This project contains two MATLAB files explain Benders-dual/Column and Constraints Generation (CCG) Algorithm to solve Two-Stage Robust Optimization (RO) problems, as below (The uncertainty set 
- Bold characters (A,y,x,c,d,u...) denote matrix/vector in above.
- CCG is proposed in [1]. It's very fashion in optimization for power systems/integrated energy systems and has been cited 1000+ times.
- "BDforExample.m"/"CCGforExample.m" explains benders-dual/CCG to solve Two-Stage RO problems
- The example used in both files are from 4. Case study: robust location-transportation problem in [1]
- MATLAB optimization modeling tool YALMIP supports constraints writing in the fashion of “Cons = [A*x<=b]”, in which A is a matrix and x, b are vectors, therefore, the codes in both files are easy to read. (at least I believe so...)
- Because they are just like what you can see about the mathematical model in the paper.
- For both files: YALMIP, see (https://yalmip.github.io/)
- Both files are calling GUROBI(https://www.gurobi.com/) to solve the problem, but other solvers (e.g. CPLEX) could be used as well. (see what solvers they support in abovementioned link for YALMIP).
- Basics of Benders-dual/CCG Algorithm to solve Two-Stage RO problems
- A simple way to realize optimization modeling in MATLAB (ONLY ~100 lines are in both .m files)
- How to do in by yourself (just try it by yourself and you would definitely learn more!)
- 鲁棒优化| C&CG算法求解两阶段鲁棒优化：全网最完整、最详细的【入门-完整推导-代码实现】笔记. I found some tricky point in it about how to guarantee Master problem could provide initial feasible solution for Subproblem to make both algorithms work (i.e. constraint in MP "sum(z)>=772" in both files), so thanks.
- When Subproblem is unbounded both file would fail. Because I still don't know how to identify scenario for which Q(y*)=inf.
[1] Zeng, Bo, and Long Zhao. "Solving two-stage robust optimization problems using a column-and-constraint generation method." Operations Research Letters 41, no. 5 (2013): 457-461.