CN109829658A - A kind of parking position distribution method based on different crowd demand - Google Patents

A kind of parking position distribution method based on different crowd demand Download PDF

Info

Publication number
CN109829658A
CN109829658A CN201910150870.XA CN201910150870A CN109829658A CN 109829658 A CN109829658 A CN 109829658A CN 201910150870 A CN201910150870 A CN 201910150870A CN 109829658 A CN109829658 A CN 109829658A
Authority
CN
China
Prior art keywords
crowd
parking
demand
destination
berth
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
Application number
CN201910150870.XA
Other languages
Chinese (zh)
Other versions
CN109829658B (en
Inventor
叶奕辰
温惠英
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.)
South China University of Technology SCUT
Original Assignee
South China University of Technology SCUT
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 South China University of Technology SCUT filed Critical South China University of Technology SCUT
Priority to CN201910150870.XA priority Critical patent/CN109829658B/en
Publication of CN109829658A publication Critical patent/CN109829658A/en
Application granted granted Critical
Publication of CN109829658B publication Critical patent/CN109829658B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a kind of parking position distribution methods based on different crowd demand, specifically: classification division is carried out to the service group in specified parking lot, then linear programming model is established according to the parking demand of different type crowd, solves the berth number that every a kind of crowd obtains;Different crowd is ranked up from more to few according to obtained berth number, then it successively chooses and is used as object, count the potential destination of the object, and it is successively sorted from big to small according to the frequency of occurrences arrived at the destination, after calculating the parking stall number that specific certain class crowd each destination should be equipped with, it is most short for foundation at a distance from destination with parking stall according to the collating sequence of destination, it is sequentially allocated the parking stall of respective number;The present invention facilitates the limited parking resource of reasonable distribution, can effectively limit and disorderly stop leaving about behavior, meet the parking demand of different service objects, can not only improve parking environment, moreover it is possible to improve people to the satisfaction of parking.

