An S4 class for genetic algorithms
Objects can be created by calls to the ga function.
callan object of class "call" representing the matched call;
typea character string specifying the type of genetic algorithm used;
mina vector providing for each decision variable the minimum of the search space in case of real-valued or permutation encoded optimizations;
maxa vector providing for each decision variable the maximum of the search space in case of real-valued or permutation encoded optimizations;
nBitsa value specifying the number of bits to be used in binary encoded optimizations;
namesa vector of character strings providing the names of decision variables (optional);
popSizethe population size;
iterthe actual (or final) iteration of GA search;
runthe number of consecutive generations without any improvement in the best fitness value before the GA is stopped;
maxiterthe maximum number of iterations to run before the GA search is halted;
suggestionsa matrix of user provided solutions and included in the initial population;
populationthe current (or final) population;
elitismthe number of best fitness individuals to survive at each generation;
pcrossoverthe crossover probability;
pmutationthe mutation probability;
fitnessthe values of fitness function for the current (or final) population;
summarya matrix of summary statistics for fitness values at each iteration (along the rows);
bestSolif keepBest = TRUE, the best solutions at each iteration;
fitnessValuethe best fitness value at the final iteration;
solutionthe value(s) of the decision variables giving the best fitness at the final iteration.
For examples of usage see ga.