DocumentCode
1954189
Title
Notice of Retraction
An experimental study of messy genetic algorithm on HIFF problem
Author
Luwei Ding ; Zhenhua Li
Author_Institution
Sch. of Comput., China Univ. of Geosci., Wuhan, China
Volume
3
fYear
2010
fDate
9-11 July 2010
Firstpage
639
Lastpage
643
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.
A messy genetic algorithm (mGA), speculated by David Goldberg in 1989, is regarded as one of the most efficient method on those problems with Building Blocks (BB). While Hierarchical-if-and-only-if (HIFF) test problem is the basic example of a hierarchically consistent building-block problem. As it features hierarchical BB structure with multiple optima, HIFF test problem becomes the hardest test function for GA. This paper addresses the problem of HIFF based on messy genetic algorithm, which is a class of iterative optimization algorithm that makes use of a local search template, adaptive representation, and a decision theoretic sampling strategy and finally, conclusion is drawn and a short discussion is given.
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.
A messy genetic algorithm (mGA), speculated by David Goldberg in 1989, is regarded as one of the most efficient method on those problems with Building Blocks (BB). While Hierarchical-if-and-only-if (HIFF) test problem is the basic example of a hierarchically consistent building-block problem. As it features hierarchical BB structure with multiple optima, HIFF test problem becomes the hardest test function for GA. This paper addresses the problem of HIFF based on messy genetic algorithm, which is a class of iterative optimization algorithm that makes use of a local search template, adaptive representation, and a decision theoretic sampling strategy and finally, conclusion is drawn and a short discussion is given.
Keywords
genetic algorithms; iterative methods; search problems; Building Blocks; David Goldberg; HIFF problem; adaptive representation; decision theoretic sampling strategy; hierarchical BB structure; hierarchical-if-and-only-if test problem; iterative optimization algorithm; local search template; messy genetic algorithm; Argon; Book reviews; Educational institutions; Variable speed drives; HIFF; building blocks; genetic algorithm; messy genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-5537-9
Type
conf
DOI
10.1109/ICCSIT.2010.5564848
Filename
5564848
Link To Document