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Optimization for Industrial Problems

  • Book
  • © 2012

Overview

Authors:
  1. Patrick Bangert

    1. algorithmica technologies GmbH, Bremen, Germany

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  • Presentation of modern methods to solve real and pressing industrial optimization problems in a practical way together with real-life examples
  • With examples usually hard to come by or not published at all
  • Presents new methods or new results about existing methods to information science
  • Includes supplementary material: sn.pub/extras

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xxii
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  2. Overview of Heuristic Optimization

    • Patrick Bangert
    Pages 1-11

  3. Statistical Analysis in Solution Space

    • Patrick Bangert
    Pages 13-27

  4. Project Management

    • Patrick Bangert
    Pages 29-36

  5. Pre-processing: Cleaning up Data

    • Patrick Bangert
    Pages 37-66

  6. Data Mining: Knowledge from Data

    • Patrick Bangert
    Pages 67-119

  7. Modeling: Neural Networks

    • Patrick Bangert
    Pages 121-164

  8. Optimization: Simulated Annealing

    • Patrick Bangert
    Pages 165-200

  9. The human aspect in sustainable change and innovation

    • Andreas Ruff
    Pages 201-241

  10. Back Matter

    Pages 243-246
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Keywords

About this book

Industrial optimization lies on the crossroads between mathematics, computer science, engineering and management. This book presents these fields in interdependence as a conversation between theoretical aspects of mathematics and computer science and the mathematical field of optimization theory at a practical level. The 19 case studies that were conducted by the author in real enterprises in cooperation and co-authorship with some of the leading industrial enterprises, including RWE, Vattenfall, EDF, PetroChina, Vestolit, Sasol, and Hella, illustrate the results that may be reasonably expected from an optimization project in a commercial enterprise. The book is aimed at persons working in industrial facilities as managers or engineers; it is also suitable for university students and their professors as an illustration of how the academic material may be used in real life. It will not make its reader a mathematician but it will help its reader in improving his plant.

Reviews

From the reviews:

“This book focusses on optimal control of industrial systems that reflect real-life problems with a ‘practical flavor’. … it is aimed at managers, professionals, practitioners or engineers of industrial facilities. It also gives a good window to real-world industrial systems for those working in academic institutions. This reviewer enjoyed reading the book and it is an excellent addition to the field … .” (D. Subbaram Naidu, Amazon.com, April, 2014)

“In Optimization for Industrial Problems, Patrick Bangert describes the tools and techniques he and his coauthors have used to address difficult industrial challenges. The book has an impressive set of 19 case studies that successfully demonstrate the role of advanced analytics in optimization. … Managers of heavy industrial equipment, who have a reasonable understanding of statistics, could also use this book to identify opportunities for using advanced data analysis and statistical models to improve plant performance.” (Kenneth Chelst, Interfaces, Vol. 43 (5), September-October, 2013)

Authors and Affiliations

  • algorithmica technologies GmbH, Bremen, Germany

    Patrick Bangert

About the author

Dr. Patrick Bangert, algorithmica technologies GmbH, Bremen, Germany

Bibliographic Information

  • Book Title: Optimization for Industrial Problems

  • Authors: Patrick Bangert

  • DOI: https://doi.org/10.1007/978-3-642-24974-7

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2012

  • Softcover ISBN: 978-3-642-24973-0Published: 05 January 2012

  • eBook ISBN: 978-3-642-24974-7Published: 05 January 2012

  • Edition Number: 1

  • Number of Pages: XXII, 246

  • Number of Illustrations: 34 b/w illustrations, 30 illustrations in colour

  • Topics: Optimization, Operations Research, Management Science

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