CN108510106A - Airport security check flow optimization method based on queuing theory and generalized random petri net - Google Patents

Airport security check flow optimization method based on queuing theory and generalized random petri net Download PDF

Info

Publication number
CN108510106A
CN108510106A CN201810184141.1A CN201810184141A CN108510106A CN 108510106 A CN108510106 A CN 108510106A CN 201810184141 A CN201810184141 A CN 201810184141A CN 108510106 A CN108510106 A CN 108510106A
Authority
CN
China
Prior art keywords
safety check
customer
transition
library
tokken
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201810184141.1A
Other languages
Chinese (zh)
Inventor
朱晓敏
包卫东
张雄涛
吴冠霖
张国良
闫辉
陈俊杰
张耀鸿
周云
刘宝宏
周文
张亮
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
National University of Defense Technology
Original Assignee
National University of Defense Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by National University of Defense Technology filed Critical National University of Defense Technology
Priority to CN201810184141.1A priority Critical patent/CN108510106A/en
Publication of CN108510106A publication Critical patent/CN108510106A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/26Government or public services
    • G06Q50/265Personal security, identity or safety

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • Human Resources & Organizations (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Development Economics (AREA)
  • General Business, Economics & Management (AREA)
  • Computer Security & Cryptography (AREA)
  • Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Educational Administration (AREA)
  • General Health & Medical Sciences (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses an airport security check flow optimization method based on a queuing theory and a generalized random petri net, which comprises the following steps of: acquiring airport security check layout information, and constructing a security check flow model based on a queuing theory, a generalized random petri net and the security check layout information; acquiring airport security inspection historical information; the security inspection historical information comprises a customer arrival time interval and the time for a service desk to detect a target; substituting the security inspection historical information into a security inspection process model to perform simulation calculation to obtain a simulation result; comparing the simulation results, judging whether the results meet the expected effect, if not, correspondingly increasing security inspection resources in the transition corresponding to the library with the largest average token number or reducing security inspection resources in the transition corresponding to the library with the smallest average token number; the simulation calculation is continued until the desired effect is met. The method and the device can accurately and effectively realize optimization of airport security check processes, and improve security check efficiency and quality.

