Grasshopper Optimisation Algorithm: Theory and application

Abstract

This paper proposes an optimisation algorithm called Grasshopper Optimisation Algorithm (GOA) and applies it to a challenging problem in structural optimisation. The proposed algorithm mathematically models and mimics the behaviour of grasshopper swarms in nature for solving optimisation problems. The GOA algorithm is first benchmarked on a set of test problems including CEC2005 to test and verify its performance qualitatively and quantitatively. It is then employed to find the optimal shape for a 52-bar truss, 3-bar truss, and cantilever beam to demonstrate its applicability. The results show that the proposed algorithm is able to provide superior results compared to well-known and recent algorithms in the literature. The results of the real applications also prove the merits of GOA in solving real problems with unknown search spaces.

Data Clustering with Grasshopper Optimization Algorithm

“…, as noted in [3], linearly decreases the space that the grasshoppers should explore and exploit. Finally function s defines the strength of social forces, and was established by creators of the algorithm as:…”

“…Grasshopper Optimization Algorithm claims to be inspired by the social behavior of grasshoppers -insects of Orthoptera order (suborder Caelifera) [3]. Each member of the swarm constitutes a single insect located in search space S and moving within its bounds.…”

“…Grasshopper Optimization Algorithm (GOA) is an optimization technique introduced by Saremi, Mirjalili and Lewis in 2017 [3]. It includes both social interaction between ordinary agents (grasshoppers) and the attraction of the best individual.…”

Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms

“…Grasshopper Optimisation Algorithm (GOA) [16] is a recently proposed naturally inspired algorithm, which is based on one of the largest swarms of all creatures. As grasshoppers are herbivores, they cause severe damage to crops.…”

“…CSA mimics the behavior of crow to store their excess food in hiding places and retrieve it when it is needed. Similarly, Ant Lion Optimizer Algorithm [15] and Grasshopper Optimisation Algorithm [16] are also a good example of social mimicry of the natural swarms.…”