Genetic Algorithm Operations
The basic GA that can produce acceptable results in many practical problems is composed of three operations:
a. Reproduction
b. Crossover
c. Mutation
The reproduction process is to allow the genetic information, stored in the good fitness for survive the next generation of the artificial strings, whereas the population's string has assigned a value and its aptitude in the object function. This value has the probability of being chosen as the parent in the reproduction process of a new generation.
The crossover is a process is divided into segments, which are exchanged with the one segments with the another string. With these process two new strings different to those that produced they are generated. It is necessary to clarify that the choice of strings crossed inside those that were chosen previously in the reproduction process is random. From the point of view of problem optimization, it is equal to the exploitation of an area of the parameters space.
The mutation is manifested with a small change in the genetic string of the individuals. In the case of artificial genetic strings, the mutation is equal to a change in the elementary portion (allele) of the individuals’ code. The mutation takes place with characteristics different to those that the individuals had at the beginning, characteristics that didn't possibly exist in the population. From the point of view of problem optimization, it is equal to a change of the search area in the parameters space.
Genetic algorithm basic parameters
The convergence of the GA to a suitable solution depends on its basic parameter like reproduction, crossover, mutation, selection and population; which to find a relationship among them to maintain search robust...
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...taken objective, which takes into focus the economic aspects (deposition efficiency) and the geometric characteristics (penetration, width and reinforcement) of the bead.
It was seen that the Genetic Algorithm can be a powerful tool in welding experiment optimization, even when the experimenter does not have a model for the process. The most important response (depth of penetration) had a difference from its target lower than 4%.
However, the optimization carried by GA technology requires a better setting of its own parameters, such as number of generations, population size, etc. Otherwise, there may be a risk of an insufficient sweeping of the search space system. In addition, it is suggested the use of conventional projects to research the space around the conditions found by the GA, in order to obtain models and/or perform a fine-tuning of the optimal parameters.
−→ C = 2 −→ r 2 (14) where components of −→ a are linearly decreased from 2 to 0 over the course of iterations and r 1 , r2 are random vectors in [0, 1]. The hunt is usually guided by the alpha. The beta and delta might also participate in hunting occasionally. In order to mathematically simulate the hunting behavior of grey wolves, the alpha (best candidate solution) beta, and delta are assumed to have better knowledge about the potential location of prey. The first three best solutions obtained so far and oblige the other search agents (including the omegas) to update their positions according to the position of the best search agents.
[7] Klug, W., Cummings, M., Spencer, C., Palladino M. (2012) Concepts of Genetics: Tenth Edition. Pearson's Education, Inc.
The simulator does something similar to this. The organisms in the beginning are identical. They have arms of a similar length as a result of their phenotypes. To simulate nature, every cycle we could say represents a generation. Every generation we see new organisms born with random mutations. Based on the environment we see different mutations on the newborn. For example, if its environment through the generations allowed its ancestors to survive, based on the phenotypes we saw in the ancestors we can see them again in the newborn. Basically saying that the parents of the newborn lived long enough to mate with the same traits., in turn giving the newborn those same exact traits. In this case, it is traits which code for arms length.
The exercise involved a series of ‘mating’ events resulting in 6 generations. Each mating event produced offspring with ‘possible’ newly inherited traits. The idea of ‘chance’ was included through simple coin tosses. Also, ideas of selection and mutations were introduced into the ‘gene pool’, which presented a deeper and more clear understanding of Mendelian inheritance and the Hardy-Weinberg equilibrium. Upon reaching the third generation, A B1 mutant allele was introduced to the blue locus-influencing fin shape and a G1 mutant allele was introduced to the green locus-influencing Mouth
Today, we can define evolutionary change on its smallest scale, or microevolution, as change in the genetic makeup of a populations from generation to generations.
