Optimized Fixed-Time Synergetic Controller via a modified Salp Swarm Algorithm for Acute and Chronic HBV Transmission System

Mendel Pub Date : 2023-12-20 DOI:10.13164/mendel.2023.2.191
Saadi Achour, Khalil Mokhtari, Abdelaziz Rahmoune, Fares Yazid
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Abstract

In this paper, we propose a Salp Swarm Algorithm (SSA) Optimized Fixed-Time Synergetic Control (FTSC) strategy for the spread of hepatitis B infection. The utilization of the SSA optimization algorithm for optimizing the Synergetic Control (SC) fraction parameters presents a non-trivial challenge due to the restriction that only odd numbers can be used for the fractional power. Therefore, an enhanced and adapted version of the SSA algorithm is proposed to effectively address this specific scenario. Our strategic approach centers on the reduction of susceptible, acutely infected, and chronically infected individuals by employing control parameters like isolation, treatment, and vaccination. The objective is to drive these target state variables to their smallest values in a fixed-time, thereby effectively controlling the epidemic. We support our proposal with numerical simulations to demonstrate the feasibility and effectiveness of the control strategy. A comparison is conducted between FTSC and SC in scenarios with and without optimization. The results indicated that FTSC holds a distinct advantage, consistently demonstrating significant progress, with up to 30\% reduction in the total convergence time to zero, outperforming SC in each case.
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通过改进的 Salp Swarm 算法优化急性和慢性乙型肝炎病毒传播系统的固定时间协同控制器
在本文中,我们提出了一种针对乙型肝炎感染传播的 Salp Swarm 算法(SSA)优化固定时间协同控制(FTSC)策略。由于分数幂只能使用奇数,因此利用 SSA 优化算法来优化协同控制(SC)分数参数是一项艰巨的挑战。因此,我们提出了一种经过改进和调整的 SSA 算法,以有效解决这一特定问题。我们的战略方法主要是通过采用隔离、治疗和接种疫苗等控制参数来减少易感者、急性感染者和慢性感染者。我们的目标是在固定时间内将这些目标状态变量驱动到最小值,从而有效控制疫情。我们通过数值模拟来证明控制策略的可行性和有效性。在有优化和无优化的情况下,对 FTSC 和 SC 进行了比较。结果表明,FTSC 具有明显的优势,始终保持着显著的进步,总收敛到零的时间最多缩短了 30%,在每种情况下都优于 SC。
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来源期刊
Mendel
Mendel Decision Sciences-Decision Sciences (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
7
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