Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
Green optimization of agro-food supply chains: integrating straw returning and deep tillage into a mixed integer linear programming model. |
| Συγγραφείς: |
Fang, Ying1 (AUTHOR), Li, Jing1 (AUTHOR) 20220183@njupt.edu.cn, Chen, Jiyuan2 (AUTHOR) |
| Πηγή: |
Environment, Development & Sustainability. Oct2026, Vol. 28 Issue 10, p24369-24404. 36p. |
| Θεματικοί όροι: |
*Rice farming, *Grain trade, Mixed integer linear programming, Soil management, Greenhouse gases, Multi-objective optimization, Soil ripping |
| Περίληψη: |
In the rice–wheat rotation system, two types of grains share the same land and supply chain. To study the green optimization of this grain supply chain, it is necessary to fully consider the production decisions of wheat and rice. Based on existing agro-food supply chain models, this paper considers the impact of straw returning and deep tillage on crop yield and greenhouse gas (GHG) emissions, and constructs a bi-objective mixed integer linear programming model that includes economic and environmental benefits. The results of the cases indicate that deep tillage is required before wheat sowing, while rice cultivation does not require deep plowing. Rice straw needs to be returned to the field, while wheat straw is best used as animal feed. Combining the inventory and transportation strategies in the results, this study can give supply chain decision-makers 94.6% confidence in achieving the optimization goals of high profit and low GHG emissions. This paper expands the scope of the green optimization model for the agro-food supply chain and provides a new path for formulating more effective green strategies for agriculture. [ABSTRACT FROM AUTHOR] |
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