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Continent-wide planning of seed production: mathematical model and industrial application
File | Description | Size | Format | |
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Continent-wide planning of seed production mathematical model and industrial application_1213.pdf | Accepted version | 992.83 kB | Adobe PDF | View/Open |
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 |