Abstract
A hybrid Orthogonal Scheme Ant Colony Optimization (OSACO) algorithm for continuous function optimization (CFO) is presented in this paper. The methodology integrates the advantages of Ant Colony Optimization (ACO) and Orthogonal Design Scheme (ODS). OSACO is based on the following principles: a) each independent variable space (IVS) of CFO is dispersed into a number of random and movable nodes; b) the carriers of pheromone of ACO are shifted to the nodes; c) solution path can be obtained by choosing one appropriate node from each IVS by ant; d) with the ODS, the best solved path is further improved. The proposed algorithm has been successfully applied to 10 benchmark test functions. The performance and a comparison with CACO and FEP have been studied.
| Language | English |
|---|---|
| Title of host publication | Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings |
| Publisher | Springer-Verlag |
| Pages | 126-133 |
| Number of pages | 8 |
| Volume | 4247 LNCS |
| ISBN (Print) | 3540473319, 9783540473312 |
| Publication status | Published - 1 Jan 2006 |
| Event | 6th International Conference Simulated Evolution and Learning, SEAL 2006 - Hefei, China Duration: 15 Oct 2006 → 18 Oct 2006 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 4247 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 6th International Conference Simulated Evolution and Learning, SEAL 2006 |
|---|---|
| Country | China |
| City | Hefei |
| Period | 15/10/06 → 18/10/06 |
Fingerprint
Keywords
- search range
- solution path
- unimodal function
- multimodal function
- pheromone information
Cite this
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Continuous function optimization using hybrid ant colony approach with orthogonal design scheme. / Zhang, Jun; Chen, Wei Neng; Zhong, Jing Hui; Tan, Xuan; Li, Yun.
Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings. Vol. 4247 LNCS Springer-Verlag, 2006. p. 126-133 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4247 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
TY - GEN
T1 - Continuous function optimization using hybrid ant colony approach with orthogonal design scheme
AU - Zhang, Jun
AU - Chen, Wei Neng
AU - Zhong, Jing Hui
AU - Tan, Xuan
AU - Li, Yun
PY - 2006/1/1
Y1 - 2006/1/1
N2 - A hybrid Orthogonal Scheme Ant Colony Optimization (OSACO) algorithm for continuous function optimization (CFO) is presented in this paper. The methodology integrates the advantages of Ant Colony Optimization (ACO) and Orthogonal Design Scheme (ODS). OSACO is based on the following principles: a) each independent variable space (IVS) of CFO is dispersed into a number of random and movable nodes; b) the carriers of pheromone of ACO are shifted to the nodes; c) solution path can be obtained by choosing one appropriate node from each IVS by ant; d) with the ODS, the best solved path is further improved. The proposed algorithm has been successfully applied to 10 benchmark test functions. The performance and a comparison with CACO and FEP have been studied.
AB - A hybrid Orthogonal Scheme Ant Colony Optimization (OSACO) algorithm for continuous function optimization (CFO) is presented in this paper. The methodology integrates the advantages of Ant Colony Optimization (ACO) and Orthogonal Design Scheme (ODS). OSACO is based on the following principles: a) each independent variable space (IVS) of CFO is dispersed into a number of random and movable nodes; b) the carriers of pheromone of ACO are shifted to the nodes; c) solution path can be obtained by choosing one appropriate node from each IVS by ant; d) with the ODS, the best solved path is further improved. The proposed algorithm has been successfully applied to 10 benchmark test functions. The performance and a comparison with CACO and FEP have been studied.
KW - search range
KW - solution path
KW - unimodal function
KW - multimodal function
KW - pheromone information
UR - http://www.scopus.com/inward/record.url?scp=33751373758&partnerID=8YFLogxK
M3 - Conference contribution book
SN - 3540473319
SN - 9783540473312
VL - 4247 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 126
EP - 133
BT - Simulated Evolution and Learning - 6th International Conference, SEAL 2006, Proceedings
PB - Springer-Verlag
ER -