Simulation modeling and analysis of check-in process based on Petri network under epidemic
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摘要:
疫情下机场航站楼增设的健康检测环节使值机流程用时变久，效率低下. 对某机场航站楼值机流程现状分析，建立基于Petri网值机流程的过程模型，可靠性试验验证模型的正确性. 研究发现：1）自助值机、网上值机和柜台值机方式均使旅客托运行李的时间过长；2）与柜台值机相比，其他两种值机方式旅客等待服务的时间更短，更多旅客选择. 最后提出通过增设自助托运设备或值机柜台的方式减少旅客排队等待时间，缓解和改善值机流程中的瓶颈环节.
Abstract:Under the normalization of the epidemic, the additional health detection link in the airport terminal has made the check-in process longer and inefficient. On the basis of analysis for current situation of check-in process of an airport terminal in China, a process model based on Petri network check-in process was established, and the correctness of the model was verified by reliability test. It is found that: 1) Self-service check-in, online check-in and counter check-in all make passengers check in their baggage for too long; 2) Compared with counter check-in, the other two check-in methods have a shorter waiting time for passengers to serve and more passengers choose. Finally, it is proposed to reduce the waiting time of passengers in line by adding self-service check-in machines or check-in counters, so as to alleviate and improve the bottleneck in the check-in process.
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Key words:
- terminal building /
- Petri network /
- check-in process /
- performance analysis /
- epidemic normalization
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图 4 与柜台值机过程
${{\rm{GSPN}}}{{{'}}}$ 模型同构的MCFigure 4. MC isomorphic to counter value process
$ {{\rm{GSPN}}}{{{'}}} $ model
图 5 与自助值机过程
$ {{\rm{GSPN}}}' $ 模型同构的MCFigure 5. MC isomorphic to self-service check-in process
$ {{\rm{GSPN}}}' $ model
图 6 与网上值机过程
$ {{\rm{GSPN}}}' $ 模型同构的MC（自助打印）Figure 6. MC (self-printing) isomorphic to online check-in process
$ {{\rm{GSPN}}}' $ model
图 7 与网上值机过程
$ {{\rm{GSPN}}}' $ 模型同构的MC（人工打印）Figure 7. MC (manually printed) isomorphic to online check-in process
$ {{\rm{GSPN}}}' $ model表 1 柜台值机过程稳定状态时的概率分布
Table 1. Probability distribution at steady state of counter check-in process
变量 概率值 变量 概率值 疫情前 疫情下 疫情前 疫情下 X1 0.03563 0.02473 X36 0.00157 0.00099 X2 — 0.14548 X37 0.00734 0.01027 X3 0.00419 0.00330 X38 0.00090 0.00097 X5 0.00150 0.00165 X39 0.00074 0.00069 X6 0.00321 0.00317 X40 0.00154 0.00129 X7 0.00121 0.00211 X41 0.00093 0.00076 X8 0.00005 0.00010 X42 0.00009 0.00007 X9 0.00001 0.00004 X43 0.00006 0.00003 X10 0.000005 0.00002 X45 0.06538 0.00469 X11 0.0000004 0.000002 X46 0.00241 0.00151 X12 0.00000001 0.00000006 X47 0.09024 0.11321 X23 0.00272 0.00153 X48 0.01417 0.01756 X25 0.02219 0.01555 X49 0.00761 0.00927 X26 0.01190 0.00758 X50 0.00808 0.00915 X27 0.03485 0.02650 X51 0.00286 0.00284 X28 0.00397 0.00310 X52 0.00022 0.00020 X29 0.00311 0.00246 X53 0.00761 0.00927 X30 0.00625 0.00499 X54 0.07322 0.08595 X31 0.00376 0.00300 X55 0.25971 0.29757 X32 0.00034 0.00027 X56 0.03754 0.04291 X33 0.00016 0.00009 X57 0.05890 0.01830 X35 0.04565 0.00319 X58 0.17818 0.12366 
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表 2 柜台值机过程各库所的平均托肯
Table 2. Average tokens for each depot of counter check-in process
库所 平均托肯数 库所 平均托肯数 疫情前 疫情下 疫情前 疫情下 i 0.03563 0.02473 P21 0.170265 0.060132 P1 — 0.14548 P22 0.01909 0.01325 P2 0.010175 0.010392 P23 0.13364 0.15209 P3 0 0 P25 0.01909 0.02173 P14 0.08909 0.06498 P26 0.01908 0.02173 P16 0.05892 0.01832 P27 0.089095 0.1014 P17 0.19103 0.15846 P28 0.26726 0.304172 P18 0.43698 0.454 P30 0.03819 0.04345 P19 0.00713 0.00495 P31 0.19362 0.04338 P20 0 0 o 0.17818 0.12366
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表 3 柜台值机过程各变迁的利用率
Table 3. Utilization rates for each variation of counter check-in process
变迁 利用率 变迁 利用率 疫情前 疫情下 疫情前 疫情下 t1 0.03563 0.02473 tTC 0.13364 0.15209 t2 — 0.14548 t27 0.01909 0.02173 t3 0.010175 0.010392 t28 0.01908 0.02173 tTB 0.08909 0.06498 t29 0.089095 0.1014 t18 0.05892 0.01832 tTD 0.26726 0.304172 t19 0.08415 0.02615 t33 0.03819 0.04345 t20 0.00713 0.00495 t34 0.0589 0.0183 t23 0.01909 0.01325 tA 0.17818 0.12366
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