 | David Pritchard - Computers - 1998 - 1192 pages
...chromosomes involved in the generation of a new population are selected according to their fitness values. Fitter chromosomes have higher probabilities of being selected. After several generations, the algorithm converges to the best chromosome which hopefully represents the optimal or suboptimal solution... | |
 | James A. Momoh - Technology & Engineering - 2000 - 498 pages
...formed by 1 . selecting, according to the fitness values, some of the parents and offspring, and 2. rejecting others so as to keep the population size...algorithms converge to the best chromosome, which, it is hoped, represent the optimum or suboptimal solution to the problem. Now, let P(t) and C(t) be... | |
 | Hoang Pham - Business & Economics - 2006 - 1135 pages
...operator or modifying a chromosome using a mutation operator. A new generation is formed by selecting, according to the fitness values, some of the parents...algorithms converge to the best chromosome, which we hope represents the optimum or suboptimal solution to the problem Population Crossover Start: Encoding... | |
 | Sergio Zani, Andrea Cerioli, Marco Riani, Maurizio Vichi - Language Arts & Disciplines - 2007 - 426 pages
...therefore, rejecting the others. Chromosomes whose fitness value is greater have higher probability of being selected. After several generations the algorithms...the best chromosome which, hopefully, represents the optimal solution to the problem. The computational advantage that is obtained by using a GA is due... | |
| |
... rejecting others so as to keep the population size constant. Fitter chromosomes have higher probabilities of being selected. After several generations, the algorithms converge to the best chromosome, which hopefully represents the optimum or suboptimal... 