CN110135721A - Train passengers based on the overload limitation dynamically inversely calculated are bought one's ticket after normal time dispatching method - Google Patents
Train passengers based on the overload limitation dynamically inversely calculated are bought one's ticket after normal time dispatching method Download PDFInfo
- Publication number
- CN110135721A CN110135721A CN201910384012.1A CN201910384012A CN110135721A CN 110135721 A CN110135721 A CN 110135721A CN 201910384012 A CN201910384012 A CN 201910384012A CN 110135721 A CN110135721 A CN 110135721A
- Authority
- CN
- China
- Prior art keywords
- station
- ticket
- normal time
- train
- buy
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 20
- 239000000284 extract Substances 0.000 claims abstract description 7
- 230000001447 compensatory effect Effects 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Train Traffic Observation, Control, And Security (AREA)
Abstract
Train passengers based on the overload limitation dynamically inversely calculated dispatching method of buying one's ticket after normal time includes add up the in real time specific passengers quantity in each station and classification, is extracted and the poll for each station presell that adds up, and dynamic is reverse to be calculated, scheduling termination condition judgement；The reverse calculating general requirement of dynamic is according to the specific passengers quantity in each station and the classification of adding up in real time, extract and add up it is each station presell poll, it is calculated when permission the last leg of setting out in advance to make arrangements buys one's ticket after normal time maximum quantity since real-time, until calculate allows next stop maximum quantity of buying one's ticket after normal time last in real time when setting out in advance to make arrangements, successively dynamic is calculated when all stations below between the next stop and the last leg of setting out in advance to make arrangements allow maximum quantity of buying one's ticket after normal time, the expression formula of all maximum quantity beam conditions that allow to buy one's ticket after normal time constitutes overall model, it must simultaneously meet, and dynamic updates, and belongs to dynamic model；Termination condition is to work as to set out in advance to make arrangements as the terminus of train.Its concept is simple, and it is convenient to realize, effectively buys one's ticket after normal time scheduling controlling to train passengers conducive to train passengers peak period.
Description
Technical field
The present invention relates to dispatching method technical fields, more particularly to the train based on the overload limitation dynamically inversely calculated multiplies
Visitor buys one's ticket after normal time dispatching method.
Background technique
Train (especially high-speed rail) has become one of most important vehicles of people's trip.Currently occur holding pre- in advance
Fixed train ticket (or high guaranteed votes) people can not climb up corresponding shift train because train (or high-speed rail) has overloaded, and seriously affect
Plan of travel.Cause to hold scheduled train ticket (or high guaranteed votes) people in advance because train (or high-speed rail) overloads to be unable to satisfy and climb up
The reason of corresponding shift train have it is very much, can only wherein most important the reason is that passenger can not buy the ticket of destination
Short distance ticket is bought, then gets on the bus and buys one's ticket after normal time, is become from " buy short multiply length " " mend length and multiplies length ", passenger is formed accumulative on train (or high-speed rail)
Property rise suddenly and sharply, ultimately form overload, thus occur holding in advance scheduled train ticket (or high guaranteed votes) people because train is (or high
Iron) corresponding shift train can not be climbed up by having overloaded.This be with overload limitation train passengers buy one's ticket after normal time scheduling face it is new
Project.
No dispatching method currently, the train passengers that there is overload to limit are bought one's ticket after normal time leads to the nothing that overloads because of train (or high-speed rail)
Method satisfaction holds scheduled train ticket (or high guaranteed votes) people in advance and climbs up corresponding shift train, can only take in full or have
Compensatory returned ticket, and apologize；And exist on the authoritative composition influence of train ticket (or high guaranteed votes).
Summary of the invention
In order to overcome the existing train passengers with overload limitation to buy one's ticket after normal time no dispatching method, cause because of train (or high-speed rail)
Overload, which is unable to satisfy, to be held scheduled train ticket (or high guaranteed votes) people in advance and climbs up corresponding shift train, can only be taken complete
Volume has compensatory returned ticket, and apologizes；And exist on train ticket (or high guaranteed votes) authoritative the defects of constituting influence, the present invention
Passengers quantity is calculated based on dynamic is reverse, the train passengers based on the overload limitation dynamically inversely calculated are provided and are bought one's ticket after normal time dispatching party
Method.
