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  2. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    The matching pursuit is an example of a greedy algorithm applied on signal approximation. A greedy algorithm finds the optimal solution to Malfatti's problem of finding three disjoint circles within a given triangle that maximize the total area of the circles; it is conjectured that the same greedy algorithm is optimal for any number of circles.

  3. Greedoid - Wikipedia

    en.wikipedia.org/wiki/Greedoid

    This result guarantees the optimality of many well-known algorithms. For example, a minimum spanning tree of a weighted graph may be obtained using Kruskal's algorithm, which is a greedy algorithm for the cycle matroid. Prim's algorithm can be explained by taking the line search greedoid instead.

  4. Category:Greedy algorithms - Wikipedia

    en.wikipedia.org/wiki/Category:Greedy_algorithms

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  5. Greedy number partitioning - Wikipedia

    en.wikipedia.org/wiki/Greedy_number_partitioning

    In computer science, greedy number partitioning is a class of greedy algorithms for multiway number partitioning. The input to the algorithm is a set S of numbers, and a parameter k. The required output is a partition of S into k subsets, such that the sums in the subsets are as nearly equal as possible. Greedy algorithms process the numbers ...

  6. Activity selection problem - Wikipedia

    en.wikipedia.org/wiki/Activity_selection_problem

    Once the greedy choice is made, the problem reduces to finding an optimal solution for the subproblem. If A is an optimal solution to the original problem S containing the greedy choice, then A ′ = A ∖ { 1 } {\displaystyle A^{\prime }=A\setminus \{1\}} is an optimal solution to the activity-selection problem S ′ = { i ∈ S : s i ≥ f 1 ...

  7. Longest-processing-time-first scheduling - Wikipedia

    en.wikipedia.org/wiki/Longest-processing-time...

    Longest-processing-time-first (LPT) is a greedy algorithm for job scheduling. The input to the algorithm is a set of jobs, each of which has a specific processing-time. There is also a number m specifying the number of machines that can process the jobs. The LPT algorithm works as follows:

  8. Nearest neighbour algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_algorithm

    The nearest neighbour algorithm is easy to implement and executes quickly, but it can sometimes miss shorter routes which are easily noticed with human insight, due to its "greedy" nature. As a general guide, if the last few stages of the tour are comparable in length to the first stages, then the tour is reasonable; if they are much greater ...

  9. Optimal binary search tree - Wikipedia

    en.wikipedia.org/wiki/Optimal_binary_search_tree

    A later simplification by Garsia and Wachs, the Garsia–Wachs algorithm, performs the same comparisons in the same order. The algorithm works by using a greedy algorithm to build a tree that has the optimal height for each leaf, but is out of order, and then constructing another binary search tree with the same heights. [7]