The Airline Crew Scheduling System Optimization Algorithm Research And Design To Achieve

The enterprise business administration is greatly changed with the rapid development of the computer and communication technologies. In order to improve the competitive ability, every enterprise is building the decision-making supporting system after its affair-dealing system has been built for many years.With the development of the civil aviation, the market competition is becoming more and more fierces. In order to enlarge the market share and keep the competitive ability of the enterprise, it is necessary and urgent for the airline company to build an effective digital management system.This thesis refers to the optimization algorithm for the crew rostering system of an Airline. This subject is based on the Simulated annealing Algorithms and Genetic Algorithms. These two algorithms above are combined by relying on"the Intelligent Crew Rostering System for the Southwest Branch of the CAAC"which is made by Chengdu Neusoft Institute of Information. The crew rostering is optimized by the research on the two algorithms above. Moreover, this subject provides the theoretical foundation on which the research and application of the Simulated annealing Algorithms and Genetic Algorithms in the rostering project will go further.The method of combining the simulated annealing Algorithms with Genetic Algorithms not only offset the disadvantages of the Simulated annealing Algorithms but also enhanced the distributivity and the self-adaptivity of the Genetic Algorithms. This thesis introduced the concepts, principles and applications of the Simulated annealing Algorithms and Genetic Algorithms. By doing research on the project named"the Intelligent Crew Rostering System for the Southwest Branch of the CAAC", the advantages of the Simulated annealing Algorithms and Genetic Algorithms in application are further found. At the same time the study of the software engineering and software quality assurance is enhanced.The innovation of this thesis is that the simulated annealing Algorithms and Genetic Algorithms are combined to optimize the Intelligent Crew Rostering System for the Southwest Branch of the CAAC. The researches on the Crew Rostering General Algorithm Model, Crew Rostering Assignment Equilibria Algorithm Model and the Crew Hot-airlines Rostering Algorithm Models are done deliberately. The GASA hybrid algorithm is given out by combining and optimizing the Simulated annealing Algorithms and Genetic Algorithms. The actual data of Airline Company tested shows its reasonability and efficiency.