DocumentCode
518388
Title
Notice of Retraction
Partner selection of virtual enterprise using two-layer ant colony optimization
Author
Lei Jiao ; Zhonghua Ni ; Xiaojun Liu ; Tingyu Liu
Author_Institution
Jiangsu Key Lab. for Design & Manuf. of Micro-Nano Biomed. Instrum., Southeast Univ., Nanjing, China
Volume
1
fYear
2010
fDate
16-18 April 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
To improve the partner selection quality of virtual enterprise (VE), an improved ant colony optimization (ACO) named two-layer ACO (TL-ACO) was proposed in this paper. According to the features of partner selection, TL-ACO divided each selection step into two stages and each stage was given independent pheromone and visibility. As a result of that, the objective function could be much simpler than if original ACO was used, and the local optimum solution can be easily avoid by using the local obstruction (LO) method which was developed based on bionics. The simulation experiment manifested that the TL-ACO was effective and high-efficiency.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
To improve the partner selection quality of virtual enterprise (VE), an improved ant colony optimization (ACO) named two-layer ACO (TL-ACO) was proposed in this paper. According to the features of partner selection, TL-ACO divided each selection step into two stages and each stage was given independent pheromone and visibility. As a result of that, the objective function could be much simpler than if original ACO was used, and the local optimum solution can be easily avoid by using the local obstruction (LO) method which was developed based on bionics. The simulation experiment manifested that the TL-ACO was effective and high-efficiency.
Keywords
biocybernetics; optimisation; virtual enterprises; bionics; local obstruction method; partner selection quality; two-layer ACO; two-layer ant colony optimization; virtual enterprise; Ant colony optimization; Biomedical measurements; Companies; Decision making; Laboratories; Manufacturing industries; Mathematical model; NP-hard problem; Pulp manufacturing; Virtual enterprises; local obstruction method; partner selection; two-layer ant colony optimization; virtual enterprise;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5486116
Filename
5486116
Link To Document