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

An S4 class for genetic algorithms

Objects can be created by calls to the `ga`

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;

`iter`

the actual (or final) iteration of GA search;

`run`

the number of consecutive generations without any improvement in the best fitness value before the GA 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;

`population`

the current (or final) population;

`elitism`

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

`pcrossover`

the crossover probability;

`pmutation`

the mutation probability;

`fitness`

the values of fitness function for the current (or final) population;

`summary`

a matrix of summary statistics for fitness values at each iteration (along the rows);

`bestSol`

if

`keepBest = TRUE`

, the best solutions at each iteration;`fitnessValue`

the best fitness value at the final iteration;

`solution`

the value(s) of the decision variables giving the best fitness at the final iteration.

Luca Scrucca

For examples of usage see `ga`

.

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