Genetic algorithms are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology such as inheritance, mutation, selection, and crossover (also called recombination). a) Optimization is a process that finds a best, or optimal, solution for a problem. Explain in your own words the three factors that are centered on optimization problems in genetic algorithms and illustrate your answers with appropriate examples. AN(6) b) In your own words, clearly discuss the five applications of genetic algorithms and provide appropriate examples to explain your answers. CR(7) c) Explain in details with practical examples how one-point crossover and two-point crossover operators work in your own words.
Genetic
techniques inspired by evolutionary biology such as inheritance, mutation,
selection, and crossover (also called recombination).
a) Optimization is a process that finds a best, or optimal, solution for a
problem. Explain in your own words the three factors that are centered
on optimization problems in genetic algorithms and illustrate your
answers with appropriate examples.
AN(6)
b) In your own words, clearly discuss the five applications of genetic
algorithms and provide appropriate examples to explain your answers.
CR(7)
c) Explain in details with practical examples how one-point crossover and
two-point crossover operators work in your own words.
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