Optimization under uncertainty in sustainable agriculture and agrifood industry

Contributor(s):

Material type: Text

TextPublication details: Springer Cham 2024Description: x, 212 pISBN:

9783031497391

Subject(s):

Agrifood industry

DDC classification:

630 ALB

Summary: 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. (https://link.springer.com/book/10.1007/978-3-031-49740-7)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Public Policy & General Management	630 ALB (Browse shelf(Opens below))	1	Available		007873

Table of contents:
Front Matter
Pages i-x
Download chapter PDF
Wine Journey: A Methodology for Analysing Wine Shipping Route Based on Temperature and Risk
Max Garafulic, Alejandro F. Mac Cawley
Pages 1-27
Model for Estimating the Demand for Soybean Railway Transport in Brazil’s Logistic Corridors Under Competitive Conditions
Thiago Guilherme Péra, Abner Matheus João, José Vicente Caixeta Filho
Pages 29-34
Implementing a Decision Support System for Plant Variety Testing in the Czech Republic
David Hampel, Martin Tláskal, Jitka Janová
Pages 35-61
Agri-food Supply Chain: An Optimisation Approach for Waste Valorisation
João Pires-Ribeiro, Lourenço Cruz, Ana Barbosa-Póvoa
Pages 63-104
Managing Risk in Fresh Produce Planning Considering Price Variability, Yield Variability, and Regional Complementarity
Miguel Peinado-Guerrero, Omar Ahumada, Rodrigo Ulloa, Xaimarie Hernandez-Cruz, Grace Neal, Abhay Jayani et al.
Pages 105-134
In Silico Evaluation and Prediction of Pesticide Supported by Reproducible Evolutionary Workflows
Anderson Oliveira, Fabricio Firmino, Pedro Vieira Cruz, Jonice de Oliveira Sampaio, Sérgio Manuel Serra da Cruz
Pages 135-159
A Precision Agriculture Approach for a Crop Rotation Planning Problem with Adjacency Constraints
Víctor M. Albornoz, Gabriel E. Zamora
Pages 161-178
A System for Supporting Supplier and Cold Storage Selection in the Fresh Fruit Supply Chain
Wladimir E. Soto-Silva, Marcela C. González-Araya, Lluís M. Plà-Aragonés
Pages 179-212
(https://link.springer.com/book/10.1007/978-3-031-49740-7)

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.

(https://link.springer.com/book/10.1007/978-3-031-49740-7)

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