| nsga-class {rmoo} | R Documentation | 
Virtual Class 'nsga'
Description
The 'nsga' class is the parent superclass of the nsga1, nsga2, and nsga3 classes
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. 
- 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. 
Objects from the Class
Since it is a virtual Class, no objects may be created from it.
Examples
showClass('nsga')