How would you go about testing all possible combinations of additions from a given set N of numbers so they add up to a given final number? A brief example: Set of numbers to add: N = {1,5,22,15,0...
A common algorithm with O (log n) time complexity is Binary Search whose recursive relation is T (n/2) + O (1) i.e. at every subsequent level of the tree you divide problem into half and do constant amount of additional work.
363 views Efficient algorithm to count contiguous subarrays that can form arithmetic progressions I'm working on a problem where I need to count, for each possible common difference D, the number of contiguous subarrays whose elements can be rearranged to form an arithmetic progression with common ... algorithm time-complexity
Which is the best sorting technique to sort the following array and if there are duplicates how to handle them: int a= {1,3,6,7,1,2}; Also which is the best sorting technique of all? void BubbleS...
A* is just like Dijkstra, the only difference is that A* tries to look for a better path by using a heuristic function which gives priority to nodes that are supposed to be better than others while Dijkstra's just explore all possible paths. Its optimality depends on the heuristic function used, so yes it can return a non optimal result because of this and at the same time better the heuristic ...
How do I calculate the distance between two points specified by latitude and longitude? For clarification, I'd like the distance in kilometers; the points use the WGS84 system and I'd like to unde...
What you're looking for are called String Metric algorithms. There a significant number of them, many with similar characteristics. Among the more popular: Levenshtein Distance : The minimum number of single-character edits required to change one word into the other. Strings do not have to be the same length Hamming Distance : The number of characters that are different in two equal length ...
5 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.
As opposed to repeated A* search, the D* Lite algorithm avoids replanning from scratch and incrementally repair path keeping its modifications local around robot pose. if you would like to really understand the algorithm. I suggest you start by reading through the pseudo code for A* and implement it.
76 After a lot of Googling, I've found that most sources say that the Dijkstra algorithm is "more efficient" than the Bellman-Ford algorithm. But under what circumstances is the Bellman-Ford algorithm better than the Dijkstra algorithm? I know "better" is a broad statement, so specifically I mean in terms of speed and also space if that applies.
