sequential convex programming
时间: 2023-10-09 12:06:41 浏览: 42
Sequential convex programming (SCP) is an iterative optimization method used to solve non-convex optimization problems. The method involves dividing a non-convex problem into a sequence of convex subproblems, which are then solved iteratively.
At each iteration, the non-convex problem is approximated by a convex subproblem, which is then solved using standard convex optimization techniques. The solution of the subproblem is used to update the solution of the non-convex problem, and the process is repeated until convergence is achieved.
SCP is particularly useful in solving optimization problems with non-convex constraints or objective functions, where traditional optimization methods may fail to find a global optimum. The method has been widely used in machine learning, control theory, and other fields where optimization is a key component.
One potential drawback of SCP is that it may converge to a local optimum rather than a global optimum. However, this can be mitigated by starting the algorithm from multiple initial points and choosing the best solution among them.
相关推荐
![pptx](https://img-home.csdnimg.cn/images/20210720083543.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![djvu](https://img-home.csdnimg.cn/images/20210720083646.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)