Description

A kind of airport security process optimization based on queueing theory and General Stochastic Petri Net Method
Technical field
The present invention relates to safety check workflow management correlative technology fields, particularly relate to a kind of random based on queueing theory and broad sense The airport security flow optimization method of petri nets.
Background technology
Airport security inspection is a component part of national communication infrastructure and a weight of Global Airports operation Want aspect.Due to the high value of Air transportation service, global airport is all different degrees of to be faced with by the attack of terrorism It threatens.In order to ensure that the journey safety of all passengers, airdrome control side have to spend a large amount of manpower and materials for safety check, and With being continuously increased for security process, the time needed for safety check is also increasing rapidly.After the outburst of 9-11 events, safety check flow, skill The related improvement of art, measure and relevant law etc. causes rapidly the extensive concern of the U.S. and other countries.Normal conditions Under, airdrome control department checks passenger and its luggage in security check point, to ensure all passengers during travelling Safety.But existing safety check flow receives criticism since the stand-by period is long.For passenger, in safety and facility Between to find a balance be very difficult.For client, carry out safety inspection is devoted a tremendous amount of time, will to navigate No matter sky travelling on time, money all seems sufficiently expensive.Therefore, under the premise of ensuring safety, optimize safety check flow pair Passenger and airline are all very favorable.
Current solution to this problem mainly has:First, analogue simulation is carried out with the method for discrete events simulation, this The service time of each information desk in system can be described in kind method, with very in queuing system and process optimization Extensively.Discrete events simulation, which can be good at the customer to regard an entity as, to be described, to record the reaching of customer, leave The service efficiency etc. of time and each workbench, but such issues that for airport security in, the luggage number of each passenger institute band It is uncertain, when inspection luggage of each passenger can be become multiple entities from an entity to be serviced, and next passenger examines It the service that a upper passenger is received such as first has to before looking into complete, and it is opposite to service number of units in discrete events simulation It is fixed, it is desirable to which that efficiency of service is relative complex from the point of view of changing Service Source number.
Another method:The method of petri network modellings analysis is suitable for use in computer scheduling of resource administrative analysis, this Kind method can analyze the various resource utilizations in system, but i.e. without concept of time also without triggering probability.Therefore Introduce the concept of time of the event occurrence rate and system of triggering transition, referred to as Stochastic Petri Nets.Country's external-open recently Beginning someone carries out analysis optimization using Stochastic Petri Nets to the production procedure of workpiece, but these methods are mainly profit With General Stochastic Petri Net come the Tokken number variation in research system, the handling capacity of Tokken in system can only be surveyed in this way Amount, for the time that a specific Tokken uses in systems, the priority arrival relationship of Tokken residing for library and service regulation without Method describes.Therefore not being suitable for this kind of customer of airport security had in the problem of quality of service requirement.
Therefore, current airport security has that the utilization of resources can not be unified with safety check efficiency.
Invention content
In view of this, a kind of based on the airport of queueing theory and General Stochastic Petri Net peace it is an object of the invention to propose Flow optimization method is examined, can accurately and effectively realize the optimization of airport security flow, improves safety check efficiency and quality.
Based on a kind of above-mentioned purpose airport security flow based on queueing theory and General Stochastic Petri Net provided by the invention Optimization method, including:
Airport security layout information is obtained, based on queueing theory, General Stochastic Petri Net and safety check layout information structure peace Examine procedural model;Wherein, the safety check procedural model includes Tokken, transition and library institute three elements;Customer represented by library is lined up position It sets;The transition indicate the information desk of customer;Tokken indicates customer and the luggage with fixed ID and timestamp, and luggage institute is right Ability trigger transition after Tokken ID corresponding to the Tokken ID answered and customer merges;Library is so the queue of first in first out cares for stack Visitor;
Obtain airport security historical information;Wherein, the safety check historical information includes customer arrival time interval and clothes It is engaged in the time used in platform detection target;
The safety check historical information is substituted into safety check procedural model and carries out simulation calculation, obtains simulation result;
Simulation result is compared, whether judging result meets desired effect, if being unsatisfactory for, then accordingly average Transition corresponding to the most library of Tokken quantity increase safety check resource or the transition corresponding to the minimum library of average Tokken number Reduce safety check resource;Continue simulation calculation until meeting desired effect.
Optionally, the safety check procedural model further includes trigger;The trigger is set to library institute outlet end, is used for table Show the triggering of transition;And the sum of probability is met for the triggering probability of the trigger of same library institute outlet end and is equal to 1.
Optionally, corresponding first library increases by one and changes at random before in the safety check procedural model, and give with Machine transition assign a random triggering probability, and when for occur every time new customer, random transition will be triggered.
Optionally, the safety check procedural model further includes customer analysis module, for for customer group in different airports Characteristic information, and then the corresponding relevant parameter adjusted in safety check procedural model;Wherein, the characteristic information includes nationality's letter Breath, gender information.
