What is the relationship between individuals fitness and their offsprings in genetic algorithm?Genetics algorithms theoretical questionWhat is the correct way to execute selection procedure in a genetic algorithm?genetic algorithm crossover operationGenetic Algorithm - deciding on the number of children to generateGenetic algorithm Crossover Number of offspringsDoes translating the genes in a chromosome for a genetic algorithm for a combinatorial function increase the diversity of candidates?Cellular Genetic Algorithm - individual evaluation before selecting parentshow to mutate offspring in genetic algorithm?What are the advantages and disadvantages of using the crossover genetic operator?Genetic Algorithm - Parent Selection vs. Crossover Probability
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What is the relationship between individuals fitness and their offsprings in genetic algorithm?
Genetics algorithms theoretical questionWhat is the correct way to execute selection procedure in a genetic algorithm?genetic algorithm crossover operationGenetic Algorithm - deciding on the number of children to generateGenetic algorithm Crossover Number of offspringsDoes translating the genes in a chromosome for a genetic algorithm for a combinatorial function increase the diversity of candidates?Cellular Genetic Algorithm - individual evaluation before selecting parentshow to mutate offspring in genetic algorithm?What are the advantages and disadvantages of using the crossover genetic operator?Genetic Algorithm - Parent Selection vs. Crossover Probability
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In genetic algorithm , is it the best way to have offsprings with high fitness is to crossover with individuals with high fitness so that the offsprings have high fitness too? Is there any guarantee that parents with high fitness will produce offsprings with high fitness ? Any mathematical proof for this.
optimization genetic-algorithm
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
add a comment |
In genetic algorithm , is it the best way to have offsprings with high fitness is to crossover with individuals with high fitness so that the offsprings have high fitness too? Is there any guarantee that parents with high fitness will produce offsprings with high fitness ? Any mathematical proof for this.
optimization genetic-algorithm
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
This question is way too general. I don't think there is a strong answer for this, and that explains the many different implementations of genetic algorithms. Some use crossover, some don't. Some always pick the best individuals as parents, some don't.
– Pablo
Apr 1 at 7:43
@Pablo Can you suggest some resources to read about what you just said. Thank you very much.
– Paulo
Apr 2 at 9:23
Perhaps you could take a look at this chapter ( cs.vu.nl/~gusz/ecbook/Eiben-Smith-Intro2EC-Ch2.pdf ). It comes from this book ( cs.vu.nl/~gusz/ecbook/ecbook.html ). Lucky you, this chapter is a free sample!
– Pablo
Apr 2 at 14:41
@Pablo Thanks a lot .
– Paulo
Apr 2 at 14:43
add a comment |
In genetic algorithm , is it the best way to have offsprings with high fitness is to crossover with individuals with high fitness so that the offsprings have high fitness too? Is there any guarantee that parents with high fitness will produce offsprings with high fitness ? Any mathematical proof for this.
optimization genetic-algorithm
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
In genetic algorithm , is it the best way to have offsprings with high fitness is to crossover with individuals with high fitness so that the offsprings have high fitness too? Is there any guarantee that parents with high fitness will produce offsprings with high fitness ? Any mathematical proof for this.
optimization genetic-algorithm
optimization genetic-algorithm
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
asked Mar 27 at 8:33
PauloPaulo
598 bronze badges
598 bronze badges
This question is way too general. I don't think there is a strong answer for this, and that explains the many different implementations of genetic algorithms. Some use crossover, some don't. Some always pick the best individuals as parents, some don't.
– Pablo
Apr 1 at 7:43
@Pablo Can you suggest some resources to read about what you just said. Thank you very much.
– Paulo
Apr 2 at 9:23
Perhaps you could take a look at this chapter ( cs.vu.nl/~gusz/ecbook/Eiben-Smith-Intro2EC-Ch2.pdf ). It comes from this book ( cs.vu.nl/~gusz/ecbook/ecbook.html ). Lucky you, this chapter is a free sample!
– Pablo
Apr 2 at 14:41
@Pablo Thanks a lot .
– Paulo
Apr 2 at 14:43
add a comment |
This question is way too general. I don't think there is a strong answer for this, and that explains the many different implementations of genetic algorithms. Some use crossover, some don't. Some always pick the best individuals as parents, some don't.
– Pablo
Apr 1 at 7:43
@Pablo Can you suggest some resources to read about what you just said. Thank you very much.
– Paulo
Apr 2 at 9:23
Perhaps you could take a look at this chapter ( cs.vu.nl/~gusz/ecbook/Eiben-Smith-Intro2EC-Ch2.pdf ). It comes from this book ( cs.vu.nl/~gusz/ecbook/ecbook.html ). Lucky you, this chapter is a free sample!
– Pablo
Apr 2 at 14:41
@Pablo Thanks a lot .
– Paulo
Apr 2 at 14:43
This question is way too general. I don't think there is a strong answer for this, and that explains the many different implementations of genetic algorithms. Some use crossover, some don't. Some always pick the best individuals as parents, some don't.
– Pablo
Apr 1 at 7:43
This question is way too general. I don't think there is a strong answer for this, and that explains the many different implementations of genetic algorithms. Some use crossover, some don't. Some always pick the best individuals as parents, some don't.
– Pablo
Apr 1 at 7:43
@Pablo Can you suggest some resources to read about what you just said. Thank you very much.
– Paulo
Apr 2 at 9:23
@Pablo Can you suggest some resources to read about what you just said. Thank you very much.
– Paulo
Apr 2 at 9:23
Perhaps you could take a look at this chapter ( cs.vu.nl/~gusz/ecbook/Eiben-Smith-Intro2EC-Ch2.pdf ). It comes from this book ( cs.vu.nl/~gusz/ecbook/ecbook.html ). Lucky you, this chapter is a free sample!
– Pablo
Apr 2 at 14:41
Perhaps you could take a look at this chapter ( cs.vu.nl/~gusz/ecbook/Eiben-Smith-Intro2EC-Ch2.pdf ). It comes from this book ( cs.vu.nl/~gusz/ecbook/ecbook.html ). Lucky you, this chapter is a free sample!
– Pablo
Apr 2 at 14:41
@Pablo Thanks a lot .
– Paulo
Apr 2 at 14:43
@Pablo Thanks a lot .
– Paulo
Apr 2 at 14:43
add a comment |
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This question is way too general. I don't think there is a strong answer for this, and that explains the many different implementations of genetic algorithms. Some use crossover, some don't. Some always pick the best individuals as parents, some don't.
– Pablo
Apr 1 at 7:43
@Pablo Can you suggest some resources to read about what you just said. Thank you very much.
– Paulo
Apr 2 at 9:23
Perhaps you could take a look at this chapter ( cs.vu.nl/~gusz/ecbook/Eiben-Smith-Intro2EC-Ch2.pdf ). It comes from this book ( cs.vu.nl/~gusz/ecbook/ecbook.html ). Lucky you, this chapter is a free sample!
– Pablo
Apr 2 at 14:41
@Pablo Thanks a lot .
– Paulo
Apr 2 at 14:43