The present invention specifically solves technical solution used by its technical problem:
Train passengers based on the overload limitation dynamically inversely calculated are bought one's ticket after normal time dispatching method, including each station of adding up in real time has
Body passengers quantity and classification, are extracted and the poll for each station presell that adds up, in real time calculating allow the last leg to buy one's ticket after normal time when setting out in advance to make arrangements
Maximum quantity constraint condition, calculate allows the next stop to buy one's ticket after normal time maximum quantity constraint condition in real time when setting out in advance to make arrangements, and dynamic is reverse to be calculated, and adjusts
Spend termination condition judgement, the sum of bus stop on the way of train, train passengers maximum carrying capacity.The reverse calculating general requirement of dynamic is root
Add up the specific passengers quantity in each station and classification when factually, extracts and the poll for each station presell that adds up, and works as from real-time calculating
Setting out in advance to make arrangements allows the last leg maximum quantity of buying one's ticket after normal time to start, until calculate allows the next stop to buy one's ticket after normal time maximum quantity most in real time when setting out in advance to make arrangements
Afterwards, successively dynamic is calculated when all stations below between the next stop and the last leg of setting out in advance to make arrangements allow maximum quantity of buying one's ticket after normal time.It is specific to adjust
Spend step:
Step 1, add up the specific passengers quantity in each station and classification in real time: calculating Bi,j, Bi,jIndicate have when jth station to the
Real-time specific passenger that i gets off at station is as a result, note n indicates the sum of bus stop on the way of train, 1≤j < i≤n here, and i, j, n are equal
Belong to natural number；
Step 2, extract and add up it is each station presell poll: calculate Ci,j, Ci,jIndicate presell i-th when jth station
Real-time specific passenger that station is got on the bus is as a result, note n indicates the sum of bus stop on the way of train, 1≤j < i≤n here, and i, j, n are equal
Belong to natural number；
Step 3, calculate in real time when set out in advance to make arrangements allow thereafter each station buy one's ticket after normal time maximum quantity constraint condition: computation model is as follows
Here note is worked as and sets out in advance to make arrangements as jth station；Remember that T indicates train passengers maximum carrying capacity, be the quantity of train overload limitation, T belongs to
In natural number；Qn,jIt indicates to allow the last leg n to buy one's ticket after normal time maximum quantity constraint condition when next stop jth station；Qn-1,jIt indicates when setting out in advance to make arrangements the
The station j allows the previous station of the last leg n to buy one's ticket after normal time maximum quantity constraint condition；Qn-2,jIt indicates to allow the last leg n when next stop jth station
Preceding two station buy one's ticket after normal time maximum quantity constraint condition；Qj+1,jIt indicates to allow maximum number of buying one's ticket after normal time when+1 station of next stop jth at next stop jth station
Measure constraint condition；Three real dots " ... " indicate that the intermediate each station in the centre from the n-th -3 station to+2 station of jth of omitting allows maximum number of buying one's ticket after normal time
Measure the calculation expression of constraint condition；A and b, which is respectively indicated, indicates the station a and the station b, and a and b belong to natural number；
Step 4, dynamic is reverse calculates: each station in step 3 buy one's ticket after normal time maximum quantity constraint condition be since the last leg,
Successively reverse calculate to+1 station of jth of the next stop when next stop jth station allows maximum quantity of buying one's ticket after normal time, and the total station n-j allows to buy one's ticket after normal time most
The expression formula of big number constraint condition；The station n-j allow to buy one's ticket after normal time maximum quantity constraint condition expression formula on the one hand require this n-j stand
The expression formula of maximum quantity beam condition of allowing to buy one's ticket after normal time constitutes overall model, it is necessary to meet simultaneously, on the other hand add up each station
Specific passengers quantity and classification are that dynamic updates, and reflect the specific passengers quantity in each station and classification in real time, reflect that the total station n-j allows
The expression formula model for maximum quantity constraint condition of buying one's ticket after normal time belongs to dynamic model；
Step 5, scheduling termination condition judges: when next stop is the terminus of train；If when next stop jth station meet j≤
N-1 does not meet the scheduling termination condition of the entire Real-Time Scheduling task of defined, calculates according to dynamic is reverse, jumps to step
1；Otherwise meet j=n when next stop jth station, meet the scheduling termination condition of the entire Real-Time Scheduling task of defined, based on dynamic
State inversely calculate overload limitation train passengers buy one's ticket after normal time dispatching method termination.
