The Custom Gridworld and Environment Demo of Ship Route Planning with Reinforcement Learning. The reinforcement learning based on Qlearning method is realized. Q tables can be saved. Support documentation of training sessions. Support the display of result graphs

Ship Routing Algorithms for Just-In-Time and Energy Efficient Voyages. By using a genetic algorithm we strive the lowest possible fuel consumption while at the same time keeping the scheduled deadlines. Two different specifications of the algorithm are available, one with a constant engine power, one with an over the route changeable engine power.