Enhancing grasshopper optimization algorithm (GOA) with levy flight for engineering applications

The grasshopper optimization algorithm (GOA) is a meta-heuristic algorithm proposed in 2017 mimics the biological behavior of grasshopper swarms seeking food sources in nature for solving optimization problems. Nonetheless, some shortcomings exist in the origin GOA, and GOA global search ability is...

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Bibliographic Details
Published in:Scientific reports 2023-01, Vol.13 (1), p.124-49, Article 124
Main Authors: Wu, Lei, Wu, Jiawei, Wang, Tengbin
Format: Article
Language:English
Subjects:
639/166/986
639/166/988
Algorithms
Animals
Exploitation
Exploration
Flight
Food sources
Grasshoppers
Heuristic
Heuristics
Humanities and Social Sciences
multidisciplinary
Optimization algorithms
Problem Solving
Science
Science (multidisciplinary)
Statistical analysis
Swarming behavior
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Summary:The grasshopper optimization algorithm (GOA) is a meta-heuristic algorithm proposed in 2017 mimics the biological behavior of grasshopper swarms seeking food sources in nature for solving optimization problems. Nonetheless, some shortcomings exist in the origin GOA, and GOA global search ability is more or less insufficient and precision also needs to be further improved. Although there are many different GOA variants in the literature, the problem of inefficient and rough precision has still emerged in GOA variants. Aiming at these deficiencies, this paper develops an improved version of GOA with Levy Flight mechanism called LFGOA to alleviate the shortcomings of the origin GOA. The LFGOA algorithm achieved a more suitable balance between exploitation and exploration during searching for the most promising region. The performance of LFGOA is tested using 23 mathematical benchmark functions in comparison with the eight well-known meta-heuristic algorithms and seven real-world engineering problems. The statistical analysis and experimental results show the efficiency of LFGOA. According to obtained results, it is possible to say that the LFGOA algorithm can be a potential alternative in the solution of meta-heuristic optimization problems as it has high exploration and exploitation capabilities.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-022-27144-4