Practical genetic algorithms /
Randy L. Haupt & Sue Ellen Haupt.
- 1 online resource (xiv, 177 pages) : illustrations
Includes bibliographical references and index.
Introduction to optimization -- The binary genetic algorithm -- The continuous parameter genetic algorithm -- Applications -- An added level of sophistication -- Advanced applications -- Evolutionary trends -- Appendix -- Glossary -- Index.
Practical Genetic Algorithms is the first introductory-level book to emphasize practical applications through the use of example problems. In an accessible style, the authors explain why the genetic algorithm is superior in many real-world applications, cover continuous parameter genetic algorithms, and provide in-depth trade-off analysis of genetic algorithm parameter selection. Written for the end user in engineering, science, and computer programming, as well as upper-level undergraduate and graduate students, Practical Genetic Algorithms provides numerous practical example problems; contains over 80 illustrations; features many figures and tables; and includes three appendices: a glossary of terms, a list of genetic algorithm routines in pseudocode, and a list of symbols used in the book.