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  3. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    This can be done efficiently in linear time and in-place. The lesser and greater sublists are then recursively sorted. This yields an average time complexity of O(n log n), with low overhead, and thus this is a popular algorithm. Efficient implementations of quicksort (with in-place partitioning) are typically unstable sorts and somewhat ...

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  5. Online algorithm - Wikipedia

    en.wikipedia.org/wiki/Online_algorithm

    Note that the final result of an insertion sort is optimum, i.e., a correctly sorted list. For many problems, online algorithms cannot match the performance of offline algorithms. If the ratio between the performance of an online algorithm and an optimal offline algorithm is bounded, the online algorithm is called competitive. [1]

  6. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...

  7. Bucket sort - Wikipedia

    en.wikipedia.org/wiki/Bucket_sort

    If division and multiplication can be done in constant time, then scattering each element to its bucket also costs (). Assume insertion sort is used to sort each bucket, then the third step costs O ( ∑ i = 1 k n i 2 ) {\displaystyle O(\textstyle \sum _{i=1}^{k}\displaystyle n_{i}^{2})} , where n i {\displaystyle n_{i}} is the length of the ...

  8. Divide-and-conquer algorithm - Wikipedia

    en.wikipedia.org/wiki/Divide-and-conquer_algorithm

    The divide-and-conquer technique is the basis of efficient algorithms for many problems, such as sorting (e.g., quicksort, merge sort), multiplying large numbers (e.g., the Karatsuba algorithm), finding the closest pair of points, syntactic analysis (e.g., top-down parsers), and computing the discrete Fourier transform . [1]

  9. Selection sort - Wikipedia

    en.wikipedia.org/wiki/Selection_sort

    It has a O(n 2) time complexity, which makes it inefficient on large lists, and generally performs worse than the similar insertion sort. Selection sort is noted for its simplicity and has performance advantages over more complicated algorithms in certain situations, particularly where auxiliary memory is limited.

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