Description

A kind of parking position distribution method based on different crowd demand
Technical field
The present invention relates to transportation planning programs and management study field, in particular to a kind of to be stopped based on different crowd demand Vehicle berth allocation method.
Background technique
As China's socio-economic development and living standards of the people improve, vehicle guaranteeding organic quantity rapid growth, this allows parking The problems such as facility is less than, Allocation Efficiency is low increasingly shows.For the equilibrium of supply and demand assignment problem of parking, Wan Chongjie, Xu Jingfei establishes Varying Coefficients Linear plan model and is solved;Xu little Dan, Chen Jun are real with the Bi-level Programming Models of sharing policy The equilibrium of supply and demand now stopped;The bright equal thought for proposing block planning and administering of horse;It opens up to equal and then carries out parking stall with ZigBee technology Intelligent management and distribution.Although different scholars attempts to make solution to problem from different angles, without clear area Divide the service characteristic of different crowd, more this angle does not account for from the parking demand of different crowd, thus causes parking A series of problems, such as position deficiency, environmental pollution, traffic accidents.In addition, there are the principles of Priority Service in certain parking lots (such as Hospital parking lot is preferably emergency case's service, and school parking lot is preferably teaching and administrative staff's service), but often because not having in life Public vehicles outside restricted service range and the parking demand phase for causing parking resource in short supply that cannot be expected with people Match.Therefore, to achieve the purpose that Balance in parking supply and demand and Priority Service specific crowd, it is necessary to go to build from the angle of service group Found new parking position distribution method.
Summary of the invention
The shortcomings that it is a primary object of the present invention to overcome the prior art and deficiency provide a kind of based on different crowd demand Parking position distribution method;The problem of for background technique, the invention proposes segmentation service crowd and according to clothes The parking demand of business crowd redistributes existing parking resource, under the premise of guaranteeing Priority Service specific crowd, Certain parking stall is suitably opened to public vehicles.
The purpose of the present invention is realized by the following technical solution:
A kind of parking position distribution method based on different crowd demand, comprising the following steps:
S1, one is chosen according to the information of acquisition to the personnel's progress information collection for taking parking behavior in survey region Or multiple characteristics divide crowd, so that it is determined that service group classification number m;
S2, parking characteristics investigation is carried out to different service group classifications respectively, and obtains parking characteristics index;
S3, building linear programming model, measure and supply according to demand magnitude relation, choose adaptable objective function, and tie Constraint condition is closed, the planning Berth number C for obtaining each category services crowd is solvedi
S4, to planning Berth number CiIt is ranked up, using maximum planning Berth number as current service crowd i;
The all purposes that S5, statistics current service crowd i can be reached, and to destination frequency of occurrences FijIt is arranged Sequence, using the destination of the maximum frequency of occurrences as current destination j;
S6, the Berth number N that current service crowd i should be configured in current destination j is calculatedij, Nij=Ci·Fij, then count Calculate current service crowd i parking stall and current destination j distance D to be allocatedijk, and be ranked up to the distance obtained is calculated, The shorter preceding N of selected distanceijA berth allocation gives current service crowd;
S7, whether traverse with judging all purposes and finish, finished if not traversing, the frequency of occurrences of selected and sorted second It as the new maximum frequency of occurrences, and determines new current destination, goes to step S6;If traversal finishes, into next step;
S8, judge whether all service groups traverse and finish, finished if not traversing, the planning pool of selected and sorted second Digit determines new current service crowd as new planning Berth number, goes to step S5;If traversal finishes, knot is exported Fruit.
Further, the service group classification number m is positive integer, and i=1,2 ..., m.
Further, the information includes gender, age, occupation, monthly income.
Further, the parking characteristics index includes to obtain existing parking stall sum Z, and the parking of the i-th class personnel needs The amount of asking Ni, parking position turnover rate αi, berth wantage LiWith the idle amount M in berthi
Further, the parking position turnover rate αiAre as follows:
αi=Si/Ti,
Wherein, SiFor the practical parking capacity for investigating the i-th class of phase personnel, and TiFor the practical parking position number of the i-th class crowd Amount.
Further, the berth wantage LiAre as follows:
Lii·Ni-Ci,
Wherein, aiFor parking position turnover rate, ai=Si/Ti;SiFor the practical parking capacity of poll cycle the i-th class personnel, Ti For the practical parking position quantity of the i-th class crowd, NiFor the parking demand of the i-th class personnel;
The idle amount M in the berthiAre as follows:
Mi=max { Ci-Ni, 0 },
Wherein, CiFor the planning berth number of the i-th class crowd.
Further, the step S3 specifically:
In step S3,
The objective function of the linear programming model are as follows:
Wherein constraint condition are as follows:
Wherein, m is service group classification sum, and m >=1 and m are positive integer;I is the i-th class crowd, 1≤i≤m;CiIt is i-th The planning berth number of class crowd, Ci≥0;Z is existing parking position sum.
Further, the objective function of the linear programming model is chosen according to relation between supply and demand, specifically: work as demand Amount is greater than or equal to supply amount, then objective function are as follows:
When demand is less than supply amount, then objective function are as follows:
