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  2. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    If the array contains all non-negative numbers, then the problem is trivial; a maximum subarray is the entire array. If the array contains all non-positive numbers, then a solution is any subarray of size 1 containing the maximal value of the array (or the empty subarray, if it is permitted).

  3. Double-ended queue - Wikipedia

    en.wikipedia.org/wiki/Double-ended_queue

    In computer science, a double-ended queue (abbreviated to deque, / d ɛ k / DEK [1]) is an abstract data type that generalizes a queue, for which elements can be added to or removed from either the front (head) or back (tail). [2]

  4. Complete graph - Wikipedia

    en.wikipedia.org/wiki/Complete_graph

    Geometrically K 3 forms the edge set of a triangle, K 4 a tetrahedron, etc. The Császár polyhedron, a nonconvex polyhedron with the topology of a torus, has the complete graph K 7 as its skeleton. [15] Every neighborly polytope in four or more dimensions also has a complete skeleton. K 1 through K 4 are all planar graphs.

  5. Proxmap sort - Wikipedia

    en.wikipedia.org/wiki/Proxmap_sort

    Each insertion sort is (), c the size of the subarrays; there are p subarrays thus p * c = n, so the insertion phase take O(n); thus, ProxmapSort is (). Average case: Each subarray is at most size c, a constant; insertion sort for each subarray is then O(c^2) at worst – a constant. (The actual time can be much better, since c items are not ...

  6. Clique problem - Wikipedia

    en.wikipedia.org/wiki/Clique_problem

    The graph shown has one maximum clique, the triangle {1,2,5}, and four more maximal cliques, the pairs {2,3}, {3,4}, {4,5}, and {4,6}. An undirected graph is formed by a finite set of vertices and a set of unordered pairs of vertices, which are called edges.

  7. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    The variant in which all inputs are positive, and the target sum is exactly half the sum of all inputs, i.e., = (+ +). This special case of SSP is known as the partition problem . SSP can also be regarded as an optimization problem : find a subset whose sum is at most T , and subject to that, as close as possible to T .

  8. Counting sort - Wikipedia

    en.wikipedia.org/wiki/Counting_sort

    For data in which the maximum key size is significantly smaller than the number of data items, counting sort may be parallelized by splitting the input into subarrays of approximately equal size, processing each subarray in parallel to generate a separate count array for each subarray, and then merging the count arrays.

  9. Multiple subset sum - Wikipedia

    en.wikipedia.org/wiki/Multiple_subset_sum

    Max-sum MSSP: for each subset j in 1,...,m, there is a capacity C j. The goal is to make the sum of all subsets as large as possible, such that the sum in each subset j is at most C j. [1] Max-min MSSP (also called bottleneck MSSP or BMSSP): again each subset has a capacity, but now the goal is to make the smallest subset sum as large as ...