Cellular Genetic Algorithms (eBook)

Enrique Alba, Bernabe Dorronsoro (Autoren)

eBook Download: PDF

2009 | 2008
XIV, 248 Seiten
Springer US (Verlag)
978-0-387-77610-1 (ISBN)

Infos

Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel emphasis on both theory and practice. This book is a key source for studying and designing cellular GAs, as well as a self-contained primary reference book for these algorithms.

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Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book. This class of genetic algorithms is shown to produce impressive results on a whole range of domains, including complex problems that are epistatic, multi-modal, deceptive, discrete, continuous, multi-objective, and random in nature. The focus of this book is twofold. On the one hand, the authors present new algorithmic models and extensions to the basic class of Cellular GAs in order to tackle complex problems more efficiently. On the other hand, practical real world tasks are successfully faced by applying Cellular GA methodologies to produce workable solutions of real-world applications. These methods can include local search (memetic algorithms), cooperation, parallelism, multi-objective, estimations of distributions, and self-adaptive ideas to extend their applicability.The methods are benchmarked against well-known metaheuristics like Genetic Algorithms, Tabu Search, heterogeneous GAs, Estimation of Distribution Algorithms, etc. Also, a publicly available software tool is offered to reduce the learning curve in applying these techniques. The three final chapters will use the classic problem of vehicle routing and the hot topics of ad-hoc mobile networks and DNA genome sequencing to clearly illustrate and demonstrate the power and utility of these algorithms.

Inhalt

Enrique Alba and Bernabé Dorronsoro 4
Preface 7
Contents 9
Part I Introduction 14
1 Introduction to Cellular Genetic Algorithms 15
2 The State of the Art in Cellular Evolutionary Algorithms 33
Part II Characterizing Cellular Genetic Algorithms 47
3 On the Effects of Structuring the Population 48
4 Some Theory: A Selection Pressure Study on cGAs 58
Part III Algorithmic Models and Extensions 81
5 Algorithmic and Experimental Design 82
6 Design of Self-adaptive cGAs 92
7 Design of Cellular Memetic Algorithms 109
8 Design of Parallel Cellular Genetic Algorithms 123
9 Designing Cellular Genetic Algorithms for Multi-objective Optimization 135
10 Other Cellular Models 147
11 Software for cGAs: The JCell Framework 161
Part IV Applications of cGAs 172
12 Continuous Optimization 173
13 Logistics: The Vehicle Routing Problem 181
14 Telecommunications: Optimization of the Broadcasting Process in MANETs 193
15 Bioinformatics: The DNA Fragment Assembly Problem 209
Part V Appendix 217
A Definition of the Benchmark Problems 218
References 230
Index 248

Produkt-Details

• Erscheint lt. Verlag: 5.4.2009
• Reihe/Serie: Operations Research/Computer Science Interfaces Series
• Reihe/Serie: Operations Research/Computer Science Interfaces Series
• Zusatzinfo: XIV, 248 p. 72 illus.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Themenwelt: Mathematik / Informatik ► Mathematik ► Analysis
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Studium ► 2. Studienabschnitt (Klinik) ► Humangenetik
• Themenwelt: Technik
• Themenwelt: Wirtschaft ► Allgemeines / Lexika
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Logistik / Produktion
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Planung / Organisation
• Schlagworte: algorithm • algorithms • Bioinformatics • Communication • evolutionary algorithm • Genetic algorithms • Metaheuristic • Multi-Objective Optimization • Optimization • Optimization algorithm • optimization algorithms
• ISBN-10: 0-387-77610-9 / 0387776109
• ISBN-13: 978-0-387-77610-1 / 9780387776101