An Efficient Grasshopper Optimization Algorithm Using Arithmetic Crossover for Global Optimization

This paper introduces an Improved Grasshopper Optimisation Algorithm (IGOA) in which the arithmetic crossover mechanism is integrated into the standard Grasshopper Optimisation Algorithm (GOA). The improvement aims to maintain a high level of global exploration, assure an effective balance between global and local search. The IGOA algorithm is tested initially with a benchmark test functions, to evaluate and illustrate its performance in terms of qualitative and quantitative aspects. To validate the proposed methodology, it is then used to determine the best design for a Cantilever Beam and Pressure Vessel design problems. The obtained results indicate that the proposed method outperforms the literature's well-known and recently published techniques. Finally, the IGOA algorithm proves its usability and usefulness when it comes to solving real-world engineering problems.