XOR Binary Gravitational Search Algorithm

Khanesar, Mojtaba Ahmadieh; Branson, David

Abstract

In this paper, an XOR binary gravitational search algorithm is introduced. Gravitational search algorithms, a physics inspired optimization algorithm, have previously been successfully applied to different real-valued optimization problems. In their binary version, the definition of a velocity vector changes to probability of change in corresponding dimensions. However, analysis shows that existing velocity vector update equation for binary gravitational search algorithm do not direct the particle towards better particle in certain cases. To apply this algorithm to binary optimization problems we introduce an XOR operator in the acceleration term. After a mathematical comparison to existing binary gravitational search algorithms it is shown that the proposed modification complies more with the definition of change in each dimension. Extensive simulations are performed showing the superiority of the proposed algorithm over other existing algorithms such as binary particle swarm optimization and an existing version of binary gravitational search algorithm.

Citation

Khanesar, M. A., & Branson, D. (2019, October). XOR Binary Gravitational Search Algorithm. Presented at 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Bari, Italy

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
• Start Date: Oct 6, 2019
• End Date: Oct 9, 2019
• Acceptance Date: Jun 23, 2019
• Online Publication Date: Nov 28, 2019
• Publication Date: 2019-10
• Deposit Date: Jul 18, 2019
• Publicly Available Date: Jul 18, 2019
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 3269-3274
• Series ISSN: 2577-1655
• Book Title: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
• ISBN: 978-1-7281-4570-9
• DOI: https://doi.org/10.1109/smc.2019.8914607
• Public URL: https://nottingham-repository.worktribe.com/output/2318825
• Publisher URL: https://ieeexplore.ieee.org/document/8914607
• Related Public URLs: http://smc2019.org/index.html
• Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
• Contract Date: Jul 18, 2019