Journal
NEURAL COMPUTING & APPLICATIONS
Volume 28, Issue -, Pages S153-S168Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-016-2328-2
Keywords
Hill climbing; Metaheuristics; Global optimization; Local search methods; Operations research
Categories
Ask authors/readers for more resources
Hill climbing method is an optimization technique that is able to build a search trajectory in the search space until reaching the local optima. It only accepts the uphill movement which leads it to easily get stuck in local optima. Several extensions to hill climbing have been proposed to overcome such problem such as Simulated Annealing, Tabu Search. In this paper, an extension version of hill climbing method has been proposed and called beta-hill climbing. A stochastic operator called beta-operator is utilized in hill climbing to control the balance between the exploration and exploitation during the search. The proposed method has been evaluated using IEEE-CEC2005 global optimization functions. The results show that the proposed method is a very efficient enhancement to the hill climbing providing powerful results when it compares with other advanced methods using the same global optimization functions.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available