The invention has the advantages that being bought one's ticket after normal time dispatching party using the train passengers based on the overload limitation dynamically inversely calculated
Method calculates passengers quantity by the way that dynamic is reverse, and solving, there are the train passengers of overload limitation to buy one's ticket after normal time no dispatching method at present,
Cause to overload because of train (or high-speed rail) be unable to satisfy hold scheduled train ticket (or high guaranteed votes) people in advance climb up it is corresponding
Shift train can only be taken in full or have compensatory returned ticket, and apologize；And exist to the authoritative structure of train ticket (or high guaranteed votes)
The problems such as at influencing.Its concept is simple, and it is convenient to realize, robustness is high, and it is effectively right to be adapted to train (or high-speed rail) passenger peak period
Train passengers are bought one's ticket after normal time the current demand of scheduling.
Detailed description of the invention
Fig. 1 is dispatching method flow chart of buying one's ticket after normal time the present invention is based on the train passengers of the overload limitation dynamically inversely calculated.
Specific embodiment
The invention patent is further described with reference to the accompanying drawings and examples:
Train passengers provided by the present invention based on the overload limitation dynamically inversely calculated are bought one's ticket after normal time dispatching method, including reality
When add up the specific passengers quantity in each station and classification, extract and the poll for each station presell that adds up, calculate permit when setting out in advance to make arrangements in real time
Perhaps the last leg is bought one's ticket after normal time maximum quantity constraint condition, and calculate allows the next stop to buy one's ticket after normal time maximum quantity constraint condition in real time when setting out in advance to make arrangements,
Dynamic is reverse to be calculated, scheduling termination condition judgement, the sum of bus stop on the way of train, train passengers maximum carrying capacity.Wherein, attached drawing
In six dots " ... " indicate when the last leg set out in advance to make arrangements and all stations that do not listed between the next stop behind set out in advance to make arrangements
Allow to buy one's ticket after normal time maximum quantity constraint condition；The reverse calculating general requirement of dynamic is according to each specific passengers quantity in station that adds up in real time
And classification, it extracts and the poll for each station presell that adds up, allows the last leg to buy one's ticket after normal time maximum quantity when setting out in advance to make arrangements from real-time calculate
Start, until calculate allows the next stop to buy one's ticket after normal time maximum quantity finally, successively dynamic calculates under setting out in advance to make arrangements below in real time when setting out in advance to make arrangements
All stations between one station and the last leg allow maximum quantity of buying one's ticket after normal time.Specific scheduling steps:
Step 1, add up the specific passengers quantity in each station and classification in real time: calculating Bi,j, Bi,jIndicate have when jth station to the
Real-time specific passenger that i gets off at station is as a result, note n indicates the sum of bus stop on the way of train, 1≤j < i≤n here, and i, j, n are equal
Belong to natural number；
Step 2, extract and add up it is each station presell poll: calculate Ci,j, Ci,jIndicate presell i-th when jth station
Real-time specific passenger that station is got on the bus is as a result, note n indicates the sum of bus stop on the way of train, 1≤j < i≤n here, and i, j, n are equal
Belong to natural number；
Step 3, calculate in real time when set out in advance to make arrangements allow thereafter each station buy one's ticket after normal time maximum quantity constraint condition: computation model is as follows
Here note is worked as and sets out in advance to make arrangements as jth station；Remember that T indicates train passengers maximum carrying capacity, be the quantity of train overload limitation, T belongs to
In natural number；Qn,jIt indicates to allow the last leg n to buy one's ticket after normal time maximum quantity constraint condition when next stop jth station；Qn-1,jIt indicates when setting out in advance to make arrangements the
The station j allows the previous station of the last leg n to buy one's ticket after normal time maximum quantity constraint condition；Qn-2,jIt indicates to allow the last leg n when next stop jth station
