Time complexity for n-queens is O(n!).
time complexity is 2^57..and space complexity is 2^(n+1).
Dijkstra's original algorithm (published in 1959) has a time-complexity of O(N*N), where N is the number of nodes.
If the range of numbers is 1....n and the size of numbers is k(small no.) then the time complexity will be theta n log..
The best and worst case time complexity for heapsort is O(n log n).
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To efficiently solve a problem with a time complexity of n log n, you can use algorithms like merge sort or quicksort. These algorithms have a time complexity of n log n, which means they can sort a list of n elements in a time proportional to n multiplied by the logarithm of n. This allows for faster and more efficient problem-solving compared to algorithms with higher time complexities.
The time complexity of the backtrack algorithm is typically exponential, O(2n), where n is the size of the problem.
The time complexity of the backtracking algorithm is typically exponential, O(2n), where n is the size of the problem.
The time complexity of the knapsack greedy algorithm for solving a problem with a large number of items is O(n log n), where n is the number of items.
The time complexity of an algorithm with a factorial time complexity of O(n!) is O(n!).
By solving a problem in n log n time complexity, the efficiency of an algorithm can be improved because it means the algorithm's running time increases at a slower rate as the input size grows. This allows the algorithm to handle larger inputs more efficiently compared to algorithms with higher time complexities.
When comparing the time complexity of an algorithm with log(n) versus n, log(n) grows slower than n. This means that an algorithm with log(n) time complexity will generally be more efficient and faster than an algorithm with n time complexity as the input size increases.
The time complexity of the algorithm is O(log n).
The time complexity of the algorithm is O(n log n).
The time complexity of sorting an array using a comparison-based sorting algorithm with a complexity of n log n is O(n log n).
The time complexity of the union find operation is typically O(log n) or O((n)), where n is the number of elements in the data structure.
time complexity is 2^57..and space complexity is 2^(n+1).