View source: R/scalarization_wt.R
scalarization_wt | R Documentation |
Perform Weighted Tchebycheff Scalarization for the MOEADr package.
scalarization_wt(Y, W, minP, eps = 1e-16, ...)
Y |
matrix of objective function values |
W |
matrix of weights. |
minP |
numeric vector containing estimated ideal point |
eps |
tolerance value for avoiding divisions by zero. |
... |
other parameters (included for compatibility with generic call) |
This routine calculates the scalarized performance values for the MOEA/D using the Weighted Tchebycheff method.
Vector of scalarized performance values.
Q. Zhang and H. Li, "MOEA/D: A Multiobjective Evolutionary Algorithm
Based on Decomposition", IEEE Trans. Evol. Comp. 11(6): 712-731, 2007.
H. Li, Q. Zhang, "Multiobjective Optimization Problems With Complicated
Pareto Sets, MOEA/D and NSGA-II", IEEE. Trans. Evol. Comp. 12(2):284-302,
2009.
F. Campelo, L.S. Batista, C. Aranha (2020): The MOEADr Package: A
Component-Based Framework for Multiobjective Evolutionary Algorithms Based on
Decomposition. Journal of Statistical Software doi: 10.18637/jss.v092.i06
W <- generate_weights(decomp = list(name = "sld", H = 19), m = 2) Y <- matrix(runif(40), ncol = 2) minP <- apply(Y, 2, min) Z <- scalarization_wt(Y, W, minP)
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