Research On GRASP Algorithms In The Application Of Airport Gate Assignment Problem

China’s civil aviation industry is experiencing a period of rapid development to take off in the rapid development of China’s overall macro-economic background,civilian airport resources gradually become stretched. In many of scarce resources, the airport gates between supply and demand are not open around the problem. Allocating the flights in a suitable airport gate is a major task. Airport gate assignment with the maximum possible optimization scheduling, can make the average walking distance travelers significantly reduced, so that visitors generate higher satisfaction, there is no doubt that this level of customer service for the increasingly demanding, increasingly competitive the field of civil aviation, is of great significance.Text refers to the relevant information on a large number of domestic and foreign scholars have studied the allocation of parking bays. By this basis, further study of the GRASP algorithm for this problem have been done. The main research work includes the following aspects:(1) Analyze the allocation of parking bays optimal scheduling algorithms home and abroad, in the summary of the strengths and weaknesses of previous studies based on in-depth analysis of several major factors that affect the final results of the allocation of gates.(2) Establish a relevant mathematical model for transit and non-transit model to model are discussed. For both kinds of mathematical models, which were studied by using a random algorithm to generate a turnaround of test data sets cannot turn the two models. Random data for experiment tests increase the credibility of the experimental results and analysis of research related to a variety of algorithms, in the application of the allocation of airport’s size characteristics of different data made data preparation. Algorithm is applied experimental methods in this paper can provide a reference for the other airports optimization scheduling problems.(3) Analyze the application of GRASP algorithm optimization problems at home and abroad. On the basis of previous research, a simplified algorithm GRASP algorithm: GSP and GRSP, and in the detailed theoretical and experimental analysis of these algorithm and genetic algorithm, exhaust algorithm and backtracking algorithm and a series of classic algorithms, and GSP algorithm, GRSP algorithm,GRASP algorithm hybrid algorithm genetic algorithm embedded in the gate allocation applications. Effects on the characteristics of each algorithm in the application of the relevant experiments are analyzed in the research and analysis.(4)For AGAP problem, we do research on applying fitness landscape analysis technology, not only from a practical effect, but also for confirming the superiority of the GRASP, compared with traditional genetic algorithm theory.