<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

A New Model for Scheduling Operations in Modern Agricultural Processes

Medical Laboratories Techniques Department

Public Health Department, Faculty of Health Science

University of Pembangunan Nasional Veteran Jakarta

K.G. Razumovsky Moscow State University of technologies and management (the First Cossack University)

Kuban State Agrarian University named after I.T. Trubilin

Foundations of Computing and Decision Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"A New Model for Scheduling Operations in Modern Agricultural Processes"}

In recent years, the increase in population and the decrease in agricultural lands and water shortages have caused many problems for agriculture and farmers....

A New Model for Scheduling Operations in Modern Agricultural Processes

Published Online: Jul 09, 2022

Page range: 151 - 161

Received: Sep 12, 2021

Accepted: Mar 30, 2022

DOI: https://doi.org/10.2478/fcds-2022-0008

Keywords
Scheduling, Agricultural operations, Flexible workshop flow, Maximum completion time

© 2022 Zulhery Noer et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A New Model for Scheduling Operations in Modern Agricultural Processes

Published Online: Jul 09, 2022

Page range: 151 - 161

Received: Sep 12, 2021

Accepted: Mar 30, 2022

DOI: https://doi.org/10.2478/fcds-2022-0008

KeywordsScheduling, Agricultural operations, Flexible workshop flow, Maximum completion time

© 2022 Zulhery Noer et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Scheduling, Agricultural operations, Flexible workshop flow, Maximum completion time