现代农业生产过程调度操作的一种新模型

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Foundations of Computing and Decision Sciences Pub Date : 2022-06-01 DOI:10.2478/fcds-2022-0008
Zulhery Noer, M. Elveny, A. Jalil, A. H. Iswanto, Samaher Al-Janabi, A. Alkaim, G. Mullagulova, Natalia Nikolaeva, R. Shichiyakh
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引用次数: 0

摘要

近年来,人口的增长和农业用地的减少以及水资源的短缺给农业和农民带来了许多问题。这就是日程安排对农民如此重要的原因。因此,实施一个最优的时间表将导致更好地利用农业用地,减少农业用水,提高农产品的效率和质量。本文研究了农产品收获的调度问题。在这个问题中,有n个农业用地,在每个土地上,m个农业作业由许多具有不同特征的机器执行。将该问题建模为一个柔性车间流程环境下以最小化农用地最大完工时间为目标的调度问题。利用Gams软件对一个整数线性数进行编程,解决了这一问题。结果表明,所提出的数学模型仅能解决中小型问题,并且由于问题的Hard-NP性质,大型软件无法实现最优解。
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A New Model for Scheduling Operations in Modern Agricultural Processes
Abstract In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers. That is why scheduling is so important for farmers. Therefore, the implementation of an optimal schedule will lead to better use of agricultural land, reduce water consumption in agriculture, increase efficiency and quality of agricultural products. In this research, a scheduling problem for harvesting agricultural products has been investigated. In this problem, there are n number of agricultural lands that in each land m agricultural operations are performed by a number of machines that have different characteristics. This problem is modeled as a scheduling problem in a flexible workshop flow environment that aims to minimize the maximum completion time of agricultural land. The problem is solved by programming an integer linear number using Gams software. The results show that the proposed mathematical model is only capable of solving small and medium-sized problems, and due to the Hard-NP nature of the problem, large-scale software is not able to achieve the optimal solution.
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来源期刊
Foundations of Computing and Decision Sciences
Foundations of Computing and Decision Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.20
自引率
9.10%
发文量
16
审稿时长
29 weeks
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