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000857606 24500 $$aOpen Problems in Optimization and Data Analysis /$$cedited by Panos M. Pardalos, Athanasios Migdalas.
000857606 264_1 $$aCham :$$bSpringer International Publishing :$$bImprint: Springer,$$c2018.
000857606 300__ $$a1 online resource (xix, 330 pages) :$$billustrations.
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000857606 4901_ $$aSpringer Optimization and Its Applications,$$x1931-6828 ;$$v141
000857606 5050_ $$aChapter 1- Social Influence-based Optimization Problems -- Chapter 2- New Statistical Robust Estimators, Open Problems -- Chapter 3- Optimal Location Problems for Electric Vehicles Charging Stations: Models and Challenges -- Chapter 4- Supply and Demand Selection Problems in Supply Chain Planning -- Chapter 5- Open problems in green supply chain modelingband optimization with carbon emission targets -- Chapter 6- Variants and Formulations of the Vehicle Routing Problem -- Chapter 7- New MIP model for Multiprocessor Scheduling Problem with Communication Delays -- Chapter 8- On Optimization Problems in Urban Transport -- Chapter 9- Some aspects of the Stackelberg Leader/Follower Model -- Chapter 10- Open research areas in distance geometry -- Chapter 11- A Circle Packing Problem and its Connection to Malfatti's Problem -- Chapter 12- Review of basic local searches for solving the Minimum sum-of-squares clustering problem -- Chapter 13- On the Design of Metaheuristics-based Algorithm Portfolios -- Chapter 14- Integral Simplex Methods for the Set Partitioning Problem: Globalization and Anti-Cycling -- Chapter 15- Open problems on Benders Decomposition Algorithm -- Chapter 16- An Example of Nondecomposition in Data Fitting by Piecewise Monotonic Divided Differences of Order Higher than Two.
000857606 506__ $$aAccess limited to authorized users.
000857606 520__ $$aComputational 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. 
000857606 650_0 $$aMathematical optimization.
000857606 650_0 $$aProduction management.
000857606 650_0 $$aSoftware engineering.
000857606 650_0 $$aComputer science$$xMathematics.
000857606 7001_ $$aPardalos, Panos M.$$eeditor.
000857606 7001_ $$aMigdalas, Athanasios.$$eeditor.
000857606 77608 $$iPrint version: $$z9783319991412
000857606 830_0 $$aSpringer optimization and its applications ;$$v141.
000857606 852__ $$bebk
000857606 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-99142-9$$zOnline Access$$91397441.1
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