Winning the CityLearn Challenge: Adaptive Optimization with Evolutionary Search under Trajectory-based Guidance

Presents a method that uses optimization solution functions as policies for sequential decision-making and adapts model parameters online via an evolutionary algorithm with trajectory-based guidance. The approach has formal global convergence guarantees and won the 2021 CityLearn Challenge, achieving superior performance across metrics while maintaining interpretability.