...gic is based on uncertainties in traditional logic there is no place for uncertainties. Some technologic areas that fuzzy logic is used can be ordered like that:
On Christmas Day in the year 2001, I gave birth to a healthy baby boy. When I looked into the brand-new face of my son I saw a beautiful mystery. I wondered what kind of man my boy would grow to be and what his life would be like. There are those in the scientific community who would argue that my son's path was already determined at the moment of his birth, that his fate could be deciphered from his genetic make-up. As a nurturing mother I know better. At two years old my son has developed a more diverse vocabulary than many children twice or even three times his age. He recognizes many written words and reads them aloud. He is able to spell his name. He can distinguish a square from a rectangle and an octagon from a hexagon. Was he born with this knowledge? The answer is no. My son, as genetically gifted as he may be, could have been born into an environment in which his inborn potential was never developed. The knowledge he now possesses can be directly traced to the teaching environment in which he has grown. Human beings are a product of both their biology and their environment.
Genetic Algorithms provide a holistic search process based on principles of natural genetics and survivals of the fittest……
In this section, the results of the research are presented. For each task carried out, the most important information obtained is presented.
Genes are, basically, the blueprints of our body which are passed down from generation to generation. Through the exploration of these inherited materials, scientists have ventured into the recent, and rather controversial, field of genetic engineering. It is described as the "artificial modification of the genetic code of a living organism", and involves the "manipulation and alteration of inborn characteristics" by humans (Lanza). Like many other issues, genetic engineering has sparked a heated debate. Some people believe that it has the potential to become the new "miracle tool" of medicine. To others, this new technology borders on the realm of immorality, and is an omen of the danger to come, and are firmly convinced that this human intervention into nature is unethical, and will bring about the destruction of mankind (Lanza).
As previously stated, there are several ways that these changes can occur, but the ones I will be focusing on are changes occurring to methyl and acetyl groups. The mechanism of heritability in animals is information coded into genes. Genes are wrapped around histones in the nucleus. When methyl groups attach to these histones, it winds the genes tighter, and since the shape is altered, it also alters the protein the gene codes for. Generally speaking, when you add a methyl group onto the histones, or "spool" of the gene, it makes it harder to code that gene’s proteins, just like if you got something stuck in the chain on your bike and tried to pedal it. The more methyl groups that build up, the worse the problem becomes. However, in most of the cases acetylation unwinds some of the histones, activating or reactivating a gene. Scientists are explo...
Mutation happens when the DNA gene gets changed, moves, or is damaged. When this happens it causes the genetic message to be carried by that gene to be different. This process can occur in somatic cells. The somatic cells are all the cells that are a living organism except the reproductive cells, meaning the body. For example, the skin cells on your legs are and will not be passed on to ones offsprings. In addition those leg cells will not effect the evolution. Another occurrence is called gametic mutations, which is in a woman's eggs and or in a man's sperm. These are cells that are and can be passed on to ones offsprings, and they are the essentials for the evolution. There are three effects mutation causes to a species. Species can only takes on one of the three. The three effects are bad, neutral, and good. Having a bad mutation can cause one to have a harder time being able to survive. Having a neutral mutation will not change or help one to survive. Having a good mutation will help one to survive and have a better chance of survival. However, mutation is random in the evolution, and provides raw material for natural selection, genetic drift, and gene flow...
GMAW (Gas Metal Arc Welding) is more economic; Springer reports that “ GMAW is an economic process because it has higher speeds and higher deposition rates than manual arc welding. There is also no need to constantly change electrodes” (Page 11). GMAW has a higher speed, which means that you can get the job done faster. It also has high deposition rates which makes the weld look clean and smooth.” This method can be used for a high range of work, but it is not suited for repair work because of it’s weld quality” (Page 4).
Inside the cells that produce sperm and eggs, chromosomes become paired. While they are pressed together, the chromosomes may break, and each may swap a portion of its genetic material for the matching portion from its mate. This form of recombination is called crossing-over. When the chromosomes glue themselves back together and separate, each has picked up new genetic material from the other. The constellation of physical characteristics it determines is now different than before crossing-over.
?Automation Reduces Weld Spatter? Welding Design & Fabrication (Jun. 2001): 37 EBSCOhost. Online. Nov. 2002 .