From the above it can be seen that the airport security provided by the invention based on queueing theory and General Stochastic Petri Net Flow optimization method is expanded using queuing theory Perti nets random to broad sense, one queue of increase residing for each library Concept realizes the monitoring to each Tokken life cycle in Petri network and initiation quantity variation to describe its precedence relationship, Finally obtain effective safety check procedural model.And it solves each to change corresponding service time in network and touch using queuing theory Hair probability is calculated, and calculating of the Markov Chain to transition times and probability is different from, and being calculated using queuing theory can be with Easily observe the influence to system migration come to the control strip of safety check resource.Therefore, the application being capable of accurate and effective Realization airport security flow optimization, improve safety check efficiency and quality.
In addition, the application also at least has the following effects that:(1) by combining queuing theory and Stochastic Petri Nets, The library of Petri network can be considered the queue of a Tokken, also by queuing theory to each changing corresponding touch in Petri network Hair probability and time provide new calculation.Petri network is innovated with theory, solves general Petri The problem of token precedence relationship can not describe in position in network.(2) method of workflow optimization is concentrated on greatly in the past Yield, and the present processes can be to service quality that the customer waited in airport is enjoyed equally object as an optimization. The stand-by period that may be needed to each customer in airport security flow is simulated, but unlike that general one Customer's whole process receives the queuing problem of service, and customer can become multiple objects to be serviced and customer itself in service process Receiving service concurrent simultaneously.(3) the triggering probability that transition are calculated with Markov Chain is compared, queuing system calculating is one white BOX Model can be very good control variable parameter monitoring system variation, once and this kind of black-box model problem pair of Markov Chain As transformation is with regard to needing to reconfigure.Accurate predictions and simulations effect can be obtained in the case where sufficient historical data expands Fruit, can be with extensive utilization in actual prediction.
Description of the drawings
Fig. 1 is the airport security flow optimization method one provided by the invention based on queueing theory and General Stochastic Petri Net The flow diagram of a embodiment;
Fig. 2 is common TSA safety checks flow diagram;
Fig. 3 is the basic petri pessimistic concurrency controls schematic diagram at safety check station provided by the invention;
Fig. 4 is the Generalized Stochastic Petri Net schematic diagram of multichannel Multiple server stations safe examination system provided by the invention;
Fig. 5 is the principle schematic provided by the invention that conversion time and toggle rate are obtained by queueing theory;
Fig. 6 is average traveler arrival time provided by the invention interval stochastic behaviour schematic diagram;
Fig. 7 is the arrival time spacing frequency schematic diagram of passenger provided by the invention;
Fig. 8 is that each passenger provided by the invention passes through the required time diagram of safety inspection;
The change schematic diagram that Fig. 9 occurs at any time and constantly for the queue length in the B of the corresponding regions Fig. 2;
Comparison schematic diagrams of the Figure 10 between close queue provided by the invention and loose queue;
Figure 11 is the difference schematic diagram of passenger's mean waiting time provided by the invention after different zones are jumped the queue.
Specific implementation mode
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference Attached drawing, the present invention is described in more detail.
It should be noted that all statements for using " first " and " second " are for differentiation two in the embodiment of the present invention The non-equal entity of a same names or non-equal parameter, it is seen that " first " " second " only for the convenience of statement, does not answer It is interpreted as the restriction to the embodiment of the present invention, subsequent embodiment no longer illustrates this one by one.
First choice is it should be noted that the application wants research safety to check the resource allocation problem in channel.First, using wide Adopted stochastic Petri net (GSPN) establishes safety check procedural model.Then, we are described by applying to queuing theory in GSPN Passenger traffic volume during airport security and its precedence relationship.On this basis, we can be very well in simulation safety check flow The safety check station stream of people handle up situation.In the case where ensureing that safety inspection project is constant, proposed to airport according to simulation result The suggestion that safety check flow optimizes.Generally speaking, present applicant proposes queueing theories and Petri network to be combined research work stream Method, and successfully solve the optimization problem of airport security flow.
Specifically, being the airport security flow provided by the invention based on queueing theory and General Stochastic Petri Net referring to Fig.1 The flow diagram of optimization method one embodiment.The airport security flow based on queueing theory and General Stochastic Petri Net Optimization method, including:
Step S1 obtains airport security layout information, based on queueing theory, General Stochastic Petri Net and safety check layout letter Breath structure safety check procedural model;Wherein, the safety check procedural model includes Tokken, transition and library institute three elements;Library is represented to be cared for Visitor is lined up position;The transition indicate the information desk of customer;Tokken indicates customer and the luggage with fixed ID and timestamp, and Ability trigger transition after Tokken ID corresponding to Tokken ID and customer corresponding to luggage merges;Library thus first in first out queue To stack customer;
Step S2 obtains airport security historical information;Wherein, the safety check historical information includes customer arrival time interval And the time used in information desk detection target;
The safety check historical information is substituted into safety check procedural model and carries out simulation calculation, obtains simulation result by step S3;
Step S4, simulation result is compared, and whether judging result meets desired effect, if being unsatisfactory for, then accordingly The libraries most in average Tokken quantity corresponding to transition increase safety check resource or average Tokken number it is minimum library institute it is right The transition answered reduce safety check resource;Continue simulation calculation until meeting desired effect.
In the application some optional embodiments, the safety check procedural model further includes trigger;The trigger is set It is placed in library institute outlet end, the triggering for indicating transition;And the triggering probability of the trigger of same library institute outlet end is met The sum of probability is equal to 1.
