The GBO Algorithm: A Novel Metaheuristic Optimization Algorithm
The Gradient-based Optimizer (GBO) is an optimization algorithm inspired by the Newton’s method. It is a metaheuristic algorithm that provides solutions to complex real-world engineering problems. The GBO uses two main operators, including the Gradient Search Rule (GSR) and Local Escaping Operator (LEO) to explore the search space. The GSR employs the gradient-based method to enhance the exploration tendency and accelerate the convergence rate, while the LEO enables the GBO to escape from local optima.
How does the GBO Algorithm Work?
The GBO algorithm starts with a set of vectors that explore the search space. The GSR and LEO operators work alongside the vector set. The GSR operator enhances the algorithm's exploration tendency by accelerating the convergence rate to achieve better positions in the search space. The LEO operator helps the algorithm to escape from local optima effectively. These two operators work together to provide a balance between exploration and exploitation.
In the first phase of evaluating the GBO, the algorithm's performance was assessed on 28 mathematical test functions. This test indicated that the GBO provides a superior solution to the optimization problem. Furthermore, the GBO algorithm was compared with five existing optimization algorithms, proving that the GBO yielded very promising results due to its enhanced capabilities of exploration, exploitation, convergence, and effective avoidance of local optima.
The second phase demonstrated the superior performance of the GBO algorithm in solving complex real-world engineering problems. These problems are extraordinarily complex, and few existing algorithms can solve them efficiently. Results indicate that the GBO algorithm effectively navigates the complex search space to provide an optimal solution.
Benefits of the GBO Algorithm
The GBO algorithm provides several benefits to engineers and scientists. One significant advantage of the GBO algorithm is that it can solve complex real-world engineering problems efficiently. Other benefits of the GBO algorithm include:
- Enhanced exploration tendency and convergence rate.
- Efficient avoidance of local optima.
- Efficient use of computational resources.
- Publicly available source codes to ensure ease of implementation.
As a result of these benefits, the GBO algorithm has become a popular optimization algorithm in engineering and scientific applications.
The GBO algorithm is a novel metaheuristic optimization algorithm that provides an efficient solution to complex real-world engineering problems. Using the GSR and LEO operators, the algorithm provides a balance between exploration and exploitation to achieve better solutions. The algorithm's benefits include enhanced exploration tendency, efficient use of computational resources, and publicly available source codes.
As a result of its promising results in various test functions and engineering applications, the GBO algorithm proves to be a valuable optimization tool for engineers and scientists seeking to solve complex real-world engineering problems.