Preceding two station buy one's ticket after normal time maximum quantity constraint condition；Qj+1,jIt indicates to allow maximum number of buying one's ticket after normal time when+1 station of next stop jth at next stop jth station
Measure constraint condition；Three real dots " ... " indicate that the intermediate each station in the centre from the n-th -3 station to+2 station of jth of omitting allows maximum number of buying one's ticket after normal time
Measure the calculation expression of constraint condition；A and b, which is respectively indicated, indicates the station a and the station b, and a and b belong to natural number；
Step 4, dynamic is reverse calculates: each station in step 3 buy one's ticket after normal time maximum quantity constraint condition be since the last leg,
Successively reverse calculate to+1 station of jth of the next stop when next stop jth station allows maximum quantity of buying one's ticket after normal time, and the total station n-j allows to buy one's ticket after normal time most
The expression formula of big number constraint condition；The station n-j allow to buy one's ticket after normal time maximum quantity constraint condition expression formula on the one hand require this n-j stand
The expression formula of maximum quantity beam condition of allowing to buy one's ticket after normal time constitutes overall model, it is necessary to meet simultaneously, on the other hand add up each station
Specific passengers quantity and classification are that dynamic updates, and reflect that the specific passengers quantity in each station and classification, the total station n-j allow to buy one's ticket after normal time in real time
The expression formula model of maximum quantity constraint condition belongs to dynamic model；
Step 5, scheduling termination condition judges: when next stop is the terminus of train；If when next stop jth station meet j≤
N-1 does not meet the scheduling termination condition of the entire Real-Time Scheduling task of defined, calculates according to dynamic is reverse, jumps to step
1；Otherwise meet j=n when next stop jth station, meet the scheduling termination condition of the entire Real-Time Scheduling task of defined, based on dynamic
State inversely calculate overload limitation train passengers buy one's ticket after normal time dispatching method termination.
Claims (2)
- The dispatching method 1. train passengers based on the overload limitation dynamically inversely calculated are bought one's ticket after normal time, including each station of adding up in real time are specific Passengers quantity and classification, are extracted and the poll for each station presell that adds up, in real time calculating allow the last leg to buy one's ticket after normal time most when setting out in advance to make arrangements Big number constraint condition, calculate allows the next stop to buy one's ticket after normal time maximum quantity constraint condition in real time when setting out in advance to make arrangements, and dynamic is reverse to be calculated, scheduling Termination condition judgement, the sum of bus stop on the way of train, train passengers maximum carrying capacity, which is characterized in that the reverse calculating of dynamic is total Body require to be extracted and the poll for each station presell that adds up according to the specific passengers quantity in each station and the classification of adding up in real time, from Calculate in real time allows the last leg maximum quantity of buying one's ticket after normal time to start when setting out in advance to make arrangements, until calculate allows the next stop to buy one's ticket after normal time in real time when setting out in advance to make arrangements Maximum quantity is finally, successively dynamic is calculated when all stations below between the next stop and the last leg of setting out in advance to make arrangements allow maximum number of buying one's ticket after normal time Amount, specific scheduling steps:Step 1, add up the specific passengers quantity in each station and classification in real time: calculating Bi,j, Bi,jIndicate have when jth station to the i-th station The real-time specific passenger to get off is as a result, note n indicates the sum of bus stop on the way of train, 1≤j < i≤n, and i, j, n are belonged to certainly So number；Step 2, extract and add up it is each station presell poll: calculate Ci,j, Ci,jIt indicates when jth station on the i-th station of presell The real-time specific passenger of vehicle is as a result, note n indicates the sum of bus stop on the way of train, 1≤j < i≤n, and i, j, n belong to nature Number；Step 3, calculate in real time when set out in advance to make arrangements allow thereafter each station buy one's ticket after