In the application some optional embodiments, corresponding first library increases by one before in the safety check procedural model A random transition, and a random triggering probability is assigned to random transition, it is random to become when for occur every time new customer Moving will be triggered.
In the application some optional embodiments, the safety check procedural model further includes customer analysis module, is used for needle To the characteristic information of customer group in different airports, and then the corresponding relevant parameter adjusted in safety check procedural model;Wherein, institute It includes nationality's information, gender information to state characteristic information.
By above-described embodiment it is found that the herein described airport security flow based on queueing theory and General Stochastic Petri Net Optimization method is expanded using queuing theory Perti nets random to broad sense, increases the concept of a queue residing for each library, To describe its precedence relationship, realizes the monitoring to each Tokken life cycle in Petri network and cause quantity variation, final To effective safety check procedural model.And it solves each to change corresponding service time and triggering probability in network using queuing theory It is calculated, is different from calculating of the Markov Chain to transition times and probability, can be easy to using queuing theory calculating Observe the influence to system migration come to the control strip of safety check resource.Therefore, the application can be realized accurately and effectively The optimization of airport security flow improves safety check efficiency and quality.
In order to clearly explain the main inventive concept of the application, the application is also disclosed in some embodiments and is mainly set Principle is counted, it is as follows:In general, the method for this kind of workflow optimization problem generally use Queuing network of safety check is ground Study carefully.One of classical way as operational research field, queueing theory have good applicability in research Random Service platform system aspects. In A.K.Erlang after 1909 are put forward for the first time the concept of queueing theory, Queuing network theory is also excellent initially as planning strategies in 1963 A part for change is proposed out.The scholars such as Shanthikumar use the flow-optimized problem of queuing network research work and acquirement Good result.2011, Stephen Louis Dorton used Queuing network and discrete events simulation in his paper Method has successfully completed the problem of about airport security process optimization.
During practical safety check, often exist each passenger can carry multiple luggage, also or multiple luggage simultaneously The case where corresponding multiple passengers.Although queuing theory has fabulous agreeing with property in Random Service platform service process research.But it is right " derivation " is presented between this kind of customer, and (it is to be subjected next that a customer becomes customer of multiple and different classifications etc. after service The service of information desk) phenomenon the problem of modeled and analyzed and will seem sufficiently complex.Based on this problem, also have both at home and abroad In the problem of many scholars start General Stochastic Petri Net being used for airport security process optimization.Not with petri pessimistic concurrency controls Disconnected development, petri networks be extended for possessing the time from simple resource scheduling model and trigger the broad sense of probability with Machine petri nets.It is very constructive that General Stochastic Petri Net, which is introduced this direction, but due to General Stochastic Petri Net Can not describe same library in the sequencings of different Tokkens therefore have priority arrival relationship for this kind of customer of airport security System describe there are certain defects.Between we want observation passenger when the abnormal behaviours such as existing " jumping the queue ", broad sense Stochastic Petri Nets can not just show so good desired effect.Therefore, we combine queuing theory and the random petri of broad sense Net, propose by library and its viewpoint that is combined with the concept of queue and information desk of corresponding trigger, to the row of constructing Team's General Stochastic Petri Net, to analyze and optimize this problem.
In the application some optional embodiments, specific analysis example is also disclosed, with United States Transportation Security office (TSA) it is studied for safety check flow.Its currently used safety check flow is as shown in Figure 2, can usually be divided For four main regions:Region A:By the passenger of preliminary examination and average traveler after arriving at the airport, respectively in preliminary examination channel and general It is waited in circulation passage.Then an optional identity veritifies platform and carries out identification check.Region B:It is general after confirming that identity is errorless Logical passenger and the passenger Jing Guo preliminary examination respectively enter in the safety inspection channel of corresponding classification and carry out safety inspection.Region C:By No abnormal passenger will take the luggage of oneself away in this region after safety inspection.Region D:It is found in safety inspection different Normal passenger will be trapped in the areas D and carry out detailed inspection, can be just allowed to enter in airport lounge after by inspection.
Based in single channel list information desk system, the passenger into safe examination system is considered by a source point production Raw and one meeting point of eventually off arrival.According to the currently used safety check flows of TSA, a single channel list clothes have been initially set up The petri pessimistic concurrency controls of business platform are as shown in Figure 3.It might as well assume that next customer starts when a upper customer receives the luggage of oneself Carry out safety check.Therefore, the capacity of library institute p3 and p5 is 1.Meanwhile when, there are when Tokken, the Tokken in p1 will not in p3 or p5 It can be changed.
Next, considering the safety check station model in the case of multichannel Multiple server stations, and it is drawn in Fig. 4.It is more in multichannel In information desk model, there are the identity veritification of multiple openings and a plurality of security check passage, thus passenger first can veritify platform from identity In it is optional one progress identity veritification, then in multiple security check passages select one progress safety check.In this model, establish Multiple libraries similar with p1 in Fig. 3 indicating to veritify the passengers to be checked such as platform j in identity.
