2009 International Conference on Information Technology and Computer Science 2009
DOI: 10.1109/itcs.2009.43
View full text |Buy / Rent full text
|
|
et al.

## Abstract:A novel algorithm called Free Search (FS) is applied to solve the scheduling problems on a single batch processing machine with non-identical job sizes (NSBM) in this paper. The concept of sensibility was introduced in FS, with which the algorithm had no restriction of the probability to zero for the parts of the search space and thus it could avoid premature convergence. In order to make it feasible to NSBM problem, we modify the parameters settings and also provide coding by vector method which makes FS prop… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2016
2016
2016
2016

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

##### Cited by 2 publications
(1 citation statement)
##### References 12 publications
(1 reference statement)
0
1
0
Order By: Relevance
“…Although achievements are preliminary, FS has showed prominent optimization potential. During the process, it is discovered that just like other evolutionary algorithms, FS also has divergence problems, premature convergence problems and so on (Zhang et al, 2009;Zhou et al, 2007;Zhu et al, 2009). The algorithm has no restriction of the probability to zero for the parts of the search space, with which it can cope with heterogeneous optimization problems.…”
Section: Introductionmentioning
confidence: 99%
“…Although achievements are preliminary, FS has showed prominent optimization potential. During the process, it is discovered that just like other evolutionary algorithms, FS also has divergence problems, premature convergence problems and so on (Zhang et al, 2009;Zhou et al, 2007;Zhu et al, 2009). The algorithm has no restriction of the probability to zero for the parts of the search space, with which it can cope with heterogeneous optimization problems.…”
Section: Introductionmentioning
confidence: 99%