Explain Genetic algorithms
Answers
Answer: The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that is based on natural selection, the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individual solutions.
Step-by-step explanation: Darwin’s theory of evolution has
been the inspiration for genetic algorithms. The algorithm uses an evolutionary
process to arrive at the solution to a problem. The algorithm works using a set
of solutions known as population and functions as an essential heuristic search
method in many artificial algorithm and machine learning applications to
determine optimized solutions for search problems.
A genetic algorithm relies on bio-inspired operators like selection, crossover and mutation.
The genetic algorithms is a method for solving both constrained and unconstrained optimization problem that is based on natural selection, the process that derives biological evolution.The genetic algorithm repetedly modifies a population of individual solution..!!!
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