply that the apparently hard problems actually have relatively easy solutions.
But the details are more complicated.Oct 29, 2009.
What is P vs NP in complexity of algorithms?
The P vs NP problem is to determine whether every problem whose solution can be quickly verified (NP) can also be solved quickly (P).
The P vs NP problem refers to the task of finding a universal algorithm that can solve and verify all problems instantly..
What is P vs NP in information theory?
In this theory, the class P consists of all those decision problems (defined below) that can be solved on a deterministic sequential machine in an amount of time that is polynomial in the size of the input; the class NP consists of all those decision problems whose positive solutions can be verified in polynomial time .
What is the descriptive complexity of P vs NP?
In this theory, the class P consists of all those decision problems (defined below) that can be solved on a deterministic sequential machine in an amount of time that is polynomial in the size of the input; the class NP consists of all those decision problems whose positive solutions can be verified in polynomial time .
What is the difference between NP and P?
P = the set of problems that are solvable in polynomial time by a Deterministic Turing Machine.
NP = the set of decision problems (answer is either yes or no) that are solvable in nondeterministic polynomial time i.e can be solved in polynomial time by a Nondeterministic Turing Machine[4]..
What is the difference between P and NP complexity?
Roughly speaking, P is a set of relatively easy problems, and NP is a set that includes what seem to be very, very hard problems, so P = NP would imply that the apparently hard problems actually have relatively easy solutions.
But the details are more complicated.Oct 29, 2009.
What is the time complexity P vs NP?
In this theory, the class P consists of all those decision problems (defined below) that can be solved on a deterministic sequential machine in an amount of time that is polynomial in the size of the input; the class NP consists of all those decision problems whose positive solutions can be verified in polynomial time .
What relationship is known about the complexity classes P and NP?
Most of scientists belive that Pu226.
- NP so there are NP problems that we can't solve in polynomial time
Why is every problem in P also in NP?
There are non-deterministic algorithms are available which takes non-deterministic polynomial time to solve these problems.
Here,we know that P-type problems are subset of NP-type problems.
All P problems are also NP problems because if a computer can easily solve it, the computer can also easily check it..
Why is the P vs NP problem important?
If P equals NP, every NP problem would contain a hidden shortcut, allowing computers to quickly find perfect solutions to them.
But if P does not equal NP, then no such shortcuts exist, and computers' problem-solving powers will remain fundamentally and permanently limited..
