DocumentCode :
2914385
Title :
Vaccine enhanced artificial immune system for multimodal function optimization
Author :
Woldemariam, Kumlachew M. ; Yen, Gary G.
Author_Institution :
Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
2143
Lastpage :
2150
Abstract :
This paper proposes the use of vaccine to promote exploration in the search space for solving multimodal function optimization problems using artificial immune system. In this method, first we divide the decision space into equal subspaces. Vaccine is then extracted randomly from each subspace. A few of these antigens are then injected into the algorithm to enhance the exploration of global and local optima. The vaccine is introduced in the form of suppressed antibodies. The goal of this process is to allocate the available antibodies at unexplored areas. Using this biologically motivated notion we design the vaccine enhanced artificial immune system for multimodal function optimization.
Keywords :
artificial immune systems; optimisation; biologically motivated notion; multimodal function optimization problems; search space exploration; vaccine enhanced artificial immune system; Artificial immune systems; Vaccines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4631083
Filename :
4631083
Link To Document :
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