This study focuses on the use of genetic algorithms to optimize control parameters in two potential strategies called mechanical and chemical control, for mitigating the spread of Huanglongbing (HLB) in citrus orchards. By developing a two-orchard model that incorporates the dispersal of the Asian Citrus Psyllid (ACP), the cost functions and objective function are explored to assess the effectiveness of the proposed control strategies. The mobility of ACP is also taken into account to capture the disease dynamics more realistically. Additionally, a mathematical expression for the global reproduction number ($R_{0}$) is derived, allowing for sensitivity analysis of the model parameters when ACP mobility is present. Furthermore, we mathematically express the cost function and efficiency of the strategy in terms of the final size and individual $R_{0}$ of each patch (i.e., when ACP mobility is absent). The results obtained through the genetic algorithms reveal optimal parameters for each control strategy, providing valuable insights for decision-making in implementing effective control measures against HLB in citrus orchards. This study highlights the importance of optimizing control parameters in disease management in agriculture and provides a solid foundation for future research in developing disease control strategies based on genetic algorithms.

翻译：本研究聚焦于利用遗传算法优化两种潜在控制策略（即机械控制与化学控制）中的控制参数，以减缓柑橘黄龙病在果园中的传播。通过构建纳入亚洲柑橘木虱扩散行为的双果园模型，我们探讨了成本函数与目标函数，以评估所提出控制策略的有效性。同时，为更真实地反映疾病动态，模型考虑了木虱的迁移能力。此外，推导出全局再生数（$R_{0}$）的数学表达式，从而可在存在木虱迁移的情况下对模型参数进行敏感性分析。进一步地，我们基于每个子区域的最终规模与局部$R_{0}$（即无木虱迁移时）给出了策略成本函数与效率的数学表达。遗传算法所得结果揭示了每种控制策略的最优参数，为制定针对柑橘黄龙病的有效防控措施提供了重要决策依据。本研究凸显了优化农业病害管理中控制参数的重要性，并为未来基于遗传算法开发病害控制策略的研究奠定了坚实基础。