nsga-class | R Documentation |

The 'nsga' class is the parent superclass of the nsga1, nsga2, and nsga3 classes

`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.

`upper`

a vector providing for each decision variable the upper bounds of the search space in case of real-valued or permutation encoded optimizations.

`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.

`front`

Rank of individuals on the non-dominated front.

`f`

Front of individuals on the non-dominated front.

`iter`

the actual (or final) iteration of NSGA search.

`run`

the number of consecutive generations without any improvement in the best fitness value before the NSGA is stopped.

`maxiter`

the maximum number of iterations to run before the NSGA search is halted.

`suggestions`

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

`population`

the current (or final) population.

`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).

`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.

Since it is a virtual Class, no objects may be created from it.

showClass('nsga')

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