Optimization for Industrial Problems pptx

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Optimization for Industrial Problems pptx

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[...]... practical optimization problems are constrained or bounded Simple boundaries are usually no problem Complicated constraints like the integral constraint above are usually complex and must often be treated specially P Bangert (ed.), Optimization for Industrial Problems, DOI 10.1007/978-3-642-24974-7_1, © Springer-Verlag Berlin Heidelberg 2012 1 2 1 Overview of Heuristic Optimization 1.1.1 Searching vs Optimization. .. and can distend to any extent Depend upon it, there comes a time when for every addition of knowledge you forget something that you knew before It is of the highest importance, therefore, not to have useless facts elbowing out the useful ones.’ ” Sherlock Holmes [Arthur Conan Doyle, A Study in Scarlet] In the solution of optimization problems, many factors act in concert to achieve the cumulative effect... macrostate is thus not a one-to-one relationship By analogy to maps we have one altitude for a specified location but possibly several locations for one specified altitude; as such the location is the microstate and the altitude the macrostate The same observation holds true for optimization problems: A particular value for the cost function is usually achieved with many settings of the process parameters... do it for the above well meant and well documented reasons as well as the practical reasons that in a book focusing on practical applications a fundamental equanimity has no place as there is simply no room for it in the book and no time for it in the day of industry problem solvers In conclusion, SA is good enough for industry work and we recommend it most heartily to all 1.2.3 Multi-Objective Optimization. .. both parties starting to un- 1.4 Example Theoretical Problems 11 derstand each other will these questions receive a correct answer This is the natural evolution of such a project and one should not be upset at this For this reason, it is crucial for the management that started the project to appreciate this point! 1.4 Example Theoretical Problems For the sake of the discussions in this book, we will... 8 What is optimization? What is an optimization problem? What are the management challenges in an optimization project? How can we deal with faulty and noisy empirical data? How do we gain an understanding of our dataset? How is a dataset converted into a mathematical model? How is the optimization problem actually solved? What are some challenges in implementing the optimal solution in industrial. .. the correct approach to optimization The bottom-up approach is not successful Thus, we recommend to always first get the bird’s eye view of a situation Both SA and GA are methods that may be applied to any problem For SA we must define how to transit from one point to another For GA we must define how two points beget another point for the next generation The rest of the method for both SA and GA are completely... ask for your patience with these Any benefits are, of course, obtained by standing on the shoulders of giants and making small changes Many case studies are co-authored by the management from the relevant industrial corporations I heartily thank all co-authors for their participation! All the case studies were also written by me and the same comments apply to them I also thank the coauthors very much for. .. can already bear useful information without further mathematical analysis Financial Data Analysis for Contract Planning Section 4.9, p 58 Preface xv Summary: Based on past financial data, we create a detailed projection into the future in several categories and so provide decision support for budgeting Lessons: Discovering basic statistical features of data first, allows the transformation of ERP data into... challenge of multi-objective optimization This is, by now, a large research field with many 8 1 Overview of Heuristic Optimization methods We will discuss the basic ideas here but refer to the literature for more details [116] The obvious solution is to create a single objective function from the various objectives and so create a new problem that has only one objective function We may, for instance, translate . class="bi x0 y0 w0 h0" alt="" Optimization for Industrial Problems 123 Patrick Bangert Optimization for Industrial Problems Printed on acid-free. possible revolution in industrial uses for mathematical methods. These uses center around the problem of optimization as almost every industrial problem concerns

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Mục lục

  • Optimization for Industrial Problems

  • Preface

    • Some Early Opinions on Technology

    • This book is practical

    • This book is intended for practitioners

    • 1.1.3 Finding through a little Searching

    • Chapter 2 Statistical Analysis in Solution Space

      • 2.1 Basic Vocabulary of Statistical Mechanics

      • 2.2 Postulates of the Theory

      • 4.2.2 Data not Ordered in Time

      • 4.3.3 Irregular and Abnormal Data

      • 4.9 Case Study: Financial Data Analysis for Contract Planning

      • 4.10 Case Study: Measuring Human Influence

      • 4.11 Case Study: Early Warning System for Importance of Production Alarms

      • Chapter 5 Data Mining: Knowledge from Data

        • 5.1 Concepts of Statistics and Measurement

          • 5.1.1 Population, Sample and Estimation

          • 5.1.2 Measurement Error and Uncertainty

          • 5.1.3 Influence of the Observer

          • 5.1.4 Meaning of Probability and Statistics

          • 5.2.2 Specific Tests

            • 5.2.2.1 Do two datasets have the same mean?

            • 5.2.2.2 Do two datasets have the same variance?

            • 5.2.2.3 Are two datasets differently distributed?

            • 5.2.2.4 Are there outliers and, if so, where?

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