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Open problems in optimization and data analysis

Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Curr...

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Detalles Bibliográficos
Autores principales: Pardalos, Panos, Migdalas, Athanasios
Lenguaje:eng
Publicado: Springer 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-99142-9
http://cds.cern.ch/record/2650862
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author Pardalos, Panos
Migdalas, Athanasios
author_facet Pardalos, Panos
Migdalas, Athanasios
author_sort Pardalos, Panos
collection CERN
description Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016. .
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spelling cern-26508622021-04-21T18:38:47Zdoi:10.1007/978-3-319-99142-9http://cds.cern.ch/record/2650862engPardalos, PanosMigdalas, AthanasiosOpen problems in optimization and data analysisMathematical Physics and MathematicsComputational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016. .Springeroai:cds.cern.ch:26508622018
spellingShingle Mathematical Physics and Mathematics
Pardalos, Panos
Migdalas, Athanasios
Open problems in optimization and data analysis
title Open problems in optimization and data analysis
title_full Open problems in optimization and data analysis
title_fullStr Open problems in optimization and data analysis
title_full_unstemmed Open problems in optimization and data analysis
title_short Open problems in optimization and data analysis
title_sort open problems in optimization and data analysis
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-3-319-99142-9
http://cds.cern.ch/record/2650862
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