A heuristic approach for finding the global minimum: Adaptive random search technique


Hamzacebi C., Kutay F.

APPLIED MATHEMATICS AND COMPUTATION, vol.173, no.2, pp.1323-1333, 2006 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 173 Issue: 2
  • Publication Date: 2006
  • Doi Number: 10.1016/j.amc.2005.05.002
  • Journal Name: APPLIED MATHEMATICS AND COMPUTATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1323-1333
  • Keywords: random search technique, global minimum, random optimization, ARSET
  • Gazi University Affiliated: No

Abstract

In this paper, a new random search technique which facilitates the determination of the global minimum, is presented. This method, called Adaptive Random Search Technique (ARSET), is experimented on test problems, and successful results are obtained. ARSET algorithm, outcome of which is observed to be relatively better, is also compared with other methods. In addition, applicability of the algorithm on artificial neural network training is tested with XOR problem. (c) 2005 Elsevier Inc. All rights reserved.