DocumentCode
2302144
Title
Notice of Retraction
A Virus Evolutionary Honeybee Mating Optimization
Author
Ning Wang ; Shoubao Su
Author_Institution
Dept. of Comput. Sci. & Technol., West Anhui Univ., Lu´an, China
Volume
3
fYear
2010
fDate
6-7 March 2010
Firstpage
198
Lastpage
201
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.
Honeybee mating optimization recently proposed is an optimization algorithm based on a particular intelligent behaviour of honeybee swarms. In this paper, inspired from virus evolutionary, by redefining mating operator and breeding operator we presented a new honeybee swarm optimization algorithm for multi-objective optimization. The test results show its performance in conducting an extensive search in the entire search space and the high potential of the proposed algorithm to solve multi-objective optimization problems.
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.
Honeybee mating optimization recently proposed is an optimization algorithm based on a particular intelligent behaviour of honeybee swarms. In this paper, inspired from virus evolutionary, by redefining mating operator and breeding operator we presented a new honeybee swarm optimization algorithm for multi-objective optimization. The test results show its performance in conducting an extensive search in the entire search space and the high potential of the proposed algorithm to solve multi-objective optimization problems.
Keywords
evolutionary computation; particle swarm optimisation; search problems; breeding operator; honeybee swarm optimization algorithm; intelligent behaviour; mating operator; multi-objective optimization; search space; virus evolutionary honeybee mating optimization; Algorithm design and analysis; Birds; Clustering algorithms; Computer science; Computer science education; Design optimization; Educational technology; Optimization methods; Particle swarm optimization; Testing; global optimiation; honeybee mating optimization; multi-objective optimization; swarm intelligence; virus evolutionary;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Type
conf
DOI
10.1109/ETCS.2010.335
Filename
5459966
Link To Document