Year: 2016
East Asian Journal on Applied Mathematics, Vol. 6 (2016), Iss. 3 : pp. 290–313
Abstract
A gravitational search algorithm (GSA) is a meta-heuristic development that is modelled on the Newtonian law of gravity and mass interaction. Here we propose a new hybrid algorithm called the Direct Gravitational Search Algorithm (DGSA), which combines a GSA that can perform a wide exploration and deep exploitation with the Nelder-Mead method, as a promising direct method capable of an intensification search. The main drawback of a meta-heuristic algorithm is slow convergence, but in our DGSA the standard GSA is run for a number of iterations before the best solution obtained is passed to the Nelder-Mead method to refine it and avoid running iterations that provide negligible further improvement. We test the DGSA on 7 benchmark integer functions and 10 benchmark minimax functions to compare the performance against 9 other algorithms, and the numerical results show the optimal or near optimal solution is obtained faster.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.030915.210416a
East Asian Journal on Applied Mathematics, Vol. 6 (2016), Iss. 3 : pp. 290–313
Published online: 2016-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 24
Keywords: Gravitational search algorithm direct search methods Nelder-Mead method integer programming problems minimax problems.
-
Multi-directional bat algorithm for solving unconstrained optimization problems
Tawhid, Mohamed A. | Ali, Ahmed F.OPSEARCH, Vol. 54 (2017), Iss. 4 P.684
https://doi.org/10.1007/s12597-017-0302-0 [Citations: 11] -
Hybrid bat algorithm and direct search methods for solving minimax problems
Ali, Ahmed F. | Tawhid, Mohamed A.International Journal of Hybrid Intelligent Systems, Vol. 14 (2018), Iss. 4 P.209
https://doi.org/10.3233/HIS-180252 [Citations: 1]