An Optimization Method for Scheduling Autonomous Potable Water Service Vehicles at Airfields

Due to increasingly serious flight delay and congestion and the issues of a low level of service and potential role of safety hazards of special vehicles at airports, an optimization method for scheduling autonomous potable water service (APWS) vehicles at airfields is studied. The level of service function for flights is developed by combining the hard time window of flights with a trapezoidal fuzzy membership function. Combined with the traditional C-W saving algorithm, the level of service function considers the time required for APWS vehicles serving flight, and with an objective to achieve the shortest total driving distance and the highest level of service to flights. Then, the total number of the flights to be served is used to measure the amount of work of each APWS vehicles, and an evaluation score for the amount of service work is proposed. Based on optimization results of C-W saving algorithm, the proposed algorithm further optimizes the sub-paths that do not reach the capacity limit of service flights, so as to achieve the minimum number of APWS vehicles and minimizing the difference in the number of flights served. A case study is carried out at a domestic airport, the results show that compared with the scenario with a single vehicle and uncoordinated service to flights, the total traveling distance of APWS vehicles is saved by 59.36%, 84 vehicle trips are saved, the level of service to flights reaches to 93.78%, and the difference of evaluation scores for the amount of service work is reduced from 93.32% to 43.96%. In contrast to the baseline algorithm, the workload of APWS vehicles can be balanced without increasing the total traveling distance, and the difference of evaluation scores for the amount of service work is reduced from 2.72 to 0.44, which significantly improves the workload balance of APWS vehicles.