The facility layout problem remains a central focus in operations research. Researchers have been exploring its complexity and seeking efficient solutions. Identifying optimal solutions for diverse facility layouts frequently presents considerable challenges, resulting in either formidable barriers or necessitating substantial effort to get a globally optimal solution promptly. Recent findings indicate that metaheuristic algorithms, including genetic algorithms and Cuckoo search, are effective for addressing the facility layout problem. Conversely, each possesses distinct advantages and downsides. This research integrates two distinct metaheuristic algorithms to develop a hybrid solution. Our implementation exhibits rapid convergence and identifies superior solutions.