But in this study, Eq.1 contained four unknown constants (A, B, K and D) were solved by Genetic Algorithm
(GA) method under no assumption.
On the one hand introduces the partial optimized algorithm to be possible to discover each individual the partial optimal solution which corresponds under the present environment, in the order to achieve the improvement community overall performance the goal; On the other hand may carry on the next generation take performance superior new community as the foundation the heredity evolution to operate the smooth this kind the strategy which unifies with the partial optimized method while may fundamentally enhance the genetic algorithm
the estimated performance, this also is one of present genetic algorithm
research main questions.
The execution time of genetic algorithm
is less than the execution of Masek algorithm.
Three localization algorithms for solving the optimization problem are compared: simplex, AMA and genetic algorithms
. This study shows that the choice of an algorithm depends on the desired accuracy and computation time.
Edge detection in medical images using a genetic algorithm
. IEEE Trans Med Imaging 1998 Jun; 17(3):469-474.
Making use of the modified genetic algorithm
and the proposed algorithm, in the four functions and with the initial data of Figure 2, the graphs of Figure 4 were obtained as response.
As described by  and , large types of route problems can be solved employing Genetic Algorithm
. In the classic version of the traveling salesman, there is a list of cities to visit and each city is a mandatory stopping point and the objective function is to minimize the traveling cost between such points.
To improve the population diversity in a genetic algorithm
used to solve equations systems, in paper , pairs of symmetric and harmonious individuals are introduced.
2002." The Use of the Simple Genetic Algorithm
in Finding the Critical Factor of Safety in Slope Stability Analysis." Computers and Geotechnics 29 (8): 699-714.
Studies aiming at simulation and optimization with the oat crop through AI via artificial neural networks and genetic algorithms
are inexistent in the Brazilian research, although they can contribute to important processes related to the management of the species.
In this paper the main contribution is the fuzzy parameter adaptation in the genetic algorithm
for optimizing fuzzy systems in the control area, but the general method can be applied in any area of application.
The optimal thermal efficiency of the system obtained by genetic algorithm
and pattern search algorithm is 35.932% and 35.970%.