Continent-wide planning of seed production: mathematical model and industrial application

The seed supply chain is one of most sophisticated elements of the agricultural value chain with long lead times, fragmented structure and high levels of uncertainty. Since the seed industry has received less attention in research compared with other sectors in the agriculture industry, it has enorm...

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Bibliographic Details
Published in:Optimization and engineering 2019-09, Vol.20 (3), p.881-906
Main Authors: Zhu, Yanbin, Shah, Nilay, Carré, Gabriel, Lemaire, Simon, Gatignol, Erick, Piccione, Patrick M.
Format: Article
Language:English
Subjects:
Arable land
Control
Engineering
Environmental Management
Farms
Financial Engineering
Harvesting
Industrial applications
Land use management
Mathematical analysis
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Production planning
Regional planning
Research Article
Supply chains
Systems Theory
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Summary:The seed supply chain is one of most sophisticated elements of the agricultural value chain with long lead times, fragmented structure and high levels of uncertainty. Since the seed industry has received less attention in research compared with other sectors in the agriculture industry, it has enormous potential for improvement due to the lack of comprehensive mathematical optimization applications, increasing competition within the industry and decreasing spare arable land worldwide. All of the existing optimization applications in the seed supply chain have concerned land allocation at the farm level as well as regional level processing and distribution after harvesting. This research closes the gap between farm level planning and regional level distribution through optimization of seed production planning at a regional level, taking account of a number of complex constraints and practical preferences. Compared to a “business as usual” approach, the proposed application can save up to 16% of the total cost as well as 9% land usage and effectively mitigate major risks in the planning phase. The method is evaluated using Syngenta’s industrial case studies.
ISSN:1389-4420
1573-2924
DOI:10.1007/s11081-019-09424-7