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.
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 Algorithm to Minimize Fuel consumption ⛽ and CO2 emission 🚢💨
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