Research On Algorithms Of Airline Crew Scheduling

With the rapid development of my country’s economy and the increasing popularity of civil aviation,the domestic civil aviation industry has ushered in an era of rapid development.The operation of the civil aviation system includes complex steps such as making flight plans,making aircraft scheduling plans,and making crew scheduling plans.The crew scheduling plan is the most important step in these steps,because the crew labor cost is second only to the fuel cost.Airline operating costs are the second largest component,and they are more controllable than fuel costs,which account for the largest proportion.The crew scheduling process can usually be divided into Crew Pairing Problem and Crew Rostering Problem.This paper aims to generate a set of crew task loops with the smallest cost,covering all flights and meeting legal standards,and establishes a crew task pairing mathematical model based on an improved dynamic memetic algorithm.According to the characteristics of crew scheduling,the optimization step is divided into two parts: task loop generation and optimization solution.Based on the depth first search,a task loop search algorithm is developed to efficiently generate feasible task loops.And developed a search algorithm for minimizing the task ring and a lower cost task ring search algorithm to update the search space to avoid suboptimal solutions due to fewer high-quality genes in the search space.Finally,the Taguchi experiment is used to determine the parameter configuration of the cultural gene algorithm,and an example of flight information of a medium-sized airline is analyzed,and the test results are given.Through the comparison of multiple key performance indicators,the results show that the dynamic cultural gene algorithm can obtain a higher quality solution for the crew task matching problem than the previous algorithms.