可持续农业的收获优化——以茶叶收获调度为例

IF 8.2 Q1 AGRICULTURE, MULTIDISCIPLINARY Artificial Intelligence in Agriculture Pub Date : 2023-10-12 DOI:10.1016/j.aiia.2023.10.001
Bedirhan Sarımehmet, Mehmet Pınarbaşı, Hacı Mehmet Alakaş, Tamer Eren
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引用次数: 0

摘要

为了确保农业的可持续性,需要解决许多优化问题。其中一个重要的问题是收获调度问题。在本研究中,讨论了茶叶的收获调度问题。茶叶收获问题包括通过考虑农民在购买地点和工厂产能下的配额来制定收获时间表。茶叶收割是与农民工厂合作进行的。工厂管理层对利用其资源很感兴趣。因此,在收获过程中应考虑工厂容量、购买地点容量和探险次数。当考察农民的一面时,可以看出农民的真正职业是不同的。在收获的日子里,农民往往无法从事他们的主要职业。在制定收获时间表时考虑农民的收获日偏好对农业的可持续性至关重要。提出了两种不同的数学模型来解决这个问题。第一种模型在因素和购买地点容量限制范围内,最大限度地减少了工厂车辆的每周考察次数。第二种模式最大限度地减少了探险次数,旨在尽可能符合农民的偏好。在一个有12个购买地点、988名农民和3392个十卡茶园的地区进行了样本应用。结果表明,农民对收割偏好的遵守率可以从52%提高到97%,这种情况不会影响工厂的考察次数。这一结果表明,考虑农民在收获日的偏好不会对工厂产生负面影响。相反,得出的结论是,这种情况增加了农业的可持续性和鼓励性。此外,结果表明,模型对解决该问题是有效的。
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Harvest optimization for sustainable agriculture: The case of tea harvest scheduling

To ensure sustainability in agriculture, many optimization problems need to be solved. An important one of them is harvest scheduling problem. In this study, the harvest scheduling problem for the tea is discussed. The tea harvest problem includes the creating a harvest schedule by considering the farmers' quotas under the purchase location and factory capacity. Tea harvesting is carried out in cooperation with the farmer - factory. Factory management is interested in using its resources. So, the factory capacity, purchase location capacities and number of expeditions should be considered during the harvesting process. When the farmer's side is examined, it is seen that the real professions of farmers are different. On harvest days, farmers often cannot attend to their primary professions. Considering the harvest day preferences of farmers in creating the harvest schedule are of great importance for sustainability in agriculture. Two different mathematical models are proposed to solve this problem. The first model minimizes the number of weekly expeditions of factory vehicles within the factor and purchase location capacity restrictions. The second model minimizes the number of expeditions and aims to comply with the preferences of the farmers as much as possible. A sample application was performed in a region with 12 purchase locations, 988 farmers, and 3392 decares of tea fields. The results show that the compliance rate of farmers to harvesting preferences could be increased from 52% to 97%, and this situation did not affect the number of expeditions of the factory. This result shows that considering the farmers' preferences on the harvest day will have no negative impact on the factory. On the contrary, it was concluded that this situation increases sustainability and encouragement in agriculture. Furthermore, the results show that models are effective for solving the problem.

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来源期刊
Artificial Intelligence in Agriculture
Artificial Intelligence in Agriculture Engineering-Engineering (miscellaneous)
CiteScore
21.60
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊最新文献
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