Compared with the prior art, the invention has the following advantages and beneficial effects:
The present invention goes to arrange parking stall according to the service characteristic and parking demand of crowd, can be more fully using existing The parking resource parking environment current with improvement, the public vehicles for facilitating the equilibrium of supply and demand and limiting outside service range enter, and are Parking area planning design and parking demand management, especially berth resource allocation provide a kind of new thinking, have practical Meaning.
Detailed description of the invention
Fig. 1 is a kind of method flow diagram of parking position distribution method based on crowd demand of the present invention;
Fig. 2 (a) is the field pattern that stops in embodiment of the present invention;
Fig. 2 (b) is the parking stall of current crowd and current destination 3 in embodiment of the present invention apart from calculating figure;
Fig. 2 (c) is the parking stall distribution diagram of current crowd and current destination 3 in embodiment of the present invention;
Fig. 2 (d) is the parking stall of current crowd and current destination 1 in embodiment of the present invention apart from calculating figure;
Fig. 2 (e) is the parking stall distribution diagram of current crowd and current destination 1 in embodiment of the present invention;
Fig. 2 (f) is finally to distribute schematic diagram in embodiment of the present invention.
Specific embodiment
Present invention will now be described in further detail with reference to the embodiments and the accompanying drawings, but embodiments of the present invention are unlimited In this.
Embodiment:
A kind of parking position distribution method based on crowd demand, as shown in Figure 1, specifically:
The linear programming model that the present invention establishes is provided first, it is assumed that has m class crowd, variable-definition is as follows:
The existing parking stall sum of Z-
CiThe planning parking position quantity of-the i-th class crowd, i=1,2 ..., m
NiThe parking demand of-the i-th class crowd, i=1,2 ..., m
αiThe parking position turnover rate of-the i-th class crowd, αi=Si/Ti, SiFor the practical parking for investigating the i-th class of phase crowd Amount, and TiFor the practical parking position quantity of the i-th class crowd, i=1,2 ..., m
LiThe wantage in the-the i-th class berth, the i.e. difference of demand and supply, Lii·Ni-Ci, i=1,2 ..., m
MiThe idle quantity in the-the i-th class berth, Mi=max { Ci-Ni, 0 }, i=1,2 ..., m
It is as follows model can be obtained:
It is that the relation between supply and demand obtained according to investigation is chosen about the objective function of model.When the need that investigation obtains The amount of asking is greater than or equal to supply amount, then the demand of certain a kind of crowd or a few class crowds cannot get or just met, so Objective function usesBerth wantage should be allowed as small as possible, allow more people that can stop as far as possible.When investigation obtains Demand be less than supply amount, then explanation drug on the market, extra berth is not utilized at this time, cause the waste of resource, Therefore it selectsIt as objective function, makes idle berth as few as possible, improves the utilization rate of resource.For constraining item PartAnd Ci>=0, the planning parking position number C of the i-th class crowdi, should be the integer more than or equal to 0, and summation should be less than Existing parking stall sum Z.In addition, the Optimized model belongs to linear programming model, because the order of constraint matrix is less than or equal to about The number of Shu Bianliang, so the model has solution.
Based on above discussion and Fig. 1, a kind of parking position distribution method based on different crowd demand include with Lower step:
Step 1
According to the classification number m of the destination determination service crowd drafted, which is any positive integer, is voluntarily set by user It is fixed.Such as in campus, crowd can be divided into teaching and administrative staff, student and guest, that is, determine m=3;It such as within the hospital, can be with Crowd is divided into medical worker, emergency case, general patient and the family members that visit a patient, that is, determines m=4.
Step 2
Parking characteristics investigation is carried out to every a kind of crowd and obtains serial index.Including obtaining existing parking stall sum Z, The parking demand N of i-th class personneli, parking position turnover rate αi, berth wantage LiWith the idle amount M in berthi.Wherein, i is positive Integer, value is between 1 and m.
For existing parking stall sum Z, indicate parking lot it is existing can receiving maximum capacity, unit be it is a, can be from Scene directly acquires the data.
For the planning berth number C of the i-th class crowdi, it is nonnegative integer, it is unknown quantity to be solved that unit, which is a,.Ci With the practical parking position quantity T of the i-th class crowdiThere is difference substantially, which is the parking demand by various people It calculates, value size can distinguish the importance of different crowd, provide foundation for the distribution of parking stall below.
For the parking demand N of the i-th class crowdi, the main parking demand for reflecting different crowd, unit be it is a, can be with Using common parking incidence model, Model On Relationship Analysis, motor vehicle OD predicted method and the volume of traffic-parking demand model etc. Solved, but no matter using where method, it is preferred that emphasis is different object crowds can be distinguished before analysis.
For the parking position turnover rate α of the i-th class crowdi, it illustrate during observation berth be repeated stopped it is flat Equal vehicle number reflects the producing level of parking facility, and its calculation formula is αi=Si/Ti.Wherein, SiTo investigate the i-th class of phase personnel Practical parking capacity, and TiFor the actual parking position quantity of the i-th class crowd, the two unit is a, and can be obtained from scene Access evidence.
For the berth wantage L of the i-th class crowdi, unit be it is a, its calculation formula is Lii·Ni-Ci
It leaves unused for the berth of the i-th class crowd and measures Mi, unit be it is a, its calculation formula is Mi=max { Ci-Ni, 0 }.
Step 3
