Open Problems in Optimization and Data Analysis

• Corporate Author: SpringerLink (Online service)
• Other Authors: Pardalos, Panos M. (Editor, http://id.loc.gov/vocabulary/relators/edt), Migdalas, Athanasios (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: Springer Optimization and Its Applications, 141
• Subjects: Mathematical optimization.; Production management.; Software engineering.; Computer mathematics.; Optimization.; Operations Management.; Software Engineering/Programming and Operating Systems.; Computational Mathematics and Numerical Analysis.
• Physical Description: XIX, 330 p. 43 illus., 24 illus. in color. online resource.
• ISBN: 9783319991429
• ISSN: 1931-6828 ;
• DOI: 10.1007/978-3-319-99142-9

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. .