Research Article
Decomposition-Based Multiobjective Optimization with Invasive Weed Colonies
Algorithm 2
MOEA/D-IWO.
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 IWO; | |
8 IWO; | |
9 / is selected from / | |
10 foreach do | |
11 if then | |
12 Repair; | |
13 end | |
14 foreach to do | |
15 if then | |
16 ; | |
17 end | |
18 end | |
19 foreach do | |
20 if then | |
21 ; | |
22 ; | |
23 end | |
24 end | |
25 end | |
26 end | |
27 end |