A Phased Scheduling Method with an Improved GA for Material Delivery Problem of Aircraft Pulsating Assembly Line*

Timely delivery of materials is essential in ensuring the smooth operation of aircraft pulsating assembly lines. According to the production characteristic of aircraft pulse-like movement in pulsating assembly lines, a material delivery model is established to minimize the time window constraint penalties and delivery costs. Due to the problem characteristics of large scale, long decision cycle and uneven distribution of tasks in time, a phased scheduling method based on an improved genetic algorithm is proposed. Firstly, the decision cycle can be divided into the aircraft moving phase and the assembling phase. Secondly, the assembling phase is subdivided into several small phases to adjust the number of used AGVs and the delivery starting time of each phase. Finally, a genetic algorithm is used within each phase to decide the delivery tasks, delivery starting time and driving paths for every AGV, which has been improved for solving the large-scale problem by optimizing the generation of initial populations and adding a local search operator. The effectiveness of the proposed algorithm is verified in a practical case of an aircraft pulsating assembly line.