Although traditional petri models can be good in safe examination system while property and concurrency feature is retouched It states.But it can not indicate triggering probability and transition times corresponding to each transition.Therefore, the application expands the model in Fig. 4 Exhibition is a General Stochastic Petri Net.To make each safety check platform machine security check passage in safety check flow have corresponding to it Transition times Δ tiAnd triggering probability λi
Set of trigger events is:
Each the triggering probability corresponding to trigger is:
In this General Stochastic Petri Net, as library institute p4c1l1In there are when Tokken, trigger t4c1l1And t5c1l1Institute Corresponding toggle rate will have following relationship:
Similarly, trigger t6c1l1And t7c1l1Also meet such condition.
Therefore, it is however generally that,
Further, it is contemplated that queueing theory reaches in description customer and has property on probation well in service process at random, and can With indicate well customer reach precedence relationship and queuing in receive service principle.In general, when being changed in petri nets Between and triggering probability obtained from timing statistics data and probability distribution.The probability that sets out of transition might as well be taken to be lined up equal to customer Arrival rate in system.So just service time corresponding with customer is identical for transition times.Fig. 5 is described to be obtained by queueing theory The principle of conversion time and toggle rate.
Process in order to which service is reached, received to customer is described, the library institute P of the application in Fig. 40Before plus Enter a random transition t '0To randomly generate the customer to arrive at the airport.Then, in conjunction with queue theory model to transition times Δ tkciliWith toggle rate λkcjljAssignment is carried out, and arrival time is assigned to distinguish to the Tokken for representing each customer and its luggage Precedence relationship.For changing t ' at random0Assign constant its transition times Δ t '0A=0 and corresponding random big toggle rate λ '0。 Whenever thering is a passenger to reach, t ' is changed0It is just triggered primary.In this way, in General Stochastic Petri Net transition times Δ t and Toggle rate λ corresponding to it can be calculated by the method for queueing theory.One is constructed on the basis of statistical data Polynary array, then wherein one element of uniformly random selection again.It can be basic according to corresponding state in the system of elements of selection It determines.Then Tokken in netting a customer and its corresponding multiple luggage with petri replaces.By to Tokken in system Transition rule be adjusted can well by the correlation between customer and luggage depict come.
Since the arrival of customer in airport often shows in Various Seasonal different periods the characteristic of multiple peak periods.Cause This, it is difficult to using general probability distribution description, it reaches characteristic.The application using SPSS to preliminary examination passenger in TSA statistical data and The stochastic behaviour at average traveler arrival time interval is analyzed.Analysis result is as shown in Figure 6 and Figure 7.According to result it is found that The value of all asymptotic conspicuousnesses is both less than 0.1.Therefore, average traveler arrival time interval is described simultaneously with common random probability distribution Not very rationally.Equally, the application can also verify other data and be described with common random probability distribution nor very rationally 's.Therefore, the application indicates that it reaches rule using the carry out random value of statistical data.
Next, the application simulates this model by writing C++ programs.Due to the inspection of preliminary examination passenger and revenue passenger It is the same in addition to putting down this part of luggage to look into process, and the application accounts for the passenger of both types respectively.It is false If the safety check scan channel of ordinary customer, the safety check scan channel of preliminary examination passenger and the quantity of identity card inspection station are respectively 9,3 With 12.According to these data, stand-by period of each passenger within a hour is simulated and has recorded, and show in fig. 8.
Compare for convenience, when the result (integer) according to emulation experiment calculates handling capacity, average latency and waits for Between variance.It obtains preliminary examination passenger and revenue passenger emulation comparison result is as shown in the table
The comparison of table 1. preliminary examination passenger and revenue passenger
As the results in table 1 show, preliminary examination passenger is in most cases less by the security check passage required time. In addition, the handling capacity of preliminary examination passenger is also larger than revenue passenger.But from the point of view of the average latency of passenger, in advance The stand-by period that inspection passenger faces fluctuates also bigger.
Before having a large amount of passengers to pour in system, each flow of safety check system can run well.In order to The bottleneck of safety check problem can be found from the links of safety check workflow.To in experiment customer reach generation data into Modification gone to improve the arrival rate of passenger.By experimental analysis, the difference that the length that B sectors arrange is stabbed at any time is changed Situation is showed with Fig. 9.
When throughput of system is less than 310, wait for the length of passenger's queue of safety check that can be fluctuated in specific level.One Denier handling capacity is more than this value, and the length of queue will fluctuate upwards.It means that the continuous increasing of the passengers quantity with arrival Add, the waiting list in the areas B will become more and more longer.Therefore, cause throughput of system that can not increase, cause the passenger's queue of safety check station The reason for the more arranging the more long is to change t2cili, t3cili, i.e., to the scanning of passenger and to the sweep test of luggage.
It, can be by changing the capacity of these bottlenecks where luggage scanning and scanning passenger are the bottleneck of safety check problem To improve the handling capacity of system.By shortening the priority of the corresponding transition times or adjustment process in these programs, to It is allowed to show outstanding than work at present method.
On the other hand, unique difference due to preliminary examination passenger and revenue passenger during safety check is just whether to need to go Lee is totally placed in this process on baggage scan frame, but the stand-by period variance bigger of preliminary examination passenger.Therefore, luggage is taken The process for going out scanning is also one of the main reason for fluctuation customer's average latency.In fact, all random processes are all The source that variance generates in system.It can be by further to operation sequence and checking process to the major limitation method of variance It standardizes to realize.
