Description Objects from the Class Slots Author(s) See Also

An S4 class for islands genetic algorithms (ISLGAs)

Objects can be created by calls to the `gaisl`

function.

`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.

Luca Scrucca

For examples of usage see `gaisl`

.

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