DocumentCode
2137041
Title
An improved gravitational search algorithm based on neighbor search
Author
Wang, Chingyue ; Gao, K.Z. ; GUO, Jun
Author_Institution
Coll. of Electr. & Inf. Eng., Yangzhou Polytech. Inst., Yangzhou, China
fYear
2013
fDate
23-25 July 2013
Firstpage
681
Lastpage
685
Abstract
The gravitational search algorithm (GSA) is a new meta-heuristic optimization method based on the law of gravity and mass interactions. An improved GSA (IGSA) is proposed in this paper where a neighbor search is employed to enhance the performance of GSA. The IGSA can obtain a better or best solution in a neighbor space through one or more times random neighbor search. Two different search methods are designed for the proposed improved gravitational search algorithm. In addition, the effect of the gravitational constant to the performance of the IGSA is discussed. Extensive computational experiments are carried out using well-known benchmark functions. Computational results and comparisons show the efficiency and effectiveness of the proposed IGSA.
Keywords
search problems; GSA; improved gravitational search algorithm; meta-heuristic optimization method; neighbor search; Algorithm design and analysis; Benchmark testing; Classification algorithms; Convergence; Educational institutions; Force; Optimization; gravitation search algorithm; meta-heuristic; random neighbor search;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2013 Ninth International Conference on
Conference_Location
Shenyang
Type
conf
DOI
10.1109/ICNC.2013.6818062
Filename
6818062
Link To Document