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

Title: Continent-wide planning of seed production: mathematical model and industrial application
Authors: Zhu, Y
Shah, N
Carré, G
Lemaire, S
Gatignol, E
Piccione, PM
Item Type: Journal Article
Abstract: 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.
Issue Date: 15-Sep-2019
Date of Acceptance: 21-Jan-2019
URI: http://hdl.handle.net/10044/1/69607
DOI: 10.1007/s11081-019-09424-7
ISSN: 1389-4420
Publisher: Springer
Start Page: 881
End Page: 906
Journal / Book Title: Optimization and Engineering
Volume: 20
Issue: 3
Copyright Statement: © 2019 Springer-Verlag. The final publication is available at Springer via https://dx.doi.org/10.1007/s11081-019-09424-7
Keywords: Science & Technology
Technology
Physical Sciences
Engineering, Multidisciplinary
Operations Research & Management Science
Mathematics, Interdisciplinary Applications
Engineering
Mathematics
Seed supply chain planning
Stochastic optimization
Cost reduction
Land usage reduction
SUPPLY CHAIN
Operations Research
01 Mathematical Sciences
09 Engineering
Publication Status: Published
Online Publication Date: 2019-02-26
Appears in Collections:Chemical Engineering
Grantham Institute for Climate Change
Faculty of Natural Sciences
Faculty of Engineering