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Closed 12 years ago.
Is there some language that is NP-complete but for which we know some "quick" algorithm? I don't mean like the ones for knapsack where we can do well on average, I mean that even in the worst case the runtime is something like 2^n^epsilon, where the result holds for any epsilon>0 and so we can allow it to get arbitrarily close to 0.
If you do find a "quick" algorithm to this np-complete problem, you just solved that
P=NP, and as you know, that is still an open question.
According to Wikipedia, "There are also decision problems that are NP-hard but not NP-complete, for example the halting problem."
There are no languages that are NP complete where we know a "quick" algorithm; otherwise, it wouldn't be NP-complete.
Related
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Closed 9 years ago.
Has anybody implemented a CUDA parallelization version of Dijkstra's Algorithm for a given sparse matrix (cuSPARSE) graph, and for source, and target node, find the minimal K path?
I really need it to solve a general graph I'll be constructing.
Vincent
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Closed 10 years ago.
A sampling algorithm could output any real number in range [0,1],but the correct answer is in the range [0.1,0.2+x]("x" is in range [0,1]), the algorithm can output a correct answer with probability more than "0.8", then how to give a good answer with high probability? (such as run it many times, and pick the median as the right answer)
I think the question may be asking about the central limit theorem. If the samplings are independent and identically distributed, the OP could apply the classical form: Classical CLT
Otherwise, I recommend viewing the rest of the Wikepedia article to see if any of the other forms are applicable.
It's difficult to tell what is being asked here. This question is ambiguous, vague, incomplete, overly broad, or rhetorical and cannot be reasonably answered in its current form. For help clarifying this question so that it can be reopened, visit the help center.
Closed 10 years ago.
What are some effective ways to understand the concepts of an algorithm? For example, there are many visual explanations for "Towers of Hanoi", and for some "easy-to-understand" algorithms. But for more complicated algorithms, I can't find animations that facilitate my understanding.
This question might seem subjective. Nevertheless, I am sure that many people just like me wonder if there are better ways to understand an algorithm more visually, because for some people, visually expressed things become more understandable.
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Closed 11 years ago.
I'm studying computability theory, and I'm looking for a problem that clearly can be solved, but not in polynomial time.
I tried thinking of all sort's of examples, but it wasn't clear why they can't be solved in polynomial time..
The travelling sales man problem.
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Closed 12 years ago.
Where can I find source code for travelling salasman problem?
nowhere, it's not been solved.
You had mentioned that you were having problems with more than 8 or 9 nodes. This isn't surprising because the complexity increases exponentially with each added node.
As a result many solutions involve Genetic programming to gradually evolve a good answer. Finding the best generally requires a brute-force check of all possibilities.
One example is here, which also provides their source code.