For a specific airport, luggage scanning checks that the data of most of flow such as file do not have obviously Variation.But the arrival situation of passenger is very likely different, such as dull season or 1 year busy season in different times, one day Peak.People from country variant culturally might have different behaviors and difference in character.These are likely to one Determine to influence the result that we analyze in degree.Therefore, customer's personality and behavior situation will be further discussed in we.
Different Culture background means different education experience and growth environment, it is however generally that from the most of same culture Number people's often shows certain similitude in some aspects of personality.The difference in character of one passenger is not enough to influence whole A airport security checks the state that system is shown, but the personality of many passengers may generate difference in systems.For example, Indian seems very crowded and urgent when waiting in line mostly, but American may get used to loose queue.Due to this The presence of species diversity, may be different to the review time of passenger.We are by slightly increasing or decreasing the transition of passenger Time compares different caused by these situations.Comparison closely between queue and loose queue is as shown in Figure 10.
The waiting time of passenger is more shorter than the passenger in more loose queue in more crowded queue.Therefore, Our model is for certain specific general character personality, for example those are happy to queue arranging to obtain close people, are sensitive.
Another common difference between culture be it is most of can be when the behaviors such as being lined up from people from different cultures It shows specifically to be accustomed to difference.American is famous with other people personal space of respect, has a kind of opposition " to insert in face of other people The social consensus of team ".But Chinese are well-known to pay the utmost attention to personal efficiency.Therefore, it is lined up more on the more airport of Chinese It is likely encountered " jumping the queue " situation.Although " jumping the queue " will not impact the entire throughput at safety check station, for other For the passenger waited in queue, after encountering " jumping the queue ", still to take more time.In order to simulate this case, The application changes customer with respect to Queue sequence in array obtained by several libraries that customer is lined up using the method for being inserted into element.Figure 11 show the difference of passenger's mean waiting time after different zones " jumping the queue ".
According to simulation result it is found that model is also sensitive to the simulation result of behaviors such as " jumping the queue ".
Therefore, generally speaking, the present processes are feasible.Petri network is suitable for description Asynchronous parallel computation machine system System model, and queueing theory is then the classical way for studying the stochastic service system course of work.What Petri network and queueing theory were combined Method is also a kind of feasible and effective method to workflow issues in research system.Especially when system asynchronous concurrent complicated or When the resource quantities such as the service station in system are changeable, and there are when precedence relationship for Tokken.
It is as follows according to the discussion of front and explanation, then the suggestion listed here to each airport:
Standardization:In order to reduce the variance of Customer waiting time, major airport should take the operation of strict standard Regulation.
Custom constraint:In order to reduce the variance of Customer waiting time and shorten the stand-by period, airport side should pass through Queue area situation is rationally designed to be lined up behavior that is even closer, and avoiding " jumping the queue " between customer.
The operation of profession:When changing corresponding transformation by training employee and employee to reduce each in petri nets Between.
High power capacity:Throughput of system is improved by increasing office worker's quantity and scanning device, especially body scanner.
Flexibly use resource:In order to limit the cost for increasing airport personnel and equipment, a feasible method is preparation one A little scan channels only opened in peak period.
More particularly passenger:In order to expand the handling capacity of security checkpoints, it is logical that more preliminary examination customers can be arranged in airport Road, and further increase the privilege of preliminary examination passenger.
By above-described embodiment it is found that the application at least has the following effects that:(1) by combining queuing theory and broad sense random Petri network, the library of Petri network can be considered the queue of a Tokken, also by queuing theory to each being changed in Petri network Corresponding triggering probability and time provide new calculation.Petri network is innovated with theory, solves one As the problem of token precedence relationship can not describe in position in petri net.(2) in the past big for the method for workflow optimization Concentrate on yield, and the present processes can be to service quality that the customer waited in airport is enjoyed equally as an optimization Object.The stand-by period that may be needed to each customer in airport security flow is simulated, but unlike that generally Customer's whole process receive the queuing problem of service, customer can become multiple objects and Gu to be serviced in service process Visitor itself receiving service concurrent simultaneously.(3) the triggering probability that transition are calculated with Markov Chain is compared, queuing system calculating is One whitepack model can be very good control variable parameter monitoring system variation, and this kind of black-box model of Markov Chain is once Problem objects transformation is with regard to needing to reconfigure.Accurately prediction and mould can be obtained in the case where sufficient historical data expands Quasi- effect, can be with extensive utilization in actual prediction.
Those of ordinary skills in the art should understand that:The discussion of any of the above embodiment is exemplary only, not It is intended to imply that the scope of the present disclosure (including claim) is limited to these examples;Under the thinking of the present invention, above example Or can also be combined between the technical characteristic in different embodiments, step can be realized with random order, and be existed such as Many other variations of the different aspect of the upper present invention, for simplicity, they are not provided in details.
The embodiment of the present invention be intended to cover fall within the broad range of appended claims it is all it is such replace, Modifications and variations.Therefore, all within the spirits and principles of the present invention, any omission, modification, equivalent replacement, the improvement made Deng should all be included in the protection scope of the present invention.

