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Figure 1 shows the difference between the genetic algorithm and interactive genetic algorithm.
Open image in new window Fig. 1 The difference between the genetic algorithm and interactive genetic algorithm.
(1995) elaborated a study about the nature of connections between the genetic algorithm and tabu search metaheuristics, searching to show the existing opportunities for creating a hybrid approach with these two standard methods to take advantage of their complementary features and to solve difficult optimization problems.
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The varying model would be varied using the genetic algorithm between a 0% accuracy and a 100% accuracy.
The major difference between the ant algorithm and the genetic algorithm is their solution space.
An interaction is created between human and computer, which has partly solved problems with the genetic algorithm in the respect.
Inspired by analysis regarding the relationship between subset size and accuracy, a squeezing algorithm is presented to shrink the genetic algorithm's chromosome cardinality during the genetic iterations.
Initialize the parameters of the genetic algorithm.
Eerr is minimized by the genetic algorithm.
Fig. 1 Flowchart of the genetic algorithm.
In what follows, first, in "Genetic algorithm and interactive genetic algorithm" section, the genetic algorithm and the interactive genetic algorithm are briefly discussed.
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