Practical mathematical optimization : basic optimization theory and gradient-based algorithms
著者
書誌事項
Practical mathematical optimization : basic optimization theory and gradient-based algorithms
（Springer optimization and its applications, v. 133）
Springer, c2018
2nd ed
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注記
Includes bibliographical references (p. 355-364) and index
内容説明・目次
内容説明
This book presents basic optimization principles and gradient-based algorithms to a general audience, in a brief and easy-to-read form. It enables professionals to apply optimization theory to engineering, physics, chemistry, or business economics.
目次
1.Introduction.- 2.Line search descent methods for unconstrained minimization.-3. Standard methods for constrained optimization.-4. Basic Example Problems.- 5. Some Basic Optimization Theorems.- 6. New gradient-based trajectory and approximation methods.- 7. Surrogate Models.- 8. Gradient-only solution strategies.- 9. Practical computational optimization using Python.- Appendix.- Index.
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