UPM Institutional Repository

Racoon optimization algorithm


Koohi, Sina Zangbari and Abdul Hamid, Nor Asilah Wati and Othman, Mohamed and Ibragimov, Gafurjan (2019) Racoon optimization algorithm. IEEE Access, 7. pp. 5383-5399. ISSN 2169-3536


Population-based meta-heuristic is a high-level method intended to provide sufficient solution for problems with incomplete information among a massive volume of solutions. However, it does not guarantee to attain global optimum in a reasonable time. To improve the time and accuracy of the coverage in the population-based meta-heuristic, this paper presents a novel algorithm called the Raccoon Optimization Algorithm (ROA). The ROA is inspired by the rummaging behaviours of real raccoons for food. Raccoons are successful animals because of their extraordinarily sensitive and dexterous paws and their ability to find solutions for foods and remember them for up to three years. These capabilities make raccoons expert problem solvers and allow them to purposefully seek optimum solutions. These behaviours exploited in the ROA to search the solution spaces of nonlinear continuous problems to find the global optimum with higher accuracy and lower time coverage. To evaluate the ROA’s ability in addressing complicated problems, it has been tested on several benchmark functions. The ROA is then compared with nine other well-known optimization algorithms. These experiments show that the ROA achieves higher accuracy with lower coverage time.

Download File

[img] Text (Abstract)
Racoon optimization algorithm.pdf

Download (56kB)

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
Faculty of Science
DOI Number: https://doi.org/10.1109/ACCESS.2018.2882568
Publisher: Institute of Electrical and Electronics Engineers
Keywords: Raccoon Optimization Algorithm (ROA); Non-linear continuous optimization problems; Structural Optimization; Evolutionary Algorithm; Meta-heuristic algorithm
Depositing User: Mr. Sazali Mohamad
Date Deposited: 17 Oct 2020 15:30
Last Modified: 17 Oct 2020 15:30
Altmetrics: http://www.altmetric.com/details.php?domain=psair.upmedu.my&doi=10.1109/ACCESS.2018.2882568
URI: http://psasir.upm.edu.my/id/eprint/81920
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item