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