Time-Dependence in Multi-Agent MDP Applied to Gate Assignment Problem

Many disturbances can impact gate assignments in daily operations of an airport. Gate Assignment Problem (GAP) is the main task of an airport to ensure smooth flight-to-Gate assignment managing all disturbances. Or, flights schedule often undergoes some unplanned disruptions, such as weather conditi...

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Bibliographic Details
Published in:International journal of advanced computer science & applications 2018, Vol.9 (2)
Main Authors: AOUN, Oussama, EL, Abdellatif
Format: Article
Language:English
Subjects:
Airports
Assignment problem
Decision theory
Disturbances
Markov processes
Multiagent systems
Robustness (mathematics)
Schedules
Time dependence
Weather
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Summary:Many disturbances can impact gate assignments in daily operations of an airport. Gate Assignment Problem (GAP) is the main task of an airport to ensure smooth flight-to-Gate assignment managing all disturbances. Or, flights schedule often undergoes some unplanned disruptions, such as weather conditions, gate availability or simply a delay that usually arises. A good plan to GAP should manage as possible stochastic events and include all in the planning of assignment. To build a robust model taking in account eventual planning disorder, a dynamic stochastic vision based on Markov Decision Process theory is designed. In this approach, gates are perceived as collaborative agents seeking to accomplish a specific set of flights assignment tasks as provided by a centralized controller. Multi-agent reasoning is then coupled with time dependence aptitude with both time-dependent action durations and stochastic state transitions. This reflection will enable setting up a new model for the GAP powered by a Time-dependent Multi-Agent Markov Decision Processes (TMMDP). The use of this model can provide to controllers at the airport a robust prior solution in every time sequence rather than bringing a risk of online schedule adjustments to handle uncertainty. The solution of this model is a set of optimal decisions time valuated to be made in each case of traffic disruption and at every moment.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2018.090247