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Welcome to an introductive tutorial on Genetic Algorithms (GA’s).

 

In the last decades many human minds have spent a lot of resources to provide the world with new tools to solve old and new problems.

Classical methods in most cases are more elegant, accurate, and efficient, but they some times encounter limitations when they need to represent and handle real world situations.

Genetic Algorithms and Evolutionary Methods in general, provide new ways to work on certain kinds of problems. They are inspired in the Darwinian laws of evolution concepts of biologic genetics.

You don’t need know the exact internal behavior of the system on which you’ll work with. However, you must have enough understanding of the system’s outputs and their effects on the environment in order to evaluate possible solutions.

Let’s take a look to some of the basic concepts that you may use to build your own algorithm for your exact needs.

Now, please see  What is a Genetic Algorithm?

 

 

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