Claims (4)

1. a kind of airport security flow optimization method based on queueing theory and General Stochastic Petri Net, which is characterized in that including:
Airport security layout information is obtained, safety check stream is built based on queueing theory, General Stochastic Petri Net and safety check layout information Journey model;Wherein, the safety check procedural model includes Tokken, transition and library institute three elements;Customer represented by library is lined up position;Institute State the information desk that transition indicate customer;Tokken indicates customer and the luggage with fixed ID and timestamp, and corresponding to luggage Ability trigger transition after Tokken ID corresponding to Tokken ID and customer merges;Library is so customer is stacked in the queue of first in first out;
Obtain airport security historical information;Wherein, the safety check historical information includes customer arrival time interval and information desk Detect the time used in target;
The safety check historical information is substituted into safety check procedural model and carries out simulation calculation, obtains simulation result;
Simulation result is compared, whether judging result meets desired effect, if being unsatisfactory for, then accordingly in average Tokken Transition corresponding to the most library of quantity increase safety check resource or the transition corresponding to the minimum library of average Tokken number are reduced Safety check resource;Continue simulation calculation until meeting desired effect.
2. optimization method according to claim 1, which is characterized in that the safety check procedural model further includes trigger;Institute It states trigger and is set to library institute outlet end, the triggering for indicating transition;And touching for the trigger of same library institute outlet end Hair probability meets the sum of probability and is equal to 1.
3. optimization method according to claim 1, which is characterized in that corresponding first library institute in the safety check procedural model Increase a random transition before, and a random triggering probability is assigned to random transition, for so that occurring new care for every time When objective, random transition will be triggered.
4. optimization method according to claim 1, which is characterized in that the safety check procedural model further includes customer analysis mould Block for the characteristic information for customer group in different airports, and then adjusts the corresponding ginseng in safety check procedural model accordingly Number;Wherein, the characteristic information includes nationality's information, gender information.
CN201810184141.1A 2018-03-06 2018-03-06 Airport security check flow optimization method based on queuing theory and generalized random petri net Pending CN108510106A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810184141.1A CN108510106A (en) 2018-03-06 2018-03-06 Airport security check flow optimization method based on queuing theory and generalized random petri net

