Genetic Algorithm : Lower and Upper Bounds
How to choose the VarMin (Lower Bound of decision Variables) and VarMax (Upper Bound of Variables) of any problem when using the genetic algorithm optimization ? What its effect on improvement ?
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The handling of bounds in the case of the use of ga is very well described.
Essentially, ga ensures that the initial population complies with the restrictions on bounds. Another point is compliance with the restrictions over the term of the algorithm, if certain conditions are met.
To define them use for example:
lb = [-1 0 0 -inf];
ub = [Inf 1 1 0];In the example above you have 4 decision variables x1…x4 which solutions are in the defined ranges of lb (1)…ub (1) for x1 and so on.
Determining meaningful bounds depends on the problem and requires insight into the problem.
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