Designing optimal power flow (OPF) models for ac–dc distribution networks poses significant challenges due to their highly nonlinear nature. However, convex relaxations can overcome the complexities.

This study explores optimizing the Traveling Salesman Problem (TSP) using Q-Learning reinforcement learning. The proposed method builds a Q-table to learn the optimal path and employs dynamic ...