Description Usage Arguments Details Value References Examples

View source: R/scalarization_awt.R

Perform Adjusted Weighted Tchebycheff Scalarization for the MOEADr package.

1 | ```
scalarization_awt(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 Adjusted Weighted Tchebycheff method.

Vector of scalarized performance values.

Y. Qi, X. Ma, F. Liu, L. Jiao, J. Sun, and J. Wu, “MOEA/D with adaptive weight adjustment,” Evolutionary Computation, vol. 22, no. 2, pp. 231–264, 2013.

R. Wang, T. Zhang, and B. Guo, “An enhanced MOEA/D using uniform directions and a pre-organization procedure,” in IEEE Congress on Evolutionary Computation, Cancun, Mexico, 2013, pp. 2390–2397.

1 2 3 4 | ```
W <- generate_weights(decomp = list(name = "sld", H = 19), m = 2)
Y <- matrix(runif(40), ncol = 2)
minP <- apply(Y, 2, min)
Z <- scalarization_awt(Y, W, minP)
``` |

MOEADr documentation built on Nov. 17, 2017, 6:56 a.m.

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