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The Simple Genetic Algorithm

By: Material type: TextTextSeries: Complex adaptive systemsPublication details: New Delhi Prentice Hall of India Private Limited 2007Description: ix, 251 pages : illustrations (some color) ; 24 cmISBN:
  • 9788120324596
Subject(s): DDC classification:
  • 005.1 VOS-S
Contents:
1. Introduction -- 2. Notation -- 3. Random Heuristic Search -- 4. The Simple Genetic Algorithm -- 5. Implementation -- 6. The Walsh Transform -- 7. Computing with the Heuristic -- 8. Basic Examples -- 9. The Inverse Heuristic -- 10. Focused Heuristics -- 11. Linear Fitness -- 12. Perturbation Arguments -- 13. Transient Behavior -- 14. Asymptotic Behavior -- 15. Hyperbolicity -- 16. Geometric Invariance -- 17. Quotients -- 18. Models -- 19. Schemata.
Summary: "The Simple Genetic Algorithm (SGA) is a classical form of genetic search. Viewing the SGA as a mathematical object, Michael D. Vose provides an introduction to what is known (i.e., proven) about the theory of the SGA. He also makes available algorithms for the computation of mathematical objects related to the SGA."--BOOK JACKET. "Although he describes the SGA in terms of heuristic search, the book is not about search or optimization perse. Rather, the focus is on the SGA as an evolutionary system."--Jacket.
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Holdings
Item type Current library Home library Call number Status Date due Barcode
Book Book Dept. of Computational Biology and Bioinformatics Processing Center Dept. of Computational Biology and Bioinformatics 005.1 VOS-S (Browse shelf(Opens below)) Available DCB279

1. Introduction -- 2. Notation -- 3. Random Heuristic Search -- 4. The Simple Genetic Algorithm -- 5. Implementation -- 6. The Walsh Transform -- 7. Computing with the Heuristic -- 8. Basic Examples -- 9. The Inverse Heuristic -- 10. Focused Heuristics -- 11. Linear Fitness -- 12. Perturbation Arguments -- 13. Transient Behavior -- 14. Asymptotic Behavior -- 15. Hyperbolicity -- 16. Geometric Invariance -- 17. Quotients -- 18. Models -- 19. Schemata.

"The Simple Genetic Algorithm (SGA) is a classical form of genetic search. Viewing the SGA as a mathematical object, Michael D. Vose provides an introduction to what is known (i.e., proven) about the theory of the SGA. He also makes available algorithms for the computation of mathematical objects related to the SGA."--BOOK JACKET. "Although he describes the SGA in terms of heuristic search, the book is not about search or optimization perse. Rather, the focus is on the SGA as an evolutionary system."--Jacket.

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