TY - GEN AB - 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. AU - Pardalos, Panos M. AU - Migdalas, Athanasios. CN - QA402.5-402.6 DO - 10.1007/978-3-319-99142-9 DO - doi ID - 857606 KW - Mathematical optimization. KW - Production management. KW - Software engineering. KW - Computer science LK - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-99142-9 N2 - 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. SN - 9783319991429 SN - 3319991426 T1 - Open Problems in Optimization and Data Analysis / TI - Open Problems in Optimization and Data Analysis / UR - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-99142-9 VL - 141 ER -