Advances in Engineering Software· 2017Q1
Grasshopper Optimisation Algorithm: Theory and application
- 2,705citations
- Q1SCImago
- 2017year
Short summary
A new Grasshopper Optimisation Algorithm (GOA), inspired by grasshopper swarm behavior, outperforms existing algorithms on structural optimization problems like truss and beam design.
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Key points
- Introduces the Grasshopper Optimisation Algorithm (GOA) based on natural grasshopper swarm behavior.
- GOA was benchmarked on CEC2005 test problems, showing strong qualitative and quantitative performance.
- Applied GOA to optimize the shape of a 52-bar truss, 3-bar truss, and cantilever beam.
- GOA achieved superior results compared to existing algorithms in both benchmark tests and real-world applications.
AI-generated from the title and abstract; the full text is not read.
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.
The authors' abstract, as published at the source. Advances in Engineering Software, 2017 · DOI ↗
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Field: Computational Theory and Mathematics
Computational Theory and MathematicsComputer Science