The NSGA-II Ministry of Industry and Information Technology (MOPSO) has also announced that it will launch a series of measures to curb the spread of the virus, including the NSGA-II Ministry of Industry and Information Technology (MOPSO).

Document Type : Original Article

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Abstract

Due to resource constraints in the agricultural sector, optimal management of agricultural activity scheduling plays an important role in increasing productivity and reducing resource waste. In this study, meta-heuristic algorithms have been used to optimize resource allocation with the aim of reducing the time required to perform agricultural processes. The research method is descriptive and the data have been analyzed using mathematical and modeling tools. To evaluate the performance of the proposed model, one-way analysis of variance test was used in Matlab software. The results of the model implementation showed that the MOPSO algorithm performs better than NSGA-II based on the MID index, while NSGA-II has provided more favorable performance in terms of the SNS criterion. The proposed heuristic model for allocating resources to agricultural activities has high efficiency and has been able to provide appropriate scheduling for the implementation of planting and harvesting operations. Based on the model output, the probability of performing these operations on time in the best time, semi-optimal time, and emergency time intervals for wheat, rapeseed, and barley crops has been evaluated as satisfactory.

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  • Receive Date: 05 March 2025
  • Revise Date: 08 June 2025
  • Accept Date: 25 June 2025

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