normal time maximum quantity constraint condition: computation model is as followsNote, which is worked as, sets out in advance to make arrangements as jth station；Remember that T indicates train passengers maximum carrying capacity, be the quantity of train overload limitation, T belongs to natural number； Qn,jIt indicates to allow the last leg n to buy one's ticket after normal time maximum quantity constraint condition when next stop jth station；Qn-1,jIt indicates to allow most when next stop jth station It buys one's ticket after normal time maximum quantity constraint condition at the previous station of latter station n；Qn-2,jIt indicates to allow preceding two station of the last leg n when next stop jth station It buys one's ticket after normal time maximum quantity constraint condition；Qj+1,jIndicate when next stop jth station+1 station of next stop jth allow to buy one's ticket after normal time maximum quantity constraint item Part；Three real dots " ... " indicate that the intermediate maximum quantity that allows to buy one's ticket after normal time of each station among from the n-th -3 station to+2 station of jth that omits constrains item The calculation expression of part；A and b, which is respectively indicated, indicates the station a and the station b, and a and b belong to natural number；Step 4, dynamic is reverse calculates: the maximum quantity constraint condition of buying one's ticket after normal time of each station in step 3 is since the last leg, successively Reverse calculate to+1 station of jth of the next stop when next stop jth station allows maximum quantity of buying one's ticket after normal time, and the total station n-j allows maximum number of buying one's ticket after normal time Measure the expression formula of constraint condition；Step 5, scheduling termination condition judges: when next stop is the terminus of train；If meeting j≤n-1 when next stop jth station, The scheduling termination condition for not meeting the entire Real-Time Scheduling task of defined calculates according to dynamic is reverse, jumps to step 1；It is no Then meet j=n when next stop jth station, meet the scheduling termination condition of the entire Real-Time Scheduling task of defined, is based on dynamic inverse To calculating overload limitation train passengers buy one's ticket after normal time dispatching method terminate.
- The dispatching method 2. train passengers according to claim 1 based on the overload limitation dynamically inversely calculated are bought one's ticket after normal time, Be characterized in that, the station n-j allow to buy one's ticket after normal time maximum quantity constraint condition expression formula on the one hand require this station n-j to allow to buy one's ticket after normal time most The expression formula of big quantity beam condition constitutes overall model, it is necessary to meet simultaneously, on the other hand add up each specific ridership in station Amount and classification are that dynamic updates, and reflect that the specific passengers quantity in each station and classification, the total station n-j allow to buy one's ticket after normal time maximum quantity about in real time The expression formula model of beam condition belongs to dynamic model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910384012.1A CN110135721B (en) | 2019-05-09 | 2019-05-09 | Train passenger ticket supplementing scheduling method based on overload limitation of dynamic reverse calculation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910384012.1A CN110135721B (en) | 2019-05-09 | 2019-05-09 | Train passenger ticket supplementing scheduling method based on overload limitation of dynamic reverse calculation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110135721A true CN110135721A (en) | 2019-08-16 |
| CN110135721B CN110135721B (en) | 2022-04-26 |
Family
ID=67576970
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910384012.1A Active CN110135721B (en) | 2019-05-09 | 2019-05-09 | Train passenger ticket supplementing scheduling method based on overload limitation of dynamic reverse calculation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110135721B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114282740A (en) * | 2021-09-07 | 2022-04-05 | 内蒙古大学 | High-speed rail ticket amount distribution optimization method considering flexible tickets |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101635045A (en) * | 2009-08-05 | 2010-01-27 | 郝晓谷 | Railway ticket system and work method thereof |
| EP2835767A1 (en) * | 2013-08-06 | 2015-02-11 | Skidata Ag | Customer medium for detecting the use of services |
| CN104463656A (en) * | 2014-12-09 | 2015-03-25 | 北海和思科技有限公司 | Timely information updating method for railway station ticketing system |
