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文件名称：Multi-Verse Optimizer: a nature-inspired algorithm for global optimization.pdf
文件大小：1.65MB
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更新时间：2023-05-22 14:14:11
MVO算法
This paper proposes a novel nature-inspired
algorithm called Multi-Verse Optimizer (MVO). The main
inspirations of this algorithm are based on three concepts in
cosmology: white hole, black hole, and wormhole. The
mathematical models of these three concepts are developed
to perform exploration, exploitation, and local search, respectively.
The MVO algorithm is first benchmarked on 19
challenging test problems. It is then applied to five real
engineering problems to further confirm its performance.
To validate the results, MVO is compared with four wellknown
algorithms: Grey Wolf Optimizer, Particle Swarm
Optimization, Genetic Algorithm, and Gravitational Search
Algorithm. The results prove that the proposed algorithm is
able to provide very competitive results and outperforms
the best algorithms in the literature on the majority of the
test beds. The results of the real case studies also
demonstrate the potential of MVO in solving real problems
with unknown search spaces. Note that the source codes of
the proposed MVO algorithm are publicly available at
http://www.alimirjalili.com/MVO.html.