Abstract
Distributed manufacturing system has steadily becoming more significant for topics for researchers within manufacturing industry. It is due to the reason that it could provide higher flexibility for an organization to cope with a demanding and fluctuating market. This paper proposes distributed task assignment mechanism for multi-load Automated Guided Vehicle (AGV) operation in manufacturing industry. The architecture is based on multi-agent system (MAS) while the task assignment is based on combinatorial auction method. Additionally, necessary improvement have been made to the standard combinatorial auction method to support dynamic attributes of AGV task assignment mechanism.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2011 2nd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2011 |
| Pages | 207-211 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | 2011 2nd International Conference on Innovations in Bio-inspired Computing and Applications, IBICA 2011 - Shenzhen, Guangdong Duration: 2011 Dec 16 → 2011 Dec 18 |
Other
| Other | 2011 2nd International Conference on Innovations in Bio-inspired Computing and Applications, IBICA 2011 |
|---|---|
| City | Shenzhen, Guangdong |
| Period | 11/12/16 → 11/12/18 |
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Keywords
- autonomous AGV
- combinatorial auction
- intelligent agent
- multi-load capacity
ASJC Scopus subject areas
- Biotechnology
- Computational Theory and Mathematics
- Computer Science Applications
Cite this
Combinatorial auction method for decentralized task assignment of multiple-loading capacity AGV based on intelligent agent architecture. / Fauadi, Muhammad Hafidz Fazli Bin Md; Li, Wan Ling; Murata, Tomohiro.
Proceedings - 2011 2nd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2011. 2011. p. 207-211 6118607.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Combinatorial auction method for decentralized task assignment of multiple-loading capacity AGV based on intelligent agent architecture
AU - Fauadi, Muhammad Hafidz Fazli Bin Md
AU - Li, Wan Ling
AU - Murata, Tomohiro
PY - 2011
Y1 - 2011
N2 - Distributed manufacturing system has steadily becoming more significant for topics for researchers within manufacturing industry. It is due to the reason that it could provide higher flexibility for an organization to cope with a demanding and fluctuating market. This paper proposes distributed task assignment mechanism for multi-load Automated Guided Vehicle (AGV) operation in manufacturing industry. The architecture is based on multi-agent system (MAS) while the task assignment is based on combinatorial auction method. Additionally, necessary improvement have been made to the standard combinatorial auction method to support dynamic attributes of AGV task assignment mechanism.
AB - Distributed manufacturing system has steadily becoming more significant for topics for researchers within manufacturing industry. It is due to the reason that it could provide higher flexibility for an organization to cope with a demanding and fluctuating market. This paper proposes distributed task assignment mechanism for multi-load Automated Guided Vehicle (AGV) operation in manufacturing industry. The architecture is based on multi-agent system (MAS) while the task assignment is based on combinatorial auction method. Additionally, necessary improvement have been made to the standard combinatorial auction method to support dynamic attributes of AGV task assignment mechanism.
KW - autonomous AGV
KW - combinatorial auction
KW - intelligent agent
KW - multi-load capacity
UR - http://www.scopus.com/inward/record.url?scp=84862928245&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84862928245&partnerID=8YFLogxK
U2 - 10.1109/IBICA.2011.56
DO - 10.1109/IBICA.2011.56
M3 - Conference contribution
AN - SCOPUS:84862928245
SP - 207
EP - 211
BT - Proceedings - 2011 2nd International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2011
ER -