Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services
With the development of the “Internet +” model and the sharing economy model, the “online car-hailing” operation model has promoted the emergence of “online-hailing agricultural machinery”. This new supply and demand model of agricultural machinery has brought greater convenience to the marketizatio...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/21/3933 |
| _version_ | 1797467393129185280 |
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| author | Li Ma Minghan Xin Yi-Jia Wang Yanjiao Zhang |
| author_facet | Li Ma Minghan Xin Yi-Jia Wang Yanjiao Zhang |
| author_sort | Li Ma |
| collection | DOAJ |
| description | With the development of the “Internet +” model and the sharing economy model, the “online car-hailing” operation model has promoted the emergence of “online-hailing agricultural machinery”. This new supply and demand model of agricultural machinery has brought greater convenience to the marketization of agricultural machinery services. However, although this approach has solved the use of some agricultural machinery resources, it has not yet formed a scientific and systematic scheduling model. Referring to the existing agricultural machinery scheduling modes and the actual demand of agricultural production, based on the idea of resource sharing, in this research, the soft and hard time windows were combined to carry out the research on the dynamic demand scheduling strategy of agricultural machinery. The main conclusions obtained include: (1) Based on the ideas of order resource sharing and agricultural machinery resource sharing, a general model of agricultural machinery scheduling that meet the dynamic needs was established, and a more scientific scheduling plan was proposed; (2) Based on the multi-population coevolutionary genetic algorithm, the dynamic scheduling scheme for shared agricultural machinery for on-demand farming services was obtained, which can reasonably insert the dynamic orders on the basis of the initial scheduling scheme, and realize the timely response to farmers’ operation demands; (3) By comparing with the actual production situation, the path cost and total operating cost were saved, thus the feasibility and effectiveness of the scheduling model were clarified. |
| first_indexed | 2024-03-09T18:53:00Z |
| format | Article |
| id | doaj.art-86b9c3feb5294d6ba8e13185893db678 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T18:53:00Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-86b9c3feb5294d6ba8e13185893db6782023-11-24T05:42:19ZengMDPI AGMathematics2227-73902022-10-011021393310.3390/math10213933Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming ServicesLi Ma0Minghan Xin1Yi-Jia Wang2Yanjiao Zhang3College of Engineering, Northeast Agricultural University, Harbin 150030, ChinaCollege of Engineering, Northeast Agricultural University, Harbin 150030, ChinaDepartment of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong 999077, ChinaBaoneng Automobile Group, Shenzhen 518000, ChinaWith the development of the “Internet +” model and the sharing economy model, the “online car-hailing” operation model has promoted the emergence of “online-hailing agricultural machinery”. This new supply and demand model of agricultural machinery has brought greater convenience to the marketization of agricultural machinery services. However, although this approach has solved the use of some agricultural machinery resources, it has not yet formed a scientific and systematic scheduling model. Referring to the existing agricultural machinery scheduling modes and the actual demand of agricultural production, based on the idea of resource sharing, in this research, the soft and hard time windows were combined to carry out the research on the dynamic demand scheduling strategy of agricultural machinery. The main conclusions obtained include: (1) Based on the ideas of order resource sharing and agricultural machinery resource sharing, a general model of agricultural machinery scheduling that meet the dynamic needs was established, and a more scientific scheduling plan was proposed; (2) Based on the multi-population coevolutionary genetic algorithm, the dynamic scheduling scheme for shared agricultural machinery for on-demand farming services was obtained, which can reasonably insert the dynamic orders on the basis of the initial scheduling scheme, and realize the timely response to farmers’ operation demands; (3) By comparing with the actual production situation, the path cost and total operating cost were saved, thus the feasibility and effectiveness of the scheduling model were clarified.https://www.mdpi.com/2227-7390/10/21/3933agricultural machinery schedulingonline-hailing agricultural machineryco-evolutionary genetic algorithmdynamic demand analysis |
| spellingShingle | Li Ma Minghan Xin Yi-Jia Wang Yanjiao Zhang Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services Mathematics agricultural machinery scheduling online-hailing agricultural machinery co-evolutionary genetic algorithm dynamic demand analysis |
| title | Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services |
| title_full | Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services |
| title_fullStr | Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services |
| title_full_unstemmed | Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services |
| title_short | Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services |
| title_sort | dynamic scheduling strategy for shared agricultural machinery for on demand farming services |
| topic | agricultural machinery scheduling online-hailing agricultural machinery co-evolutionary genetic algorithm dynamic demand analysis |
| url | https://www.mdpi.com/2227-7390/10/21/3933 |
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