Open Problems in Optimization and Data Analysis: 141 (Springer Optimization and Its Applications, 141) - Tapa dura
Libro 133 de 176: Springer Optimization and Its Applications
Sinopsis
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
De la contraportada
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Open Problems in Optimization and Data Analysis (eng)
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Open Problems in Optimization and Data Analysis (Springer Optimization and Its Applications, 141)
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Open Problems in Optimization and Data Analysis
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ISBN 10: 3319991418
ISBN 13: 9783319991412
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 352 pp. Englisch. Nº de ref. del artículo: 9783319991412
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Open Problems in Optimization and Data Analysis
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Springer International Publishing, 2018
ISBN 10: 3319991418
ISBN 13: 9783319991412
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Overviews open problems in optimization, computational geometry, algorithms, logistics, data science, and statisticsPresents theoretical and practical techniquesBroadens understanding and significance of challenging and open prob. Nº de ref. del artículo: 234946356
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Open Problems in Optimization and Data Analysis: 141 (Springer Optimization and Its Applications)
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Open Problems in Optimization and Data Analysis: 141 (Springer Optimization and Its Applications)
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Open Problems in Optimization and Data Analysis: 141 (Springer Optimization and Its Applications)
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Open Problems in Optimization and Data Analysis
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Springer, Palgrave Macmillan Dez 2018, 2018
ISBN 10: 3319991418
ISBN 13: 9783319991412
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 352 pp. Englisch. Nº de ref. del artículo: 9783319991412
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Open Problems in Optimization and Data Analysis
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ISBN 10: 3319991418
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783319991412
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Open Problems in Optimization and Data Analysis
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