nsga-class function

Virtual Class 'nsga'

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

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')