Modified grasshopper optimisation algorithm

Abstract

The grasshopper optimization algorithm (GOA) mimics the foraging behavior of grasshopper insects. It is one of the youngest and widespread algorithms for optimization. In GOA exploration and exploitation depends on coefficient c used in position update process. So as to improve balancing in exploration and exploitation this paper introduced modified coefficient c for fine tuning these to contradictory process while searching for optimum solution. The new value of c is decided adaptively and stimulated by hyperbolic function. The anticipated algorithm is named as modified GOA (mGOA) and tested over a standard set of benchmark problems. Outcomes proves that mGOA outperformed considered algorithm for more than 90% problems.