Research on Intelligent Scheduling of Foreign Flight Attendants' busy time Based on Parallel Genetic Algorithm

Abstract

The current intelligent scheduling method of foreign service staff based on intelligent optimization algorithm realizes the scheduling of staff by individual coding, which leads to the low stability of the algorithm because the constraints and optimization of the objective function are not comprehensive enough. In this regard, the intelligent scheduling method of foreign service staff of busy time airlines based on parallel genetic algorithm is proposed. By setting the optimal parameters such as population size, the objective function is constructed with the airline operation revenue and passenger service degree as the objectives, and the shallow copy of data is used to optimize and constrain the function, and the outbound flight service staff scheduling model is constructed. In the experiment, the stability of the proposed intelligent scheduling method is verified. The analysis of the experimental results shows that the objective function constructed by using the proposed method has a high degree of convergence and high stability.