DocumentCode :
627312
Title :
Multi-producer group search optimizer for function optimization
Author :
Junaed, A.B.M. ; Akhand, M.A.H. ; Al-Mahmud ; Murase, K.
Author_Institution :
Dept. of Comput. Sci. & Eng., Khulna Univ. of Eng. & Technol., Khulna, Bangladesh
fYear :
2013
fDate :
17-18 May 2013
Firstpage :
1
Lastpage :
4
Abstract :
Group Search Optimizer (GSO) is a population based optimization technique on the metaphor of producer-scrounger which is based on social behavior of animals where producer searches for finding foods and scrounger searches for joining opportunities. GSO has found as an efficient method for solving function optimization problems for which it modeled. Originally it was implemented for single producer. In this study we have extended the GSO algorithm for multiple producers, which is common in nature. We tested single producer and multiple producers on some benchmark problems and found better result for multiple producers.
Keywords :
evolutionary computation; optimisation; GSO algorithm; animal social behavior; function optimization problems; metaphor; multiple producers; multiproducer group search optimizer; population based optimization technique; producer-scrounger metaphor; single producer; Animals; Benchmark testing; Educational institutions; Optimization; Sociology; Statistics; Wheels; Animal Behaviour; Function Optimization; Group Search Optimizer; Multiple Producer; Swarm Intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics, Electronics & Vision (ICIEV), 2013 International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4799-0397-9
Type :
conf
DOI :
10.1109/ICIEV.2013.6572665
Filename :
6572665
Link To Document :
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