2011年1月8日 · Here is a Java version which is well suited for small N and very large target sum, when complexity O(t*N) (the dynamic solution) is greater than the exponential algorithm. My version uses a meet in the middle attack, along with a little bit shifting in order to reduce the complexity from the classic naive O(n*2^n) to O(2^(n/2)) .

2016年1月21日 · The same applies to the 14-bit integer PIN, so guessing the PIN would require you to solve a 2^14 possible outcome puzzle, hence an algorithm of time complexity O(2^n). So, those types of problems, where combinations of elements in a set S differs, and you will have to try to solve the problem by trying all possible combinations, will have this ...

Same core algorithm but we keep track of the top-k elements and keep m equal to the most distant element in the k-elements. Same trick applies. If the distance in any single direction is more than the distance we'd have to beat to make the current list of best elements, we can know that that point cannot make the list of top-k elements, and ...

2019年3月22日 · The fantastic answer at: What would cause an algorithm to have O(log log n) complexity? gives an intuitive explanation of where the O(log log n) comes from: while log n comes from an algorithm that removes half of the options at each step, and log log n comes from an algorithm that reduces the options to the square root of the total at each step!

Stuff you know: A common way to classify algorithms is by runtime, and by citing the big-Oh complexity of an algorithm, you can get a pretty good estimation of which one is "better" -- whichever has the "smallest" function in the O! Even in the real world, O(N) is "better" than O(N²), barring silly things like super-massive constants and the like.

2021年1月4日 · The time complexity of the binary search algorithm belongs to the O(log n) class. This is called big O notation. The way you should interpret this is that the asymptotic growth of the time the function takes to execute given an input set of size n will not exceed log n.

The algorithm is obtained by unrolling and combining two successive iterations of the classic cross product algorithm. I'm not so sure how the two algorithms compare regarding numerical precision. My impression is that the above algorithm is better than the classic one because the multiplication tend to restore the loss of precision of the ...

2011年8月3日 · Unless P = NP, there is no polynomial-time algorithm for generating general Sudoku problems with exactly one solution. In his master's thesis, Takayuki Yato defined The Another Solution Problem (ASP), where the goal is, given a problem and some solution, to find a different solution to that problem or to show that none exists.

CastorTiu has a really nice demo solution on CodeProject, A* algorithm implementation in C#, that animates the search algorithm and allows the user to tweak a few settings. [...] EpPathFinding.cs- A Fast Path Finding Algorithm (Jump Point Search) in C# (grid-based). It has a nice, clear GUI and allows a few settings to be tweaked.

2009年2月8日 · Now, imagine the graph has cycles, and your searching algorithm will finish and report success in the first of them. The graph is undirected, and therefore, the when the algorithm inspects an edge, there are only two possibilities: Either it has visited the other end of the edge, or it has and then, this edge closes a circle.