Risk-Sensitive Peak-Aware Energy Scheduling: Competitive and Learning-Augmented Algorithms
Risk is a critical consideration in many energy-related problems, where stakeholders are often sensitive to rare but costly events. However, traditional online algorithms typically optimize expected cost and can perform poorly in such risk-sensitive settings. Motivated by this challenge, we study the design of algorith...