gaisl-class {GA} | R Documentation

## Class "gaisl"

### Description

An S4 class for islands genetic algorithms (ISLGAs)

### Objects from the Class

Objects can be created by calls to the `gaisl` function.

### Slots

`call`

  an object of class `"call"` representing the matched call;

`type`

  a character string specifying the type of genetic algorithm used;

`lower`

  a vector providing for each decision variable the lower bounds of the search space in case of real-valued or permutation encoded optimisations. Formerly this slot was named `min`;

`upper`

  a vector providing for each decision variable the upper bounds of the search space in case of real-valued or permutation encoded optimizations. Formerly this slot was named `max`;

`nBits`

  a value specifying the number of bits to be used in binary encoded optimizations;

`names`

  a vector of character strings providing the names of decision variables (optional);

`popSize`

  the population size;

`numIslands`

  the number of islands;

`migrationRate`

  the migration rate;

`migrationInterval`

  the migration interval;

`maxiter`

  the maximum number of ISLGA iterations before the search is halted;

`run`

  the number of consecutive generations without any improvement in the best fitness value before the ISLGA is stopped;

`maxiter`

  the maximum number of iterations to run before the GA search is halted;

`suggestions`

  a matrix of user provided solutions and included in the initial population;

`elitism`

  the number of best fitness individuals to survive at each generation;

`pcrossover`

  the crossover probability;

`pmutation`

  the mutation probability;

`optim`

  a logical specifying whether or not a local search using general-purpose optimisation algorithms should be used;

`islands`

  a list containing the objects of class `ga` corresponding to each island GA evolution;

`summary`

  a list of matrices of summary statistics for fitness values at each iteration (along the rows). Each element of the list corresponds to the evolution of an island;

`fitnessValues`

  a list of best fitness values found in each island at the final iteration;

`solutions`

  a list of matrices, one for each island, containing the values of the decision variables giving the best fitness at the final iteration;

`fitnessValue`

  the best fitness value at the final iteration;

`solution`

  a matrix containing the values of the decision variables giving the best fitness at the final iteration.

### Author(s)

Luca Scrucca

### See Also

For examples of usage see `gaisl`.

[Package GA version 3.2 Index]