In this paper, we describe the formatting guidelines for ACM SIG Proceedings. For accurately estimating the ground service time of the transit flight and realizing the accuracy of the flight push time control, a time estimation method based on Markov Monte Carlo (MCMC) for the ground service of the transit flight is proposed. Based on actual process and time modeling, the ground service process is abstracted into an idealized Markov process. The Monte Carlo method is used to dynamically simulate the distribution of idealized links, and the Pearson chi-square fitting method is used to test the authenticity of the distribution. According to the actual process, the Markov Monte Carlo network structure is optimized, and the dynamic parameters of the structure are obtained by random numbers, and the ground service time of the flight is dynamically estimated from the actual operational logic relationship. Combined with the actual operation data of a central airport in China, It is showed that the mean absolute error of the dynamic method in this paper is 0.8 min shorter than that of the static method, and the error fluctuation is relatively stable, thus verifying the validity of the method.
[1]
Hamsa Balakrishnan,et al.
Dynamic Control of Airport Departures: Algorithm Development and Field Evaluation
,
2014,
IEEE Transactions on Intelligent Transportation Systems.
[2]
Michele Monaci,et al.
A Fast Heuristic for Airport Ground-Service Equipment–and–Staff Allocation☆
,
2014
.
[3]
Usama A. Badawi,et al.
Real-time aircraft turnaround operations manager
,
2014
.
[4]
Alexei Sharpanskykh,et al.
An agent-based model to study compliance with safety regulations at an airline ground service organization
,
2016,
Applied Intelligence.
[5]
Hamsa Balakrishnan,et al.
A Queuing Model of the Airport Departure Process
,
2016,
Transp. Sci..
[6]
Pernilla Ulfvengren,et al.
Preparing for Airport Collaborative Decision Making (A-CDM) implementation: an evaluation and recommendations
,
2014,
Cognition, Technology & Work.
[7]
Michèle Sebag,et al.
The grand challenge of computer Go
,
2012,
Commun. ACM.