GA
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.