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Coverage planning for capacitated field operations, Part I: Task decomposition

机译：有限的现场操作的覆盖计划，第一部分：任务分解

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In certain field operations, such as fertilising, capacity restrictions lead to significant nonproductive in-field travelling and out-of-field transport, thereby reducing field efficiency and increasing operating costs. This indicates a potential benefit from improving the efficiency of capacitated operations by minimising the non-productive travelled elements. A prerequisite for the optimisation of a field operation is the identification of the activities which contribute to the reduction of the efficiency and the definition of the actions that take place during the operation. The objective of this paper was to identify the sources of non-productivity in capacitated field operations and decompose the operation to feasible driving actions. Based on the monitoring of operations and subsequent data analysis, the recorded driven paths were decomposed into four types of non-productive activities. The involved driving actions during the fertilising operation were then defined, and finally, the potential of minimising the contribution of each non-productive activity to the operation efficiency by the selection of appropriate driving actions, was quantified. This assessment revealed that the selection of a subsequent action, might on one hand decrease the contribution of a specific non-productive activity to the total non-working travelled distance, but on the other hand might increase this contribution of another activity. There is therefore a trade-off between the positive contribution to the overall efficiency between one activity and the negative contribution from another. This indicates that a targeted algorithmic optimisation method should be devised by searching for the optimal combination among the prescribed driving actions. (C) 2015 IAgrE. Published by Elsevier Ltd. All rights reserved.
机译：在某些田间作业中，例如施肥，能力限制导致大量非生产性的田间旅行和田间运输，从而降低了田间效率并增加了运营成本。这表明通过最大限度地减少非生产性行进要素，提高了有能力操作的效率，具有潜在的好处。优化现场作业的先决条件是识别有助于降低效率的活动，并定义作业期间发生的动作。本文的目的是确定有能力的野外作业的非生产力原因，并将该作业分解为可行的驾驶行为。基于对操作的监视和随后的数据分析，将记录的驱动路径分解为四种非生产性活动。然后定义了施肥过程中涉及的驾驶行为，最后，通过选择适当的驾驶行为，量化了将每种非生产性活动对运营效率的贡献最小化的潜力。该评估表明，选择后续措施，一方面可能会降低特定的非生产性活动对非工作行进总距离的贡献，但另一方面可能会增加另一项活动的这一贡献。因此，在一项活动对整体效率的正面贡献与另一项活动的负面贡献之间需要权衡。这表明应该通过在规定的驾驶行为之间搜索最佳组合来设计有针对性的算法优化方法。 （C）2015年。由Elsevier Ltd.出版。保留所有权利。

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