| 000 | 01374nam a22001937a 4500 | ||
|---|---|---|---|
| 999 |
_c1455 _d1455 |
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| 020 | _a9780470937419 | ||
| 041 | _aEnglish | ||
| 082 | _a006.3 | ||
| 100 |
_a Dan Simon _92638 |
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| 245 | _aEvolutionary optimization algorithms : biologically-Inspired and population-based approaches to computer intelligence | ||
| 250 | _a1st | ||
| 520 | _a"This book is a clear and lucid presentation of Evolutionary Algorithms, with a straightforward, bottom-up approach that provides the reader with a firm grasp of the basic principles of EAs. Covering the theory, history, mathematics, and applications of evolutionary optimization algorithms, this timely and practical book offers lengthy examples, a companion website, MATLAB code, and a Solutions Manual--making it perfect for advanced undergraduates, graduates, and practicing engineers involved in engineering and computer science"-- Summary: "Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear (but theoretically rigorous) understanding of Evolutionary Algorithms, with an emphasis on implementation rather than models"-- | ||
| 650 | 0 |
_a Evolutionary computation _92639 |
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| 650 | 0 |
_aComputer algorithms; _92058 |
|
| 650 | 0 |
_a Biologically-inspired computing _92640 |
|
| 650 | 0 |
_aMATHEMATICS / Discrete Mathematics. _92641 |
|
| 856 | _uhttps://digilib.sltc.ac.lk/login | ||
| 942 | _cEB | ||
| 945 |
_c3278 _dManu Pasantha PERUMBULI ACHCHIGE |
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