Multi-Island Genetic Algorithm

In the Multi-Island Genetic Algorithm, as with other genetic algorithms, each design point is perceived as an individual with a certain value of fitness, based on the value of the objective function and constraint penalty. An individual with a better objective function value and a better penalty value has a higher fitness value.

The main feature of the Multi-Island Genetic Algorithm that distinguishes it from traditional genetic algorithms is that each population of individuals is divided into several sub-populations called “islands.” All traditional genetic operations are performed separately on each sub-population. Some individuals are then selected from each island and migrated to different islands periodically. This operation is called “migration.” Two parameters control the migration process:

  • Migration Interval. The number of generations between each migration.

  • Migration Rate. The percentage of individuals migrated from each island at the time of migration.