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Open Problems in Optimization and Data Analysis

  • Book
  • © 2018

Overview

Editors:
  1. Panos M. Pardalos

    1. Industrial and Systems, Engineering Department, University of Florida, Center For Applied Optimization, Gainesville, USA

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  2. Athanasios Migdalas

    1. Industrial Logistics, ETS Institute, Lulea University of Technology, Norrbotten, Sweden

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    You can also search for this editor in PubMed   Google Scholar

  • Overviews open problems in optimization, computational geometry, algorithms, logistics, data science, and statistics
  • Presents theoretical and practical techniques
  • Broadens understanding and significance of challenging and open problems

Part of the book series: Springer Optimization and Its Applications (SOIA, volume 141)

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About this book

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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Table of contents (17 chapters)

  1. Front Matter

    Pages i-xix
    Download chapter PDF

  2. A Note on Open Problems and Challenges in Optimization Theory and Algorithms

    • A. Migdalas, P. M. Pardalos
    Pages 1-8

  3. Social Influence-Based Optimization Problems

    • Chao Li, Jing Yuan, Ding-Zhu Du
    Pages 9-22

  4. New Statistical Robust Estimators, Open Problems

    • George Zioutas, Chris Chatzinakos, Athanasios Migdalas
    Pages 23-47

  5. Optimal Location Problems for Electric Vehicles Charging Stations: Models and Challenges

    • A. Karakitsiou, A. Migdalas, P. M. Pardalos
    Pages 49-60

  6. Supply and Demand Selection Problems in Supply Chain Planning

    • Roshanak Mohammadivojdan, Joseph Geunes
    Pages 61-82

  7. Open Problems in Green Supply Chain Modeling and Optimization with Carbon Emission Targets

    • Konstantina Skouri, Angelo Sifaleras, Ioannis Konstantaras
    Pages 83-90

  8. Variants and Formulations of the Vehicle Routing Problem

    • Yannis Marinakis, Magdalene Marinaki, Athanasios Migdalas
    Pages 91-127

  9. New MIP model for Multiprocessor Scheduling Problem with Communication Delays

    • Abdessamad Ait El Cadi, Mustapha Ratli, Nenad Mladenović
    Pages 129-149

  10. On Optimization Problems in Urban Transport

    • Tran Duc Quynh, Nguyen Quang Thuan
    Pages 151-170

  11. Some Aspects of the Stackelberg Leader/Follower Model

    • L. Mallozzi, R. Messalli, S. Patrì, A. Sacco
    Pages 171-181

  12. Open Research Areas in Distance Geometry

    • Leo Liberti, Carlile Lavor
    Pages 183-223

  13. A Circle Packing Problem and Its Connection to Malfatti’s Problem

    • D. Munkhdalai, R. Enkhbat
    Pages 225-248

  14. Review of Basic Local Searches for Solving the Minimum Sum-of-Squares Clustering Problem

    • Thiago Pereira, Daniel Aloise, Jack Brimberg, Nenad Mladenović
    Pages 249-270

  15. On the Design of Metaheuristics-Based Algorithm Portfolios

    • Dimitris Souravlias, Konstantinos E. Parsopoulos
    Pages 271-284

  16. Integral Simplex Methods for the Set Partitioning Problem: Globalisation and Anti-Cycling

    • Elina Rönnberg, Torbjörn Larsson
    Pages 285-303

  17. Open Problems on Benders Decomposition Algorithm

    • Georgios K. D. Saharidis, Antonios Fragkogios
    Pages 305-317

  18. An Example of Nondecomposition in Data Fitting by Piecewise Monotonic Divided Differences of Order Higher Than Two

    • I. C. Demetriou
    Pages 319-330
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Editors and Affiliations

  • Industrial and Systems, Engineering Department, University of Florida, Center For Applied Optimization, Gainesville, USA

    Panos M. Pardalos

  • Industrial Logistics, ETS Institute, Lulea University of Technology, Norrbotten, Sweden

    Athanasios Migdalas

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