| 紀錄類型: |
書目-語言資料,印刷品
: 單行本
|
| 作者: |
MartinsJoaquim R. R. A., |
| 其他作者: |
NingS. Andrew, |
| 出版地: |
Cambridge |
| 出版者: |
Cambridge University Press; |
| 出版年: |
2022. |
| 面頁冊數: |
xiii, 637 p.ill. (some col.) : 26 cm; |
| 標題: |
Engineering design - Mathematical models. - |
| 標題: |
Mathematical optimization. - |
| 標題: |
Multidisciplinary design optimization. - |
| 標題: |
MATHEMATICS / Optimization - |
| 摘要註: |
"Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 200 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice"--Provided by publisher. |
| ISBN: |
9781108833417 |
| 內容註: |
A short history of optimization Numerical models and solvers Unconstrained gradient-based optimization Constrained gradient-based optimization Computing derivatives Gradient-free optimization Discrete optimization Multiobjective optimization Surrogate-based optimization Convex optimization Optimization under uncertainty Multidisciplinary design optimization. |