Robust Reward-Risk Ratio Optimization with Application in Allocation of Generation Asset

摘要

In this paper, we study reward-risk ratio models under partial known message of random variables, which is called robust (worst-case) performance ratio problem. Based on the positive homogenous and concave/convex measures of reward and risk respectively, the new robust ratio model is reduced equivalently to convex optimization problems. Such model exhibits a mix-max optimization framework.