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New Approach for Differential Harvest Problem: The model checking way

机译:差异收成问题的新方法:模型检验方法

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The development, in the last decades, of technologies for precision agriculture allows the acquisition of crop data with a high spatial resolution. This offers possibilities for innovative control and raises new logistics issues that may be solved using discrete event models. In vineyards, some technologies make it possible to define zones with different qualities of grapes and sort the grapes at harvest to make different vintages. In this context, the Differential Harvest Problem (DHP) consists in finding a trajectory of the harvesting machine in the field in order to obtain at least a given quantity of higher quality grapes and minimising working time. In available literature, the DHP has been solved using Constraint Programming. In this paper, we investigate if it is possible to solve the DHP using the Cost Optimal Reachability Analysis feature of a model-checking tool such as UppAal-CORA. A model named DHP PTA has been designed based on the priced timed automata formalism and the UppAal-CORA tool. The method made it possible to obtain the optimal trajectory of a harvesting machine for a vine plot composed of up to 12 rows. The study is based on real vineyard data.
机译:在过去的几十年中,精准农业技术的发展使得能够以高空间分辨率获取作物数据。这为创新控制提供了可能性,并引发了新的物流问题,可以使用离散事件模型解决这些问题。在葡萄园中,某些技术可以定义具有不同品质的葡萄的区域,并在收获时对葡萄进行​​分类以制成不同的年份。在这种情况下,差异收获问题(DHP)在于找到田间收割机的运行轨迹,以获得至少一定数量的更高品质的葡萄并最大程度地减少工作时间。在现有文献中,已经使用约束编程解决了DHP。在本文中,我们研究了是否可以使用模型检查工具(例如UppAal-CORA)的成本最佳可达性分析功能来解决DHP。根据定价的定时自动机形式和UppAal-CORA工具,设计了一个名为DHP PTA的模型。该方法可以为最多由12行组成的葡萄田获得收割机的最佳轨迹。该研究基于真实的葡萄园数据。

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