Title: An improved binary Crow-JAYA optimisation system with various evolution operators, such as mutation for finding the max clique in the dens graph

Authors: Mohammad Al-Batah; Mohammad Ryiad Al-Eiadeh

Addresses: Faculty of Science and Information Technology, Department of Computer Science, Jadara University, Irbid, 21110, Jordan ' Faculty of Electrical and Computer Engineering, Department of Engineering and Technology, University of IUPUI, Indianapolis, 46202, USA

Abstract: The paper proposes an Improved Binary Cuckoo Search Algorithm-Binary Jaya Optimiser (IBCSA-BJO) with binary Jaya Optimiser (JO) to solve the max clique problem. This algorithm integrates opposition-based learning (OBL), transfer functions, Lévy flight, mutation, Xor, 1-point crossover, and the repairing method to enhance initial population diversity, improve searching capabilities, and avoid local optima traps. Transfer functions convert continuous values to binary, while the repairing method fixes infeasible solutions. Evaluations on benchmark problems demonstrate the effectiveness of IBCSA-BJO as a competitive alternative to state-of-the-art approaches.

Keywords: max clique problem; binary crow search algorithm; binary Jaya optimiser; evolutionary operator; OBL; opposition-based learning; transfer functions.

DOI: 10.1504/IJCSM.2024.139088

International Journal of Computing Science and Mathematics, 2024 Vol.19 No.4, pp.327 - 338

Received: 02 Feb 2023
Accepted: 01 Apr 2024
Published online: 12 Jun 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article