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810184141.1A CN108510106A (en) 2018-03-06 2018-03-06 Airport security check flow optimization method based on queuing theory and generalized random petri net

Publications (1)

Publication Number Publication Date
CN108510106A true CN108510106A (en) 2018-09-07

Family

ID=63377270

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810184141.1A Pending CN108510106A (en) 2018-03-06 2018-03-06 Airport security check flow optimization method based on queuing theory and generalized random petri net

Country Status (1)

Country Link
CN (1) CN108510106A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110765664A (en) * 2019-11-26 2020-02-07 北京首都国际机场股份有限公司 Security check efficiency optimization method based on simulation
CN112036053A (en) * 2020-09-04 2020-12-04 中国航空无线电电子研究所 Petri net-based airport surface sliding simulation and optimization method
CN113378416A (en) * 2021-08-16 2021-09-10 傲林科技有限公司 Event network simulation-based optimization method and device and computer equipment

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103632005A (en) * 2013-12-04 2014-03-12 中国航空综合技术研究所 Task reliability modeling method for failure reconfiguration process of dynamic reconfiguration system
CN106650985A (en) * 2016-09-12 2017-05-10 南京航空航天大学 Method for predicting the chain effect of abnormal flight derived event based on stochastic Petri nets
CN107730053A (en) * 2017-11-07 2018-02-23 民航成都信息技术有限公司 System model method for building up and device

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103632005A (en) * 2013-12-04 2014-03-12 中国航空综合技术研究所 Task reliability modeling method for failure reconfiguration process of dynamic reconfiguration system
CN106650985A (en) * 2016-09-12 2017-05-10 南京航空航天大学 Method for predicting the chain effect of abnormal flight derived event based on stochastic Petri nets
CN107730053A (en) * 2017-11-07 2018-02-23 民航成都信息技术有限公司 System model method for building up and device

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
冯小博等: "机场安检站优化乘客吞吐量研究", 《无线互联科技》 *
樊荣: "机场安检口客流量的优化", 《环球市场信息导报》 *
马宏飞等: "基于Petri网络的安检流程优化的研究", 《信息科学》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110765664A (en) * 2019-11-26 2020-02-07 北京首都国际机场股份有限公司 Security check efficiency optimization method based on simulation
CN112036053A (en) * 2020-09-04 2020-12-04 中国航空无线电电子研究所 Petri net-based airport surface sliding simulation and optimization method
CN112036053B (en) * 2020-09-04 2024-05-03 中国航空无线电电子研究所 Airport scene sliding simulation and optimization method based on Petri network
CN113378416A (en) * 2021-08-16 2021-09-10 傲林科技有限公司 Event network simulation-based optimization method and device and computer equipment

Similar Documents

Publication Publication Date Title
CN107086935B (en) People flow distribution prediction method based on WIFI AP
Manataki et al. A generic system dynamics based tool for airport terminal performance analysis
Madadi et al. Modeling and simulation of a bank queuing system
CN108510106A (en) Airport security check flow optimization method based on queuing theory and generalized random petri net
Ilk et al. Workforce management in omnichannel service centers with heterogeneous channel response urgencies
Thampan et al. Functional efficiency in airport terminals: A review on Overall and Stratified Service Quality
Lytvyn et al. Aviation aircraft planning system project development
Andreatta et al. A set of approximate and compatible models for airport strategic planning on airside and on landside
Laik et al. Predicting airline passenger load: A case study
Evdokimova et al. Coupled queues with customer impatience
Milne et al. Minimizing health risks as a function of the number of airplane boarding groups
CN115098564A (en) Passenger travel demand analysis method and system
Parlar et al. Event‐based allocation of airline check‐in counters: a simple dynamic optimization method supported by empirical data
Fayez et al. Managing airport operations using simulation
Khaleghi et al. Multi-period hub location problem considering polynomial time-dependent demand
Au et al. Establishing a three-step model of designing the polling stations for shorter queue and smaller waiting time: a case study using computer simulation
Ponickì et al. Possibilities of simulation tools for describing queuing theory and operations service lines in railway passenger transport
Wang et al. A multi-tier inspection queueing system with finite capacity for differentiated border control measures
Novrisal et al. Simulation of departure terminal in Soekarno-Hatta International airport
Trigos et al. A simulation-based heuristic that promotes business profit while increasing the perceived quality of service industries
Rolim et al. A method to evaluate determinant factors on airport check-in level of service
James et al. Development of model categories for performance improvement studies related to airport terminal operations
Nguyen et al. Mixture density networks as a general framework for estimation and prediction of waiting time distributions in queueing systems
Xie Optimizing the Passenger Throughput at an Airport Security Checkpoint
Ojirobe et al. AN ANALYSES ON PATIENTS’ QUEUING SYSTEM AT MUHAMMAD ABDULLAHI WASE SPECIALIST HOSPITAL, KANO

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20180907