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Genetically Inclined


Genetic Algorithms (GAs) are adaptive methods which may be used to solve search and optimization problems. They are based on the genetic processes of biological organisms
GAs have the following features:

• They can solve complex problems without any knowledge of the solution method

• They adapt to the relative to the mutation of the problem
Application Areas

Optimization − Genetic Algorithms are most commonly used in optimization problems wherein we have to maximize or minimize a given objective function value under a given set of constraints.

Economics − GAs are also used to characterize various economic models like game theory equilibrium resolution, asset pricing, etc.

Image Processing − GAs are used for various digital image processing (DIP) tasks as well like dense pixel matching.

Vehicle routing − With multiple soft time windows, multiple depots and a heterogeneous fleet.

Robot Trajectory − GAs have been used to plan the path which a robot arm takes by moving from one point to another.
 
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