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NSGA-III: Nondominated sorting genetic algorithm III
Reference: K. Deb and H. Jain, An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, part I: Solving problems with box constraints, IEEE Transactions on Evolutionary Computation, 2014, 18(4): 577-601.
NSGA-III is an improved version of the classic multi-objective evolutionary algorithm (MOEA) NSGA-II. NSGA-III implements reference points to tackle the difficulties of many-objective optimization.
Variables
Meaning
npop
Population size
iter
Iteration number
lb
Lower bound
ub
Upper bound
nobj
The dimension of objective space
pc
Crossover probability (default = 1)
pm
Mutation probability (default = 1)
eta_c
Spread factor distribution index (default = 30)
eta_m
Perturbance factor distribution index (default = 20)