基于智能网联的机场摆渡车车辆路径优化模型和算法

Airport Shuttle Vehicle Routing Optimization Model and Algorithm Based on Internet of Things

摘要: 基于智能网联动态跟踪航班的旅客接运任务、摆渡车的状态，据此构建一类机场摆渡车车辆路径优化的数学模型，考虑不同航班的旅客接运任务时间窗等现实因素，将若干旅客接运任务分配给不同类型机场加油车，确定车辆执行这些旅客接运任务的顺序，追求机场摆渡车调度成本最小化。根据问题特征，设计求解该问题的遗传算法，定义编码方案、产生初始种群的启发式算法、适应度函数、交叉和变异操作。最后，以某机场摆渡车调度为例，生成最佳车辆路径方案，分析不同车辆数对结果的影响，从而证明模型和算法的优越性。

Abstract: By using the internet of things to dynamically track the status of the passenger pick-up task and the shuttle car, a multi-objective linear programming model for airport shuttle vehicles problems is constructed. By considering the practical factors such as the time window of passenger pick-up task of different flights, the model aims to assign several passenger pick-up tasks to different types of airport refueling vehicles and determine the order of the vehicles to perform these passenger pick-up tasks, and, so as to minimize the scheduling cost of airport shuttle vehicles. According to the characteristics of the problem, the genetic algorithm is designed to solve the problem, where the coding scheme is defined, the heuristic algorithm for generating the initial population, the fitness function, crossover and mutation operations are defined. Finally, taking an airport shuttle bus scheduling as an example, the optimal vehicle routing scheme is generated, and the influence of different vehicle numbers on the result is analyzed, so as to prove the superiority of model and algorithm.