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has row numbers in the population matrix given by ma = 1, 3, 5, . . . and the father has the row numbers pa = 2, 4, 6, . . . This approach doesn t model nature well but is very simple to program. It s a good one for beginners to try. 2. Random pairing. This approach uses a uniform random number generator to select chromosomes. The row numbers of the parents are found using ma=ceil(Nkeep*rand(1, Nkeep)) pa=ceil(Nkeep*rand(1, Nkeep)) where ceil rounds the value to the next highest integer. 3. Weighted random pairing. The probabilities assigned to the chromosomes in the mating pool are inversely proportional to their cost. A chromosome with the lowest cost has the greatest probability of mating, while the chromosome with the highest cost has the lowest probability of mating. A random number determines which chromosome is selected. This type of weighting is often referred to as roulette wheel weighting. There are two techniques: rank weighting and cost weighting. a. Rank weighting. This approach is problem independent and nds the probability from the rank, n, of the chromosome: Pn = N keep - n + 1 = 4 - n+1 5-n = 1+ 2 + 3+ 4 10 (2.11) abonamente cablu si internet upc Se internet, se tévé nincs több településen Fejérben | 24.hu
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