1555. Optimization models and algorithms for sustainable crop planning and scheduling
Invited abstract in session TA-7: Scheduling models and algorithms II, stream Scheduling and Project Management.
Tuesday, 8:30-10:00Room: Clarendon GR.01
Authors (first author is the speaker)
| 1. | Paolo Detti
|
| Department of Information Engineering and Mathematics, University of Siena | |
| 2. | Mario Benini
|
| Department of Information Engineering and Mathematics, University of Siena | |
| 3. | Luca Nerozzi
|
| Department of Information Engineering and Mathematics , University of Siena |
Abstract
Sustainable agriculture is crucial for long-term food security and environmental health, addressing challenges such as resource depletion, biodiversity loss, and climate change. However, it also presents new challenges for farmers, who find long-term crop planning increasingly difficult due to constraints like resource management, environmental regulations, and climate variability. In this work, we present decision models and optimization algorithms designed to support farmers by solving multi-period crop rotation planning problems, with the objective of maximizing the profit, taking into account sustainability regulations and sustainable agronomic practices. In such problems, the rotation of different crop types over a plot of land affects the yield and the profit of each crop, and crop rotation benefits and rewards coming from sustainability regulations must be considered. We propose an arc-flow Integer Linear Programming model and a matheuristic algorithm, based on column generation, to efficiently solve the problem. An optimal dynamic programming algorithm for a special case and a complexity analysis of the pricing problems are also provided. An extensive experimental study using real-world data from Italian farms and the sustainability regulations of the European Union's Common Agricultural Policy is presented. The numerical results demonstrate the effectiveness of our proposed methods in optimizing crop rotation while ensuring compliance with sustainability constraints.
Keywords
- OR in Agriculture
- Mathematical Programming
- Scheduling
Status: accepted
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