04578nam a22005655i 4500 978-3-031-49740-7 DE-He213 20251030111750.0 cr nn 008mamaa 240328s2024 sz | s |||| 0|eng d 9783031497407 978-3-031-49740-7 10.1007/978-3-031-49740-7 doi T57.6-.97 KJT bicssc KJMD bicssc BUS049000 bisacsh KJT thema KJMD thema Optimization Under Uncertainty in Sustainable Agriculture and Agrifood Industry [electronic resource] / edited by Víctor M. Albornoz, Alejandro Mac Cawley, Lluis M. Plà-Aragonés. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. X, 212 p. 67 illus., 54 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda 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. Operations research. 57943 Agriculture Economic aspects. Management science. 57941 Operations Research and Decision Theory. 67143 Agricultural Economics. Operations Research, Management Science. 65527 Albornoz, Víctor M. editor. edt http://id.loc.gov/vocabulary/relators/edt 74174 Mac Cawley, Alejandro. editor. edt http://id.loc.gov/vocabulary/relators/edt 74175 Plà-Aragonés, Lluis M. editor. edt http://id.loc.gov/vocabulary/relators/edt 74176 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031497391 Printed edition: 9783031497414 Printed edition: 9783031497421 https://doi.org/10.1007/978-3-031-49740-7 ZDB-2-BUM ZDB-2-SXBM 58731 58731