updt_best | R Documentation |
Population update using the best neighborhood replacement method for the MOEADr package.
updt_best(update, X, Xt, Y, Yt, V, Vt, normYs, W, BP, constraint, aggfun, ...)
update |
List containing the population update parameters. See
Section
|
X |
Matrix of candidate solutions |
Xt |
Matrix of incumbent solutions |
Y |
Matrix of objective function values of |
Yt |
Matrix of objective function values of |
V |
List object containing information about the constraint violations
of the candidate solutions, generated by |
Vt |
List object containing information about the constraint violations
of the incumbent solutions, generated by |
normYs |
List generated by |
W |
matrix of weights, generated by |
BP |
Neighborhood list, generated by |
constraint |
list containing the parameters defining the constraint
handling method. See Section |
aggfun |
List containing the aggregation function parameters. See
Section |
... |
other parameters (included for compatibility with generic call) |
The Best Neighborhood Replacement method consists of three steps:
For each subproblem i
, the best candidate solution x_j
from the
entire population is determined.
The neighborhood of subproblem i
is replaced by the neighborhood
of subproblem j. The size of this neighborhood is given by a parameter
Tr
.
The Restricted replacement (see updt_restricted()
) is then
applied using this new neighborhood.
This update routine is intended to be used internally by the main moead()
function, and should not be called directly by the user.
List object containing the update population matrix (X
),
and its corresponding matrix of objective function values (Y
) and
constraint value list (V
).
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
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.