Genetic Algorithms

Formulating a Genetic Algorithm Optimization

To formulate a GA in IML you must decide on five basic optimization parameters:

1. Encoding:: The general structure and form of the solution.
2. Objective:: The function to be optimized. IML also enables you to specify whether the function is to be minimized or maximized.
3. Selection:: How members of the current solution population will be chosen to be parents to propagate the next generation.
4. Crossover:: How the attributes of parent solutions will be combined to produce new offspring solutions.
5. Mutation:: How random variation will be introduced into the new offspring solutions to maintain genetic diversity.

The following section discusses each of these items in more detail.