Construct the preference index matrix based only on performance values.
constraint_none(B, bigZ, bigV, ...)[ N x (T+1) ] matrix of preference indices. Each row i contains
a permutation of {1, 2, ..., (T+1)}, where 1,...,T correspond
to the solutions contained in the neighborhood of the i-th subproblem,
B[i, ], and T+1 corresponds to the incumbent solution for that
subproblem. The order of the permutation is defined by the increasing values
of f(xk), where f(xk) is the aggregation function value of
the k-th solution being compared.
Matrix of neighborhoods (generated by define_neighborhood(...)))
Matrix of scalarized objective values for each neighborhood and the
incumbent solution (generated by scalarize_values)
Matrix of violation values for each neighborhood and the incumbent solution
other parameters (unused, included for compatibility with generic call)
This function ignores the violation values when constructing the preference index matrix, using only the scalarized performance values.
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 tools:::Rd_expr_doi("10.18637/jss.v092.i06")