Barber Optimization Algorithm: A New Human-Based Approach for Solving Optimization Problems

In this study, a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm (BaOA). Inspired by the human interactions between barbers and customers, BaOA captures two key processes: the customer’s selection of a hairstyle and the detailed refinement during the haircut. These processes are translated into a mathematical framework that forms the foundation of BaOA, consisting of two critical phases: exploration, representing the creative selection process, and exploitation, which focuses on refining details for optimization. The performance of BaOA is evaluated using 52 standard benchmark functions, including unimodal, high-dimensional multimodal, fixed-dimensional multimodal, and the Congress on Evolutionary Computation (CEC) 2017 test suite. This comprehensive assessment highlights BaOA’s ability to balance exploration and exploitation effectively, resulting in high-quality solutions. A comparative analysis against twelve widely known metaheuristic algorithms further demonstrates BaOA’s superior performance, as it consistently delivers better results across most benchmark functions. To validate its real-world applicability, BaOA is tested on four engineering design problems, illustrating its capability to address practical challenges with remarkable efficiency. The results confirm BaOA’s versatility and reliability as an optimization tool. This study not only introduces an innovative algorithm but also establishes its effectiveness in solving complex problems, providing a foundation for future research and applications in diverse scientific and engineering domains.