Optimal agricultural spreading scheduling through surrogate-based optimization and MINLP models
作者机构：Veolia Research and InnovationChemin de la digue–78603Maisons-LaffitteFrance
出 版 物：《Information Processing in Agriculture》 (农业信息处理（英文）)
年 卷 期：2021年第8卷第1期
页 面：159-172页
核心收录：
学科分类：120301[管理学-农业经济管理] 12[管理学] 1203[管理学-农林经济管理]
基 金：Many thanks to Bill Parton Robin Kelly and Melanie Hartmann at the University of Colorado for all the technical support provided on the Century model
主 题：Surrogate-based optimization Mixed-Integer-Nonlinear programming Smart agriculture Agricultural scheduling Compost amendments
摘 要：The most commonly used definition of climate smart agriculture(CSA)is provided by the Food and Agricultural Organisation of the United Nations,which defines CSA as“agriculture that sustainably increases productivity,enhances resilience,reduces/removes greenhouse gas where possible,and enhances achievement of national food security and development goals.In this definition,the principal goal of CSA is identified as food security and development,while productivity,adaptation,and mitigation are identified as the three interlinked pillars necessary for achieving this *** the context provided by the CSA,soils are seen as a lever to improve the carbon footprint of agriculture,namely through their role as carbon *** soils and in particular agricultural soils’content in soil organic carbon(SOC)in one of the measures enabling to improve the environmental impact of agricultural *** this context,composts can be seen as an important feedstock for sustainable *** support the development of organic amendment strategies enabling to increase soils’SOC content,this work proposes a novel methodology to optimize the monthly scheduling of composts and mineral fertilizers *** schedule proposed maximizes soil health-via improved SOC content-while ensuring optimal gross operating surplus from *** problem is subjected to certain operational,regulatory and soil-dynamics constraints which leads to a complex optimization problem and has to be solved in a relatively short time period for decision-making *** is a nonlinear optimization problem(NLP)which is based on a soil-simulation model from which the analytic functions are not explicitly available for the optimization *** and regulatory constraints are explicitly defined and integer and continuous variables are needed in the *** order to effectively solve it in a deterministic way,a novel surrogate-modeling approach for the objective functions and constra
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