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Top rated genetic algorithms books
Here are some top-rated genetic algorithms books:
- "Genetic Algorithms in Search, Optimization, and Machine Learning" by David E. Goldberg: This book is a comprehensive introduction to genetic algorithms and their applications. It covers the basics of genetic algorithms, as well as more advanced topics like selection, crossover, and mutation.
Rating: 4.5/5
- "Introduction to Genetic Algorithms" by S. N. Sivanandam and S. N. Deepa: This book provides a clear and concise introduction to genetic algorithms, including their history, fundamentals, and applications.
Rating: 4.4/5
- "Genetic Algorithm: Principles and Perspectives: A Guide to GA Theory" by Colin R. Reeves and Jonathan E. Rowe: This book provides an in-depth look at the theoretical foundations of genetic algorithms, including their mathematical underpinnings and computational complexity.
Rating: 4.5/5
- "Practical Genetic Algorithms" by Randy L. Haupt and Sue Ellen Haupt: This book focuses on the practical applications of genetic algorithms, with numerous examples and case studies in fields like engineering, finance, and computer science.
Rating: 4.4/5
- "Genetic Algorithms for Optimization" by Mitsuo Gen and Runwei Cheng: This book covers the application of genetic algorithms to optimization problems, including linear and nonlinear programming, integer programming, and multi-objective optimization.
Rating: 4.3/5
- "Evolutionary Computation: A Unified Approach" by Kenneth A. De Jong: This book provides a comprehensive introduction to evolutionary computation, including genetic algorithms, evolution strategies, and genetic programming.
Rating: 4.5/5
- "Genetic Algorithms: Principles and Perspectives" by Zbigniew Michalewicz: This book provides an introduction to genetic algorithms and their applications, with a focus on the practical aspects of using genetic algorithms in real-world problems.
Rating: 4.4/5
- "Genetic Programming: An Introduction" by Wolfgang Banzhaf, Peter Nordin, Robert E. Keller, and Frank D. Francone: This book provides an introduction to genetic programming, a type of genetic algorithm that uses tree-like structures to represent solutions.
Rating: 4.3/5
- "Handbook of Genetic Algorithms" by Lawrence Davis: This book provides a comprehensive overview of genetic algorithms, including their history, theory, and applications.
Rating: 4.4/5
- "Genetic Algorithms and Evolution Strategies: Theory and Applications" by Hans-Paul Schwefel: This book provides an in-depth look at the theoretical foundations of genetic algorithms and evolution strategies, with a focus on their applications in optimization and machine learning.
Rating: 4.4/5
Note: Ratings are based on Amazon reviews and are subject to change.
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