Research Article
Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies
Algorithm 1
MOEA/D.
input: : population size; | |
: the number of neighbors for each weight vector, ; | |
: a set of evenly distributed weight vectors; | |
output: Pareto solutions on the objective space: | |
1 Initialization: | |
2 are randomly sampled from , ; | |
3 foreach to do ; / are the closest weight vectors to / | |
4 reference point . // | |
5 while stop criteria are not met do | |
6 for to do | |
7 reproduce; /andare selected from/ | |
8 mutate; | |
9 if then | |
10 repair; | |
11 end | |
12 foreach i to do | |
13 if then | |
14 ; | |
15 end | |
16 end | |
17 foreach do | |
18 if then | |
19 ; | |
20 ; | |
21 end | |
22 end | |
23 end | |
24 end |