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Genetics and Algorithms
A genetic algorithm is a search heuristic that is inspired by Charles Darwin's theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation.
Optimisation
Optimization is the process of making something better. In any process, we have a set of inputs and a set of outputs as shown in the following figure.Optimization refers to finding the values of inputs in such a way that we get the “best” output values.
Suggested Video
Tutorial - Create your own GA (Genetic Algorithm)
First: Setting the scene - the knapsack problem
Additional Information
They are commonly used to generate high-quality solutions for optimization problems and search problems.
Genetic algorithms simulate the process of natural selection which means those species who can adapt to changes in their environment are able to survive and reproduce and go to next generation. In simple words, they simulate “survival of the fittest” among individual of consecutive generation for solving a problem.
How it works
Each generation consist of a population of individuals and each individual represents a point in search space and possible solution. Each individual is represented as a string of character/integer/float/bits. This string is analogous to the Chromosome.