Weise T. Global Optimization Algorithms. Theory and Application

University of Science and Technology of China, 2011,-1217 p.Third edition, extended and revised. Zip with examples is attached on the first pageThis e-book is devoted to Global Optimization algorithms, which are methods for finding solutions of high quality for an incredible wide range of problems. We introduce the basic concepts of optimization and discuss features which make optimization problems difficult and thus, should be considered when trying to solve them. In this book, we focus on metaheuristic approaches like Evolutionary Computation, Simulated Annealing, Extremal Optimization, Tabu Search, and Random Optimization. Especially the Evolutionary Com- putation methods, which subsume Evolutionary Algorithms, Genetic Algorithms, Genetic Programming, Learning Classifier Systems, Evolution Strategy, Differential Evolution, Par- ticle Swarm Optimization, and Ant Colony Optimization, are discussed in detail. In this third edition, we try to make a transition from a pure material collection and compendium to a more structured book. We try to address two major audience groups: 1. Our book may help students, since we try to describe the algorithms in an under- standable, consistent way. Therefore, we also provide the fundamentals and much background knowledge. You can find (short and simplified) summaries on stochastic theory and theoretical computer science in Part VI on page636. Additionally, appli- cation examples are provided which give an idea how problems can be tackled with the different techniques and what results can be expected.2. Fellow researchers and Ph.D. students may find the application examples helpful too. For them, in-depth discussions on the single approaches are included that are supported with a large set of useful literature references.The contents of this book are divided into three parts. In the first part, different op- timization technologies will be introduced and their features are described. Often, small examples will be given in order to ease understanding. In the second part starting at page 528, we elaborate on different application examples in detail. Finally, in the last part fol- lowing at page 636, the aforementioned background knowledge is provided. In order to maximize the utility of this electronic book, it contains automatic, clickable links. They are shaded with dark gray so the book is still b/w printable. You can click on1. entries in the table of contents,2. citation references like Heitk¨otter and Beasley [1202],
3. page references like 253,
4. references such as see Figure 28.1 on page 254 to sections, figures, tables, and listings, andThe following scenario is an example for using the book: A student reads the text and finds a passage that she wants to investigate in-depth. She clicks on a citation which seems interesting and the corresponding reference is shown. To some of the references which are online available, links are provided in the reference text. By clicking on such a link, the Adobe ReaderR2 will open another window and load the regarding document (or a browser window of a site that links to the document). After reading it, the student may use the backwards button in the Acrobat Reader’s navigation utility to go back to the text initially read in the e-book.If this book contains something you want to cite or reference in your work, please use the citation suggestion provided in Chapter A on page 943 . Also, I would be very happy if you provide feedback, report errors or missing things that you have (or have not) found, criticize something, or have any additional ideas or suggestions. Do not hesitate to contact me via my email address tweise@gmx.de. Matter of fact, a large number of people helped me to improve this book over time. I have enumerated the most important contributors in Chapter D – Thank you guys, I really appreciate your help! At many places in this book we refer to Wikipedia – The Free Encyclopedia [2888] which is a great source of knowledge. Wikipedia – The Free Encyclopedia contains articles and definitions for many of the aspects discussed in this book. Like this book, it is updated and improved frequently. Therefore, including the links adds greatly to the book’s utility, in my opinion.Part I FoundationsProblem Space and Objective Functions
Optima: What does good mean?
Search Space and Operators: How can we find it?
Fitness and Problem Landscape: How does the Optimizer see it?
The Structure of Optimization: Putting it together
Solving an Optimization Problem
Baseline Search Patterns
Forma Analysis
General Information on Optimization
Part II Difficulties in OptimizationProblem Hardness
Unsatisfying Convergence
Ruggedness and Weak Causality
Deceptiveness
Neutrality and Redundancy
Epistasis, Pleiotropy, and Separability
Noise and Robustness
Overfitting and Oversimplification
Dimensionality (Objective Functions)
Scale (Decision Variables)
Dynamically Changing Fitness Landscape
The No Free Lunch Theorem
Lessons Learned: Designing Good Encodings
Part III Metaheuristic Optimization AlgorithmsHill Climbing
Simulated Annealing
Evolutionary Algorithms
Genetic Algorithms
Evolution Strategies
Genetic Programming
Evolutionary Programming
Differential Evolution
Estimation Of Distribution Algorithms
Learning Classifier Systems
Memetic and Hybrid Algorithms
Ant Colony Optimization
River Formation Dynamics
Particle Swarm Optimization
Tabu Search
Extremal Optimization
GRASPs
Downhill Simplex (Nelder and Mead)
Random Optimization
Part IV Non-Metaheuristic Optimization AlgorithmsState Space Search
Branch And Bound
Cutting-Plane Method
Part V Applications
Real-World Problems
Benchmarks
Part VI Background
Set Theory
Graph Theory
Stochastic Theory and Statistics
Part VII ImplementationThe Specification Package
The Implementation Package
Demos
B GNU Free Documentation License (FDL)
C GNU Lesser General Public License (LGPL)
D Credits and Contributors