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基于智能优化算法的渔业资源管理模型的优化脉冲控制研究
Research on Optimal Impulse Control of Fishery Resource Management Model Based on Intelligent Optimization Algorithm

DOI: 10.12677/aam.2024.136275, PP. 2869-2879

Keywords: 脉冲模型,优化算法,渔业捕捞,最优控制
Impulse Model
, Optimization Algorithm, Fishery Capture, Optimal Control

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Abstract:

本文建立了一类渔业脉冲捕捞控制模型。考虑模型会发生更符合现实情况的多次脉冲捕捞情况,引入使得鱼群可持续发展的循环指标为优化目标,将智能优化算法与渔业捕捞脉冲控制模型相结合,利用不同优化算法对模型进行优化分析,得出了对模型适应度最高的算法。最后通过数值模拟,得出了在不同脉冲次数下的最优脉冲控制策略。
In this paper, we develop a model of impulse catch control in a fishery. Considering that the model will have multiple pulse fishing more in line with the reality, the cycle index that makes the sustainable development of fish stocks is introduced as the optimization goal, the intelligent optimization algorithm is combined with the fishery capture pulse control model, and different optimization algorithms are used to optimize and analyze the model, and the algorithm with the highest fitness for the model is obtained. Finally, through numerical simulation, the optimal pulse control strategy under different pulse times is obtained.

References

[1]  张凤琴. 生物数学发展概述[J]. 运城学院学报, 2005, 23(5): 1-3.
[2]  Milman, V.D. and Myshkis, A.D. (1960) On the Stability of Motion in the Presence of Impulses. Sibirskii Matematicheskii Zhurnal, 1, 233-237.
[3]  陈兰荪, 孟新柱, 焦建军. 生物动力学[M]. 北京: 科学出版社, 2009.
[4]  陈兰荪, 王东达. 数学, 物理学与生态学的结合——种群动力学模型[J]. 物理, 1994, 23(7): 408-413.
[5]  郭红建, 叶凯莉. 一类带有成比例收获和禁渔期的单种群渔业模型[J]. 信阳师范学院学报(自然科学版), 2013, 26(4): 485-488.
[6]  赵立纯, 张庆灵, 杨启昌. Logistic脉冲系统的最优脉冲控制[J]. 系统工程理论与实践, 2003, 23(9): 41-47+55.
[7]  Blaquiere, A. (1977) Differential Games with Piecewise Continuous Trajectories. In: Hagedorn, P., Knobloch, H.W. and Olsder, G.J., Eds., Differential Games and Applications. Lecture Notes in Control and Information Sciences, Vol. 3, Springer, 34-66.
https://doi.org/10.1007/BFb0009063
[8]  刘贤波, 窦家维. 脉冲微分系统的数值模拟与可视化[J]. 科学技术与工程, 2011, 11(28): 6785-6790+6801.
[9]  张晶晶. 基于改进粒子群算法求解常微分方程定解问题[D]: [硕士学位论文]. 哈尔滨: 哈尔滨工业大学, 2018.
[10]  黄光球, 陆秋琴. 具脉冲出生和季节性捕杀的种群系统优化算法[J]. 计算机科学与探索, 2021, 15(10): 2002-2014.
[11]  孙靖, 查明明. 关于在“最优化方法”中引入智能优化算法的思考[J]. 科教文汇(上旬刊), 2018(28): 47-48.
[12]  侯祥林, 钱颖, 吴海涛. 非线性常微分方程边值问题的最优化算法[J]. 工程数学学报, 2010, 27(4): 663-668.
[13]  王晓翠. 基于遗传算法的微分方程求解问题的研究[D]: [硕士学位论文]. 天津: 河北工业大学, 2007.
[14]  Verma, S.K., Yadav, S. and Nagar, S.K. (2017) Optimization of Fractional Order PID Controller Using Grey Wolf Optimizer. Journal of Control, Automation and Electrical Systems, 28, 314-322.
https://doi.org/10.1007/s40313-017-0305-3
[15]  杨维, 李歧强. 粒子群优化算法综述[J]. 中国工程科学, 2004, 6(5): 87-94.
[16]  席裕庚, 柴天佑, 恽为民. 遗传算法综述[J]. 控制理论与应用, 1996, 13(6): 697-708.
[17]  Faramarzi, A., Heidarinejad, M., Mirjalili, S., et al. (2020) Marine Predators Algorithm: A Nature-Inspired Metaheuristic. Expert Systems with Applications, 152, Article 113377.
https://doi.org/10.1016/j.eswa.2020.113377

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