Pests may lead to low crop productivity and profitability. Pesticides are commonly used to protect crops from pests. However, too much pesticide is not only associated with harmful effects to the environment but may also lead to sub-optimal pest management. The existing works focus on the vehicle routing problem for pesticide management without giving due consideration to finding the optimal time, amount, and area for pesticide application. To solve this issue, this paper takes an active stance and introduces demand management for pesticide using an active mass-spring suspension system. Moreover, using a controller based on model predictive control that uses the active demand management model, this paper efficiently solves the problem of finding the right time, amount and place for pesticide application in an agricultural field. A greedy algorithm is then proposed to solve the vehicle routing problem after identifying the optimal time, and place for pesticide application. The proposed solution minimizes the risk of pest infestation by considering pest risk prediction models. The simulation results show that the proposed technique can maximize the protection for crops against pests. Moreover, a performance analysis of the proposed technique shows that it has significantly lower computational complexity and can converge to the optimal solution at least 78% faster than existing techniques.

害虫可能导致农作物生产力和利润率下降。农药通常用于保护农作物免受害虫侵害。但是，过多的农药不仅与对环境的有害影响有关，而且还可能导致有害生物管理不力。现有的工作集中在农药管理的车辆路径问题上，而没有充分考虑寻找农药施用的最佳时间，数量和面积。为了解决这个问题，本文采取了积极的态度，并介绍了使用主动质量弹簧悬挂系统的农药需求管理。此外，使用基于模型预测控制的控制器，该控制器使用主动需求管理模型，有效地解决了在农业领域中寻找合适的农药施用时间，数量和地点的问题。然后提出了贪婪算法，以在确定最佳时间和农药施用地点后解决车辆路径问题。通过考虑有害生物风险预测模型，提出的解决方案将有害生物侵扰的风险降至最低。仿真结果表明，该技术可以最大程度地保护农作物免受害虫侵害。此外，对所提出技术的性能分析表明，它具有较低的计算复杂度，并且可以比现有技术快至少78％收敛到最佳解决方案。仿真结果表明，该技术可以最大程度地保护农作物免受害虫侵害。此外，对所提出技术的性能分析表明，它具有较低的计算复杂度，并且可以比现有技术快至少78％收敛到最佳解决方案。仿真结果表明，该技术可以最大程度地保护农作物免受害虫侵害。此外，对所提出技术的性能分析表明，它具有较低的计算复杂度，并且可以比现有技术快至少78％收敛到最佳解决方案。