Research on the geometric model of Bentauron based on simulated annealing algorithm
DOI:
https://doi.org/10.54097/tw332a77Keywords:
Equidistant spiral equation, simulated annealing algorithm, particle swarm optimization algorithm, random seed, and iterative algorithm.Abstract
Based on the background of the traditional folk culture activity "Bench Dragon", this paper presents mathematical modeling and optimization analysis for the marching and turning of the dragon dance team on a specific path. Firstly, this paper determines the velocity and position distribution of each bench under the condition of constant faucet speed by helix equation. Aiming at the problem of the faucet entering the turning space smoothly, this paper determines the minimum pitch which satisfies the space limitation by mathematical derivation and iterative algorithm. In order to further optimize the turning path, the optimal turning path is obtained by combining the simulated annealing algorithm and the random seed method, and the tangency between the turning curve and the spiral path is ensured. Finally, through the method of dichotomy and particle swarm optimization, the paper finds the optimal solution that the maximum traveling speed of the leader does not exceed 2 m/s, which ensures the speed coordination and safety of the whole team. The optimization scheme proposed in this paper not only ensures the smooth entry and exit of the dragon dance team in the complex path, but also improves the appreciation and practicability of the performance.
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[1] Morshedin H M, Sadjadi J S, Amiri B, et al. Competitive pricing and seed node selection in a two-echelon supply chain [J]. Operations Research Perspectives, 2024, 13: 100314.
[2] A. W A, S. A J. Applicability of GLI 2012 spirometry equation among preschool aged Jordanian [J]. Respiratory Medicine, 2021, 182: 106397.
[3] Putra A L, Köstler M, Grundwürmer M, et al. State estimation of a biogas plant based on spectral analysis using a combination of machine learning and metaheuristic algorithms [J]. Applied Energy, 2024, 377: 124447.
[4] Copple R. The Fallacy of Unambiguous Warning [J]. Parameters, 2024, 54(3): 50.
[5] Mallaiah M, Rama Rao K, Venkateswarlu C. A simulated annealing optimization algorithm based nonlinear model predictive control strategy with application [J]. Evolving Systems, 2021, 12(1): 225-231.
[6] Chernov A, Lê T. Analytic and Gevrey class regularity for parametric elliptic eigenvalue problems and applications [J]. SIAM Journal on Numerical Analysis, 2024, 62(4): 1874-1900.
[7] Lin H, Yang X. Dichotomy algorithm for solving weighted min-max programming problem with addition-min fuzzy relation inequalities constraint [J]. Computers & Industrial Engineering, 2020, 146: 106537.
[8] Han F, Chen W T, Ling Q H, et al. Multi-objective particle swarm optimization with adaptive strategies for feature selection [J]. Swarm and Evolutionary Computation, 2021, 62: 100847.
[9] Gad a G. Particle swarm optimization algorithm and its applications: a systematic review [J]. Archives of computational methods in engineering, 2022, 29(5): 2531-2561.
[10] Al-Azzawi A, Stadler P, Kong H, et al. Length Modelling of Spiral Superficial Soft Strain Sensors Using Geodesics and Covering Spaces[J]. Robotics, 2023, 12(6): 164.
[11] Zhao Liqun. A preliminary discussion on recursive calculation method and recursive algorithm from the perspective of computational thinking [J]. Digital Technology and Application, 2002, 40(07): 140-143.
[12] Zhao J, Liu X, Wang S, et al. Review of Design and Control Optimization of Axial Flux PMSM in Renewable-energy Applications[J]. Chinese Journal of Mechanical Engineering, 2023, 36(1): 45.
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