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.