Abstract
Agricultural machinery rental is a new service form that uses big data in agriculture to improve the utilization rate of agricultural machinery and promote the development of the agricultural economy. To realize agricultural machinery scheduling optimization in cloud services, a dynamic artificial bee-ant colony algorithm (DABAA) is proposed to solve the above problem. First, to improve the practicability of the mathematical model in agricultural production, a dynamic coefficient is proposed. Then the mutation operation is combined with the artificial bee colony (ABC) algorithm to improve the algorithm. Then, iterative threshold adjustment and optimal fusion point evaluation are used to combine the ABC algorithm with the ant colony optimization (ACO) algorithm, which not only improves the search precision but also improves the running speed. Finally, two groups of comparison experiments are carried out, and the results show that the DABAA can obviously improve the running speed and accuracy of cloud services in agricultural machinery rental.
| Original language | English |
|---|---|
| Article number | 88 |
| Journal | Algorithms |
| Volume | 15 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
Keywords
- Agricultural machinery
- Ant colony optimization (ACO)
- Artificial bee colony (ABC)
- Big data
- Cloud service
- Max-min ant system (MMAS)
- Quality of service (QoS)
- Rental optimization
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