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Stochastic universal sampling

Stochastic universal sampling (SUS) is a selection technique used in evolutionary algorithms for selecting potentially useful solutions for recombination. It was introduced by James Baker.

Pseudo Code
Described as an algorithm, pseudocode for SUS looks like: SUS(Population, N) F := total fitness of Population N := number of offspring to keep P := distance between the pointers (F/N) Start := random number between 0 and P Pointers := [Start + i*P | i in [0..(N-1) return RWS(Population,Pointers) RWS(Population, Points) Keep = [] for P in Points I := 0 while fitness sum of Population[0..I] Population[0..I] is the set of individuals with array-index 0 to (and including) . Here RWS() describes the bulk of fitness proportionate selection (also known as "roulette wheel selection") – in true fitness proportional selection the parameter is always a (sorted) list of random numbers from 0 to . The algorithm above is intended to be illustrative rather than canonical. ==See also==
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