  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.
