University of Science and Technology of China, 2011,-1217 pp.
Third edition, extended and revised. Zip with examples is attached on the first page
This 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, Leaing 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 page
636. 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 PhD 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 on
1. 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,
and
5. URLs and links like http://www.lania.mx/?ccoello/EMOO/ [accessed 2007-10-25].
The 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(собачка)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 Foundations.
Introduction.
Problem 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 Pattes.
Forma Analysis.
General Information on Optimization.
Part II Difficulties in Optimization.
Introduction.
Problem 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 Leaed: Designing Good Encodings.
Part III Metaheuristic Optimization Algorithms.
Introduction.
Hill Climbing.
Simulated Annealing.
Evolutionary Algorithms.
Genetic Algorithms.
Evolution Strategies.
Genetic Programming.
Evolutionary Programming.
Differential Evolution.
Estimation Of Distribution Algorithms.
Leaing 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 Algorithms.
Introduction.
State Space Search.
Branch And Bound.
Cutting-Plane Method.
t V Applications.
Real-World Problems.
Benchmarks.
Part VI Background.
Set Theory.
Graph Theory.
Stochastic Theory and Statistics.
t VII Implementation.
Introduction.
The Specification Package.
The Implementation Package.
Demos.
B GNU Free Documentation License (FDL).
C GNU Lesser General Public License (LGPL).
D Credits and Contributors.
Third edition, extended and revised. Zip with examples is attached on the first page
This 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, Leaing 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 page
636. 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 PhD 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 on
1. 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,
and
5. URLs and links like http://www.lania.mx/?ccoello/EMOO/ [accessed 2007-10-25].
The 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(собачка)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 Foundations.
Introduction.
Problem 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 Pattes.
Forma Analysis.
General Information on Optimization.
Part II Difficulties in Optimization.
Introduction.
Problem 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 Leaed: Designing Good Encodings.
Part III Metaheuristic Optimization Algorithms.
Introduction.
Hill Climbing.
Simulated Annealing.
Evolutionary Algorithms.
Genetic Algorithms.
Evolution Strategies.
Genetic Programming.
Evolutionary Programming.
Differential Evolution.
Estimation Of Distribution Algorithms.
Leaing 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 Algorithms.
Introduction.
State Space Search.
Branch And Bound.
Cutting-Plane Method.
t V Applications.
Real-World Problems.
Benchmarks.
Part VI Background.
Set Theory.
Graph Theory.
Stochastic Theory and Statistics.
t VII Implementation.
Introduction.
The Specification Package.
The Implementation Package.
Demos.
B GNU Free Documentation License (FDL).
C GNU Lesser General Public License (LGPL).
D Credits and Contributors.