Petrol truck scheduling optimization considering multi-path selection and congestion

We study petrol truck scheduling problem considering multi-path selection and congestion. In real life, drivers can choose paths to go between the start and finish when distributing oil, and with the increase of vehicles, road blockage has become a practical trouble. Setting the lowest cost of the scheduling process as objective function and taking truck volume, demand of petrol station and unloading time windows as constraints, an optimization model of petrol truck scheduling problem is established, and a heuristic approach is proposed. In our approach, we generate path combinations randomly. Then we remove combinations which do not comply with all the constraints. After these steps, we calculate the objective function of every feasible solutions and get the best solution. A real-life example with time windows is used to testify the model. And another case with 30 stations is tested to verify that the solving time is in a reasonable range. Through computational results, this approach shows good feasibility and high calculation speed.