Grasshopper Optimisation Algorithm: Theory and application. (March 2017)

• Record Type: Journal Article
• Authors: Saremi, Shahrzad; Mirjalili, Seyedali; Lewis, Andrew
• Is Part Of: Advances in engineering software. Volume 105(2017)
• Page Start: 30
• Page End: 47
• Publication Date: 2017-03
• Subjects: Optimization -- Optimization techniques -- Heuristic algorithm -- Metaheuristics -- Constrained optimization -- Benchmark -- Algorithm; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2017.01.004
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: The Grasshopper Optimisation Algorithm inspired by grasshopper swarms is proposed. The GOA algorithm is benchmarked on challenging test functions. The results on the unimodal functions show the superior exploitation of GOA. The exploration ability of GOA is confirmed by the results on multimodal and composite functions. The results on structural design problems confirm the performance of GOA in practice. Abstract: This paper proposes an optimisation algorithm called Grasshopper Optimisation Algorithm (GOA) and applies it to challenging problems 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.