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  2. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    For example, for the array of values [−2, 1, −3, 4, −1, 2, 1, −5, 4], the contiguous subarray with the largest sum is [4, −1, 2, 1], with sum 6. Some properties of this problem are: If the array contains all non-negative numbers, then the problem is trivial; a maximum subarray is the entire array.

  3. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    Conversely, given a solution to the SubsetSumZero instance, it must contain the −T (since all integers in S are positive), so to get a sum of zero, it must also contain a subset of S with a sum of +T, which is a solution of the SubsetSumPositive instance. The input integers are positive, and T = sum(S)/2.

  4. Project Euler - Wikipedia

    en.wikipedia.org/wiki/Project_Euler

    If we list all the natural numbers below 10 that are multiples of 3 or 5, we get 3, 5, 6 and 9. The sum of these multiples is 23. Find the sum of all the multiples of 3 or 5 below 1000. It is a 5% rated problem, indicating it is one of the easiest on the site. The initial approach a beginner can come up with is a bruteforce attempt. Given the ...

  5. Combinatorial optimization - Wikipedia

    en.wikipedia.org/wiki/Combinatorial_optimization

    A minimum spanning tree of a weighted planar graph.Finding a minimum spanning tree is a common problem involving combinatorial optimization. Combinatorial optimization is a subfield of mathematical optimization that consists of finding an optimal object from a finite set of objects, [1] where the set of feasible solutions is discrete or can be reduced to a discrete set.

  6. Change-making problem - Wikipedia

    en.wikipedia.org/wiki/Change-making_problem

    Another example is attempting to make 40 US cents without nickels (denomination 25, 10, 1) with similar result — the greedy chooses seven coins (25, 10, and 5 × 1), but the optimal is four (4 × 10). A coin system is called "canonical" if the greedy algorithm always solves its change-making problem optimally.

  7. Combinatorial explosion - Wikipedia

    en.wikipedia.org/wiki/Combinatorial_explosion

    One example in a game where combinatorial complexity leads to a solvability limit is in solving chess (a game with 64 squares and 32 pieces). Chess is not a solved game . In 2005 all chess game endings with six pieces or fewer were solved, showing the result of each position if played perfectly.

  8. Fenwick tree - Wikipedia

    en.wikipedia.org/wiki/Fenwick_tree

    For example, the parent of 6 = 110 2 is 4 = 100 2. Implicit node 0 is the root. Implicit node 0 is the root. Each level k {\displaystyle k} of the tree contains nodes with indices corresponding to sums of k {\displaystyle k} distinct powers of 2 (with k = 0 {\displaystyle k=0} representing an empty sum 0).

  9. de Bruijn sequence - Wikipedia

    en.wikipedia.org/wiki/De_Bruijn_sequence

    For example, a digital door lock with a 4-digit code (each digit having 10 possibilities, from 0 to 9) would have B (10, 4) solutions, with length 10 000. Therefore, only at most 10 000 + 3 = 10 003 (as the solutions are cyclic) presses are needed to open the lock, whereas trying all codes separately would require 4 × 10 000 = 40 000 presses.