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.