| CN104765799A (en) * | 2015-03-27 | 2015-07-08 | 王鸿宾 | Intelligent quick self-service ticket-supplementing querying system |
| WO2016015454A1 (en) * | 2014-07-29 | 2016-02-04 | 刘健 | Automatic ticket selling and checking system for railway train |
| CN105321211A (en) * | 2014-07-16 | 2016-02-10 | 夏小叶 | Real-time train capacity query method and system |
| WO2017006006A1 (en) * | 2015-07-03 | 2017-01-12 | Metrolab | Method and system for managing the traffic of a line of vehicles travelling between several station stops |
-
2019
- 2019-05-09 CN CN201910384012.1A patent/CN110135721B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101635045A (en) * | 2009-08-05 | 2010-01-27 | 郝晓谷 | Railway ticket system and work method thereof |
| EP2835767A1 (en) * | 2013-08-06 | 2015-02-11 | Skidata Ag | Customer medium for detecting the use of services |
| CN105321211A (en) * | 2014-07-16 | 2016-02-10 | 夏小叶 | Real-time train capacity query method and system |
| WO2016015454A1 (en) * | 2014-07-29 | 2016-02-04 | 刘健 | Automatic ticket selling and checking system for railway train |
| CN104463656A (en) * | 2014-12-09 | 2015-03-25 | 北海和思科技有限公司 | Timely information updating method for railway station ticketing system |
| CN104765799A (en) * | 2015-03-27 | 2015-07-08 | 王鸿宾 | Intelligent quick self-service ticket-supplementing querying system |
| WO2017006006A1 (en) * | 2015-07-03 | 2017-01-12 | Metrolab | Method and system for managing the traffic of a line of vehicles travelling between several station stops |
Non-Patent Citations (2)
| Title |
|---|
| JITAO LI: "Microscopic simulation on ticket office of large scale railway passenger station", 《7TH ADVANCED FORUM ON TRANSPORTATION OF CHINA (AFTC 2011)》 * |
| 朱金福 等: "航空客运舱位控制和超售综合动态建模研究", 《系统工程学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114282740A (en) * | 2021-09-07 | 2022-04-05 | 内蒙古大学 | High-speed rail ticket amount distribution optimization method considering flexible tickets |
| CN114282740B (en) * | 2021-09-07 | 2022-09-23 | 内蒙古大学 | High-speed rail ticket amount distribution optimization method considering flexible tickets |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110135721B (en) | 2022-04-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108536965B (en) | Urban rail transit line operation service reliability calculation method | |
| CN104637334B (en) | A kind of bus arrival time real-time predicting method | |
| CN107947244B (en) | New energy power station grid-connected power advanced control method | |
| CN113635945B (en) | Train operation diagram adjusting method and device | |
| CN108173293A (en) | Meter and the new energy active power output maximum value on-line calculation method of operation of power networks constraint | |
| CN105354786A (en) | Carbon emission reduction based quantification method for environmental benefits of urban rail transit | |
| CN103279669A (en) | Method and system for simulating calculation of transport capacity of urban rail transit network | |
| CN106203657A (en) | A kind of reservation based on system APP of hiring a car estimating electricity is hired a car method | |
| CN110135721A (en) | Train passengers based on the overload limitation dynamically inversely calculated are bought one's ticket after normal time dispatching method | |
| CN109920252A (en) | A kind of coordination optimizing method and system of electrical traffic interacted system | |
| CN112819316A (en) | Hub transportation energy identification method of comprehensive passenger transport hub rail transit system | |
| CN109064076A (en) | Multi-mode public transportation mode selection method based on prospect theory | |
| CN103489060A (en) | Shift method capable of ensuring relative fairness of shift | |
| CN110390479A (en) | Bus time of departure dispatching method, equipment, storage medium and device | |
| CN104809543B (en) | Power system operating mode generation method based on monthly power transmission and transforming equipment repair schedule | |
| CN109902966A (en) | A kind of user ranking method and system | |
| CN109685492A (en) | A kind of public transport mode of payment and device | |
| CN108609031A (en) | The implementation method and device of train arrival reminding | |
| CN108090626A (en) | A kind of Meshing Method of distribution net gridding planning | |
| Liu et al. | A note on transit coordination using integer-ratio headways | |
| Cudahy | Whither Deregulation: A look at the Portents | |
| CN107316090A (en) | A kind of intelligent bus booking method | |
| Lebedeva et al. | Modeling of public transport waiting time indicator for the transport network of a large city | |
| CN106603295A (en) | SaaS service content determination method and system | |
| CN106295826A (en) | WEB client side carries out preengaging the method hired a car based on reservation time of chartering mileage |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |