Author(s)

Kai Wang^*, HuanHuan Zou, Ming Fang

Affiliation(s)

The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang, China.

Corresponding Author

Kai Wang

ABSTRACT

In order to enrich the population diversity of the original marine predator algorithm (MPA), balance the phased exploration and development effect of the algorithm, and enhance the ability of leaping out of the local optimal solution, so as to improve the effect of solving engineering optimization problems, a multi-strategy developed marine predator algorithm (MSDMPA) is proposed. The algorithm first initializes the population through sine chaotic mapping and uses a phased position update mechanism with nonlinear convergence factor   to guide individual position updates. At the same time, the adaptive monotonically decreasing update strategy for step size control   is introduced. Finally, the algorithm is improved by combining the strategy of the Levy flight. The simulation experiment is based on 13 benchmark test functions to verify the effectiveness of various improvement strategies. The convergence analysis and Wilcoxon rank sum test are performed on the optimization results of the improved algorithm and the comparison algorithms, proving that MSDMPA has good optimization performance and robustness. Finally, MSDMPA is applied to the pressure vessel of a large hospital's liquid oxygen tank, further verifying its effectiveness and reliability in solving practical problem.

KEYWORDS

Marine predator algorithm; MPA; MSDMPA; Convergence factor; Monotonically decreasing; Pressure vessel

CITE THIS PAPER

Kai Wang, HuanHuan Zou, Ming Fang. A multi-strategy developed marine predator algorithm and its application in  pressure vessel. Journal of Computer Science and Electrical Engineering. 2024, 6(4): 39-52. DOI: https://doi.org/10.61784/jcsee3025.

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