Border Collie Optimization

Title

Border Collie Optimization

Creator

Dutta T.; Bhattacharyya S.; Dey S.; Platos J.

Description

In recent times, several metaheuristic algorithms have been proposed for solving real world optimization problems. In this paper, a new metaheuristic algorithm, called the Border Collie Optimization is introduced. The algorithm is developed by mimicking the sheep herding styles of Border Collie dogs. The Border Collie's unique herding style from the front as well as from the sides is adopted successfully in this paper. In this algorithm, the entire population is divided into two parts viz., dogs and sheep. This is done to equally focus on both exploration and exploitation of the search space. The Border Collie utilizes a predatory move called eyeing. This technique of the dogs is utilized to prevent the algorithm from getting stuck into local optima. A sensitivity analysis of the proposed algorithm has been carried out using the Sobol's sensitivity indices with the Sobol g-function for tuning of parameters. The proposed algorithm is applied on thirty-five benchmark functions. The proposed algorithm provides very competitive results, when compared with seven state-of-the-art algorithms like Ant Colony optimization, Differential algorithm, Genetic algorithm, Grey-wolf optimizer, Harris Hawk optimization, Particle Swarm optimization and Whale optimization algorithm. The performance of the proposed algorithm is analytically and visually tested by different methods to judge its supremacy. Finally, the statistical significance of the proposed algorithm is established by comparing it with other algorithms by employing Kruskal-Wallis test and Friedman test. 2013 IEEE.

Source

IEEE Access, Vol-8, pp. 109177-109197.

Date

2020-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Benchmark test functions; Border Collie optimization; Friedman test; Kruskal-Wallis test; metaheuristic; optimization; swarm intelligence

Coverage

Dutta T., Department of Computer Science and Engineering, University Institute of Technology, Burdwan, 713104, India; Bhattacharyya S., Department of Computer Science and Engineering, CHRIST, Deemed to Be University, Bengaluru, 560029, India; Dey S., Department of Computer Science, Sukanta Mahavidyalaya, Jalpaiguri, 735210, India; Platos J., Department of Computer Science, FEECS, VSB-Technical University of Ostrava, Ostrava, 70800, Czech Republic

Rights

All Open Access; Gold Open Access; Green Open Access

Relation

ISSN: 21693536

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1109/ACCESS.2020.2999540

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087330032&doi=10.1109%2fACCESS.2020.2999540&partnerID=40&md5=032469ae52626dbd629b5aadec388109