decomposition_sld: Problem Decomposition using Simplex-lattice Design

View source: R/decomposition_sld.R

decomposition_sldR Documentation

Problem Decomposition using Simplex-lattice Design

Description

Problem Decomposition using Simplex-lattice Design for MOEADr package

Usage

decomposition_sld(decomp, ...)

Arguments

decomp

list containing the relevant decomposition parameters. Besides decomp$name = "sld", this method requires the definition of the following key-value pairs:

  • decomp$H, decomposition constant. Suggested values for decomp$H are (use with caution):

    m |H |N
    2 |99 |100
    3 |12 |91
    5 |6 |210

    It is important to highlight that the number of vectors generated (N) must be greater than the number of neighbors declared in neighbors$T (see moead() for details).

  • decomp$.nobj: integer value, decomp$.nobj > 1. Number of objectives of the problem.

...

other parameters (included for compatibility with generic call)

Details

This routine calculates the weight vectors for the MOEA/D using the Simplex-lattice Design.

References

I. Das, J. Dennis (1998), "Normal Boundary Intersection - A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems", SIAM J. Optim., 8(3), 631-657. DOI: 10.1137/S1052623496307510

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

Examples

decomp <- list(name = "sld", H = 99, .nobj = 2)
W <- decomposition_sld(decomp)


MOEADr documentation built on Jan. 9, 2023, 1:24 a.m.