The Research Of Boarding Strategy Efficiency Based On Cellular Automata

For airlines,the efficiency of aircraft turnover,which is closely related to operational efficiency and operating costs,is a crucial factor in winning the competition.The boarding process is a critical path in the turnover,which takes 1/3 of the turnover time.Therefore,adopting a reasonable strategy which can improve boarding efficiency is an effective way to improve operational efficiency and reduce operating costs.In order to explore the efficiency of different boarding strategies,boarding interference model,boarding process simulation,and strategy efficiency analysis are studied based on cellular automaton.At first,an interference time model considering the characteristics of passengers and luggage is constructed through the high fidelity simulation experiment which is designed to explore the formation mechanism and time rule of the aisle interference.Secondly,referring to the domestic large airport check-in process and passengers arriving regularity,the paper puts forward a feasible way to organize passenger boarding,and realizes the whole process simulation together with its validity test from the boarding area to the cabin.And on this basis,the efficiency of 8 strategies are analyzed according to the 3 indicators.Furthermore,the robustness of boarding strategies are discussed with different gate opening intervals,passenger age distribution and baggage specification distribution,etc.The results show that the relative efficiency and robustness of different strategies are mainly influenced by the difference of boarding order between strategies.Using orderly strategy instead of random boarding can reduce the time by 20%~35%.Strategies that can make full use of corridor space,such as OI3 and RP4,have higher efficiency.In terms of robustness,RP4,OI3,HB3 and Random perform better,which can be applied to more actual boarding scenes.Particularly,HB3 and Random are better options when considering the efficiency of boarding,strategic robustness and the actual demand of passengers.