| 000 | 01693nam a22002777a 4500 | ||
|---|---|---|---|
| 005 | 20260331114242.0 | ||
| 008 | 260331b |||||||| |||| 00| 0 eng d | ||
| 020 | _a9788126509331 | ||
| 040 | _cAL | ||
| 041 | _aeng | ||
| 082 |
_a620.0015196 _bRAVE |
||
| 100 |
_aRavindran A and others _9259815 |
||
| 245 |
_aEngineering optimization _b: methods and applications Ed 2 |
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| 250 | _a2 | ||
| 260 |
_aNew Delhi _bWiley _c2018 |
||
| 300 |
_axv,667p _bPB _c23x15cm |
||
| 365 |
_2Information Science and Engineering _aVBI-2645 _b₹471.75 _c₹ _d₹629.00 _e25% _f20-02-2026 |
||
| 520 | _aIn the most general terms, optimization theory is a body of mathematical results and numerical methods for finding and identifying the best candidate from a collection of alternatives without having to explicitly enumerate and evaluate all possible alternatives. The process of optimization lies at the root of engineering, since the classical function of the engineer is to design new, better, more efficient and less expensive systems as well as to devise plans and procedures for the improved operation of existing systems. Most optimization routines are lengthy and therefore are efficiently applied through the use of the computer, but an understanding of the processes is needed to identify needs and interpret results. This book supplies the student and practicing engineer with the tools to understand and use optimization theory. | ||
| 650 |
_aLinearization _9259816 |
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| 650 |
_aEngineering Case Studies _9259817 |
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| 650 |
_aQuadratic Approximation _9259818 |
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| 650 |
_aLinear Algebra _9259819 |
||
| 700 |
_aRagsdell K M _9259820 |
||
| 700 |
_aReklaitis G V _9259821 |
||
| 942 |
_2ddc _cBK |
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| 999 |
_c241088 _d241088 |
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