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Optimization under uncertainty in sustainable agriculture and agrifood industry

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Optimization under uncertainty in sustainable agriculture and agrifood industryedited by Víctor M. Albornoz, Alejandro Mac Cawley, Lluis M. Plà-Aragonés.
其他作者:	Albornoz, Víctor M.
出版者:	Cham :Springer International Publishing :2024.
面頁冊數:	x, 212 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Sustainable agriculture.
電子資源:	https://doi.org/10.1007/978-3-031-49740-7
ISBN:	9783031497407$q(electronic bk.)

Optimization under uncertainty in sustainable agriculture and agrifood industry
Optimization under uncertainty in sustainable agriculture and agrifood industry[electronic resource] /edited by Víctor M. Albornoz, Alejandro Mac Cawley, Lluis M. Plà-Aragonés. - Cham :Springer International Publishing :2024. - x, 212 p. :ill. (some col.), digital ;24 cm.

Wine Journey: A methodology for analyzing wine shipping route based on temperature and Risk -- Model for estimating the demand for soybean railway transport in Brazil's logistic corridors under competitive conditions -- Implementing a decision support system for plant variety testing in the Czech Republic -- Agri-Food Supply Chain - An optimisation approach for waste valorization -- Managing risk in fresh produce planning considering price varia-bility, yield variability, and region-al complementarity -- In Silico Evaluation and Prediction of Pesticide Supported by Reproducible Evolutionary Workflows -- A precision agriculture approach for a crop rotation planning problem with adjacency constraints -- A System for Supporting Supplier and Cold Storage Selection in the Fresh Fruit Supply Chain.

This book explores optimization under uncertainty and related applications in agriculture, sustainable supply chains and the agrifood industry. Rapid changes in the primary sector are leading to more and more industrialized structures, which require optimization methods in order to cope with today's challenges. Addressing uncertainty in the agrifood industry may lead to more robust supply chain designs or to diversified risk. Sustainability requires interaction with the environmental or social sciences. This book bridges the gap between optimization theory, uncertainty, sustainability and primary-sector applications (mainly in the agriculture and food industry, but also fisheries, forestry and natural resources in general) Although it has been a major challenge for the operations research community, this urgently needed interdisciplinary collaboration is not adequately covered in most current curricula in applied mathematics, economics or (agronomic/industrial/forest) engineering. This book highlights research that can help fill this gap. The individual chapters cover applications of stochastic integer linear programming and multicriteria decision methods in agriculture. The topics addressed include uncertainty in areas such as the sugar cane industry, pig farming, and cold storage for perishable products. Large-scale sustainable food production is a growing concern; this book offers solutions to help meet global demand in agriculture by using and improving the methods of optimization theory and operations research.

ISBN: 9783031497407$q(electronic bk.)

Standard No.: 10.1007/978-3-031-49740-7doiSubjects--Topical Terms:

277356
Sustainable agriculture.

LC Class. No.: S494.5.S86

Dewey Class. No.: 630.2086

Optimization under uncertainty in sustainable agriculture and agrifood industry
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520 $a This book explores optimization under uncertainty and related applications in agriculture, sustainable supply chains and the agrifood industry. Rapid changes in the primary sector are leading to more and more industrialized structures, which require optimization methods in order to cope with today's challenges. Addressing uncertainty in the agrifood industry may lead to more robust supply chain designs or to diversified risk. Sustainability requires interaction with the environmental or social sciences. This book bridges the gap between optimization theory, uncertainty, sustainability and primary-sector applications (mainly in the agriculture and food industry, but also fisheries, forestry and natural resources in general) Although it has been a major challenge for the operations research community, this urgently needed interdisciplinary collaboration is not adequately covered in most current curricula in applied mathematics, economics or (agronomic/industrial/forest) engineering. This book highlights research that can help fill this gap. The individual chapters cover applications of stochastic integer linear programming and multicriteria decision methods in agriculture. The topics addressed include uncertainty in areas such as the sugar cane industry, pig farming, and cold storage for perishable products. Large-scale sustainable food production is a growing concern; this book offers solutions to help meet global demand in agriculture by using and improving the methods of optimization theory and operations research.
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