Successive Convex Approximation (SCA)
作者：凯鲁嘎吉 - 博客园 http://www.cnblogs.com/kailugaji/
Successive Convex Approximation(连续凸近似，SCA)是一种求解非凸优化问题的处理方法，它将非凸优化问题转化为一系列凸问题，从而得到原问题的近似解。
1. 非凸优化问题描述
2. SCA求解非凸优化问题
求解非凸问题(1)已经转化为求解凸优化问题(5)，然后应用凸优化方法[2]进行求解即可。
3. 参考文献
[1] Di Lorenzo P, Scutari G. Next: In-network nonconvex optimization[J]. IEEE Transactions on Signal and Information Processing over Networks, 2016, 2(2): 120-136.
[2] Boyd S, Vandenberghe L. Convex optimization[M]. Cambridge university press, 2004.
[3] Razaviyayn, Meisam. (2014). Successive convex approximation: analysis and applications. Retrieved from the University of Minnesota Digital Conservancy, http://hdl.handle.net/11299/163884.
