Improved Grasshopper Optimization Algorithm Using Crazy Factor

This paper presents the new improved grasshopper optimization algorithm using crazy factor (crazy-GOA). The crazy factor technique helps to make a sudden direction change in order to enhance the diversity while exploring the entire search space. This method is a blessing in most of the modified version of the algorithms to achieve the optimal solution with smaller number of iterations. This paper explains the utilization of such technique to achieve the global optimum very fast, and this is a prime requirement of most of the applications. The experimental result analysis is performed using unimodal as well as multimodal standard benchmark functions. For extra verification as well as validation, the new improved algorithm is compared with other popular intelligent algorithms. The test result projected by this modified algorithm is superior to other intelligent algorithms in addition to classical GOA.