A fast and elitist multiobjective genetic algorithm based on R.
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fn |
Objective functions to be minimized |
varNo |
Number of decision variables |
objDim |
Number of objective functions |
lowerBounds |
Lower bounds of each decision variable |
upperBounds |
Upper bounds of each decision variable |
popSize |
Size of population |
tourSize |
Size of tournament |
generations |
Number of generations |
cprob |
Crossover probability |
XoverDistIdx |
Crossover distribution index, it can be any nonnegative real number |
mprob |
Mutation probability |
MuDistIdx |
Mutation distribution index, it can be any nonnegative real number |
The returned value is a 'nsga2R' object with the following fields in additional to above NSGA-II settings:
parameters |
Solutions of decision variables found |
objectives |
Non-dominated objective function values |
paretoFrontRank |
Nondomination ranks (or levels) that each non-dominated solution belongs to |
crowdingDistance |
Crowding distance of each non-dominated solution |
Ching-Shih (Vince) Tsou cstsou@mail.ntcb.edu.tw
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002), " A fast and elitist multiobjective genetic algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, 6(2), 182-197.
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