Research Article
A Novel MOEA/D for Multiobjective Scheduling of Flexible Manufacturing Systems
Algorithm 1
Algorithm DMOEA/D.
Input | |
: the number of sub-problems used in DMOEA/D; | |
: the set of uniform spread weight vectors; | |
H: the size of neighborhood of each weight vector; | |
Initialize | |
Set , initialize population ; | |
Set , , initialize , where ; | |
Compute the Euclidean distances between any two weight vectors and figure out the H closest ones of each weight vector; | |
Set , where are the H closest weight vectors to . | |
While(the stopping criterion is not met) | |
For | |
Randomly select three different neighbors xa, xb, and xc from E(j); | |
Generate the mutated solution xv from xa, xb, and xc; | |
Generate the trial solution xu from xj and xv; Amend xu; | |
For | |
If | |
Set ; | |
// End For | |
For (each index ) | |
If() | |
Set ; ; | |
// End For | |
Remove all the vectors dominated by F(xu) from EP; | |
If(there is no vector dominates F(xu) and F(xu) do not exist in EP) | |
Add F(xu) into EP; | |
// End For | |
// End While | |
Output EP |