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  2. Josephus problem - Wikipedia

    en.wikipedia.org/wiki/Josephus_problem

    In computer science and mathematics, the Josephus problem (or Josephus permutation) is a theoretical problem related to a certain counting-out game. Such games are used to pick out a person from a group, e.g. eeny, meeny, miny, moe. A drawing for the Josephus problem sequence for 500 people and skipping value of 6.

  3. Steinhaus–Johnson–Trotter algorithm - Wikipedia

    en.wikipedia.org/wiki/Steinhaus–Johnson...

    The Hamiltonian cycle in the Cayley graph of the symmetric group generated by the Steinhaus–Johnson–Trotter algorithm Wheel diagram of all permutations of length = generated by the Steinhaus-Johnson-Trotter algorithm, where each permutation is color-coded (1=blue, 2=green, 3=yellow, 4=red).

  4. Heap's algorithm - Wikipedia

    en.wikipedia.org/wiki/Heap's_algorithm

    In a 1977 review of permutation-generating algorithms, Robert Sedgewick concluded that it was at that time the most effective algorithm for generating permutations by computer. [ 2 ] The sequence of permutations of n objects generated by Heap's algorithm is the beginning of the sequence of permutations of n +1 objects.

  5. Permutation - Wikipedia

    en.wikipedia.org/wiki/Permutation

    Following this algorithm, the next lexicographic permutation will be [1, 3, 2, 4], and the 24th permutation will be [4, 3, 2, 1] at which point a[k] < a[k + 1] does not exist, indicating that this is the last permutation.

  6. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    The algorithm takes a list of all the elements of the sequence, and continually determines the next element in the shuffled sequence by randomly drawing an element from the list until no elements remain. [1] The algorithm produces an unbiased permutation: every permutation is equally likely.

  7. Clique problem - Wikipedia

    en.wikipedia.org/wiki/Clique_problem

    In some cases, these algorithms can be extended to other, non-perfect, classes of graphs as well. For instance, in a circle graph, the neighborhood of each vertex is a permutation graph, so a maximum clique in a circle graph can be found by applying the permutation graph algorithm to each neighborhood. [48]

  8. Sudoku solving algorithms - Wikipedia

    en.wikipedia.org/wiki/Sudoku_solving_algorithms

    The solution R is a total relation and hence a function. Sudoku rules require that the restriction of R to X is a bijection, so any partial solution C, restricted to an X, is a partial permutation of N. Let T = { X : X is a row, column, or block of Q}, so T has 27 elements. An arrangement is either a partial permutation or a permutation on N.

  9. Lehmer code - Wikipedia

    en.wikipedia.org/wiki/Lehmer_code

    The usual way to prove that there are n! different permutations of n objects is to observe that the first object can be chosen in n different ways, the next object in n − 1 different ways (because choosing the same number as the first is forbidden), the next in n − 2 different ways (because there are now 2 forbidden values), and so forth.