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Open Problems in Optimization and Data Analysis

Om 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. 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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  • Språk:
  • Engelska
  • ISBN:
  • 9783319991412
  • Format:
  • Inbunden
  • Sidor:
  • 330
  • Utgiven:
  • 17. december 2018
  • Utgåva:
  • 12018
  • Mått:
  • 155x235x0 mm.
  • Vikt:
  • 694 g.
  Fri leverans
Leveranstid: 2-4 veckor
Förväntad leverans: 28. januari 2025
Förlängd ångerrätt till 31. januari 2025
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Beskrivning av 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. 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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