数值优化，个人保存。Jorge Nocedal Stephen J.Wright 同时也是机器学习必修课程之一.

本书是数值最优化的权威著作，英文原版pdf格式

Numerical Optimization 数值优化 Jorge Nocedal Stephen J. Wright

OSQP的Python界面 Python包装器：运算符拆分QP解算器。 OSQP（算子拆分二次程序）求解器是一个数值优化程序包，用于解决以下形式的问题： minimize 0.5 x' P x + q' x subject to l <= A x <= u 其中x in R^n中的x in R^n是优化变量。 目标函数由P in S^n_+的正半定矩阵P in S^n_+和q in R^n向量q in R^n 。 线性约束由A in R^{mxn}的矩阵A in R^{mxn}和l in R^m U {-inf}^m向量l in R^m U {-inf}^m u in R^m U {+inf}^m 。 文献资料 该接口。 包装 该存储库执行测试并构建pypi轮子。 Conda软件包位于 forge上。

This is a book for people interested in solving optimization problems. Because of the wide (and growing) use of optimization in science, engineering, economics, and industry, it is essential for students and practitioners alike to develop an understanding of optimization algorithms.

经典的优化理论与方法书籍，英文版，慢慢读 很有收获

This is a book for people interested in solving optimization problems. Because of the wide (and growing) use of optimization in science, engineering, economics, and industry, it is essential for students and practitioners alike to develop an understanding of optimization algorithms.Knowledge of the capabilities and limitations of these algorithms leads to a better understanding of their impact on various applications, and points the way to future research on improving and extending optimization algorithms and software. Our goal in this book is to give a comprehensive description of the most powerful, state-of-the-art, techniques for solving continuous optimization problems. By presenting the motivating ideas for each algorithm, we try to stimulate the reader’s intuition and make the technical details easier to follow. Formal mathematical requirements are kept to a minimum.

英文版的最优化算法教程，内容简单易于理解，而且提供了很多精彩的算法。

This is a book for people interested in solving optimization problems. Because of the wide (and growing) use of optimization in science, engineering, economics, and industry, it is essential for students and practitioners alike to develop an understanding of optimization algorithms. Knowledge of the capabilities and limitations of these algorithms leads to a better understanding of their impact on various applications, and points the way to future research on improving and extending optimization algorithms and software. Our goal in this book is to give a comprehensive description of the most powerful, state-of-the-art, techniques for solving continuous optimization problems. By presenting the motivating ideas for each algorithm, we try to stimulate the reader’s intuition and make the technical details easier to follow. Formal mathematical requirements are kept to a minimum.

Numerical Optimization 2ed - Nocedal.pdf 第二版 全英文 超清晰 对于学习最优化理论知识有较好的帮助