An S4 class for differential evolution algorithm
Objects can be created by calls to the de
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
;
names
a vector of character strings providing the names of decision variables (optional);
popSize
the population size;
iter
the actual (or final) iteration of DE search;
run
the number of consecutive generations without any improvement in the best fitness value before the DE is stopped;
maxiter
the maximum number of iterations to run before the DE 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;
stepsize
the stepsize or weighting factor;
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;
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 de
.