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  2. Fisher–Yates shuffle - Wikipedia

    en.wikipedia.org/wiki/Fisher–Yates_shuffle

    [9] [10] The only difference between Durstenfeld's and Sattolo's algorithms is that in the latter, in step 2 above, the random number j is chosen from the range between 1 and i−1 (rather than between 1 and i) inclusive. This simple change modifies the algorithm so that the resulting permutation always consists of a single cycle.

  3. Rider optimization algorithm - Wikipedia

    en.wikipedia.org/wiki/Rider_optimization_algorithm

    The rider optimization algorithm (ROA) [1] [5] [6] is devised based on a novel computing method, namely fictional computing that undergoes series of process to solve the issues of optimizations using imaginary facts and notions.

  4. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1] [2] Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.

  5. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    If a ≡ +3, X alternates ±1↔±3, while if a ≡ −3, X alternates ±1↔∓3 (all modulo 8). It can be shown that this form is equivalent to a generator with modulus m/4 and c ≠ 0. [1] A more serious issue with the use of a power-of-two modulus is that the low bits have a shorter period than the high bits.

  6. Discrete-event simulation - Wikipedia

    en.wikipedia.org/wiki/Discrete-event_simulation

    The use of pseudo-random numbers as opposed to true random numbers is a benefit should a simulation need a rerun with exactly the same behavior. One of the problems with the random number distributions used in discrete-event simulation is that the steady-state distributions of event times may not be known in advance.

  7. Random number - Wikipedia

    en.wikipedia.org/wiki/Random_number

    When a cubical die is rolled, a random number from 1 to 6 is obtained. A random number is generated by a random process such as throwing Dice. Individual numbers can't be predicted, but the likely result of generating a large quantity of numbers can be predicted by specific mathematical series and statistics.

  8. Jim Carrey Clarifies His Retirement Comments: It's 'More ...

    www.aol.com/jim-carrey-clarifies-retirement...

    Jim Carrey isn't swearing off acting for good.. The actor returns to the big screen in the new sequel Sonic the Hedgehog 3 after previously saying in 2022 that he was "being fairly serious" about ...

  9. Sorting algorithm - Wikipedia

    en.wikipedia.org/wiki/Sorting_algorithm

    For example, if any number of elements are out of place by only one position (e.g. 0123546789 and 1032547698), bubble sort's exchange will get them in order on the first pass, the second pass will find all elements in order, so the sort will take only 2n time.