… Vehicle Routing Problem (VRP) using reinforcement learning. In this approach, we train a
single policy model that finds near-optimal solutions for a broad range of problem instances of …

… learning is similar to supervised one, but not all observations have labels (outputs). Finally,
reinforcement learning … only focuses on reinforcement learning (RL) application to routing in …

… We tested on two kinds of routing problems — VRP and VRPTW, with problem sizes of 20,
50 and 100, respectively. The test sets are generated based on the routing simulator, named …

… This work presents a survey of reinforcement learning-based (RL) approaches proposed
to solve the vehicle routing problem (VRP) along with its different variants. The paper also …

… to solve sub-problems conjointly. As an alternative approach, this work presents a deep
reinforcement learning method for solving the global routing problem in a simulated environment…

… It should be emphasized that none of the proposals discussed above in this literature
review uses reinforcement learning among its optimization problem solving structures. …

… for solving combinatorial optimization problems. The deep … model is proposed to solve
routing problems. In this model, … NP-hard problem, vehicle routing problem. The experiments …

… We analyze the literature on reinforcement learning for SDVRP originating from the … for
dynamic routing problems. Either, the problems themselves are assignment problems without …

… routing helps companies reduce operational costs and increases its competitiveness. The
vehicle routing problem (VRP) seeks to identify optimal routes … on reinforcement learning (RL) …

… find optimal routing paths in networks with dynamic traffic distributions. In this paper, we
develop a reinforcement learning routing algorithm (RL-Routing) to solve a TE problem of SDN …