Solve the planning Berth number C of every a kind of crowdi.The data of steps 1 and 2 are substituted into formula (1), by manually calculating or The parking position number C to match with every a kind of crowd can be obtained in special Mathematical software (such as Matlab and Lingo)i
Step 4
By from big to small to planning Berth number CiIt is ranked up, with CiMaximum value is current value and determines current service people Group i.
Step 5
With counting all purposes that current crowd i can be reached j, by from big to small to destination frequency of occurrences FijIt is arranged Sequence, with FijMaximum value is current value and determines current destination j.
Step 6
Calculate the parking stall number N that current crowd i should be equipped in current destination jijAfterwards, it calculates separately all unappropriated Parking stall and destination j distance Dijk(number that k indicates each parking stall), and by being ranked up from small to large, selected distance is shorter Preceding NijGive service group i in a parking stall.Specific calculating process is as follows:
Firstly, the Berth number N that current service crowd i should be configured in current destination jij=Ci·Fij
Then, for service group i, whole unallocated parking stalls are calculated at a distance from current destination j, with specific reference to offer Or the plane drawing of design, the geometric center of parking stall and destination to be allocated is marked first, then geometric center connecting the two, The length of obtained line segment is the parking stall at a distance from current destination j, which can be realized by computer or artificial measuring and calculating, It after all unallocated parking stalls are obtained at a distance from current destination j, is ranked up, is determined from small to large according to its numerical values recited Dijk(wherein, apart from shortest k=1, distance time short k=2, the k=3 short apart from third, and so on);
Finally, according to ranking results above-mentioned, the shorter preceding N of selected distanceijA unappropriated berth allocation is to current clothes Business crowd i.
Step 7
Judge whether all j traverse to finish, if so, 8 are gone to step, if it is not, then selected and sorted is only second to current FijIt is new FijIt as current value and determines new destination j, then goes to step 6.
Step 8
Judge whether all i traverse to finish, if so, output is as a result, entire iterative process terminates, if it is not, the then row of selection Sequence is only second to current CiNew CiIt as current value and determines new service group i, then goes to step 5.
Step 4 now provides specific example containing complicated loop structure to step 8 in order to be better described.
Assuming that existing 2 class crowd, i.e. i=1,2, obtained CiRespectively C1=10, C2=5;1st class crowd has 3 differences Destination, i.e. j=1,2,3, the frequency F after statisticsijRespectively F11=0.3, F12=0.2, F13=0.5;2nd class crowd has 2 A destination, wherein have a destination identical as the destination 2 of the 1st class, and another is different from destination above-mentioned, because This, is for the 2nd class crowd, j=2,4, the frequency after then counting is respectively F22=0.4, F24=0.6;It is above-mentioned for visual representation Data, available table 1.
According to step 4, C is determinediCurrent value is 10, and current service crowd is the 1st class crowd.In general, distribution obtains CiIt is bigger, illustrate that such crowd is more important, i.e. such crowd object for should be Priority Service, therefore, the 1st class crowd should be prior to 2nd class crowd is serviced.So next parking stall distribution is first since the 1st class crowd, the 1st class crowd is assigned Followed by the 2nd class crowd is allocated.
According to step 5, the destination that current crowd (the 1st class crowd) can reach is counted.In general, an individual is answered There are one or more intention destinations, by the frequency of the available different destinations of statistics Different Individual, but in order to preferably Parking stall is distributed, is then frequency by Frequancy digit conversion.Frequency is higher, shows that such crowd is bigger to the demand of the destination, such as F in upper example13Maximum, illustrating that crowd 1 arrives at the destination 3 demand can be higher than to destination 1 and destination 2, so distribution Should meet the needs of crowd 1 arrives the destination when specific parking stall first.
According to step 6, for 1 class crowd, the parking stall number that destination 3 should be equipped with is N13=10 × 0.5=5, then According to the parking stall in specific parking lot distribution and destination locations (such as Fig. 2 (a)), calculate between each parking stall and destination away from From that is, parking stall geometric center point is at a distance from the geometric center point of destination, such as Fig. 2 (b).Because there are 15 parking stalls, institute in parking lot With, k=1,2 ..., 15, and iteration coding in front and back will not repeat.From Fig. 2 (b) it is found that D136<D131<D137<D132<D138<D133< D139<D134<D1310<D135<D1314<D1315<D1312<D1311<D1313, therefore, 6,1,7,2,8 this 5 parking stalls is selected to distribute to the 1st Class crowd, such as Fig. 2 (c).
According to step 7, there is no traversals to finish (also surplus destination 1 and destination 2) by j, because of F11It is only second to F13, so It selects destination 1 as next destination, executes step 6 again, the parking stall number that can calculate destination 1 should be equipped with is N13=10 × 0.3=3, and D1111<D1112<D1113<D1114<D119<D1115<D1110<D113<D114<D115(such as Fig. 2 (d)), because This, selects 11,12,13 this 3 parking stalls to distribute to the 1st class crowd, such as Fig. 2 (e).Because there are no traversals to finish, selection Destination 2 is current destination and executes step 6 again, finally can distribute to the 1st class crowd for 14,15.
According to step 8, there are no traversals to finish by i, therefore the 2nd class crowd is selected to carry out distribution as above, and i traversal finishes Afterwards, shown in the result of final output such as Fig. 2 (f), so far, entire assigning process terminates.
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment Limitation, other any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present invention, It should be equivalent substitute mode, be included within the scope of the present invention.

Claims (8)

1. a kind of parking position distribution method based on different crowd demand, which is characterized in that comprise the steps of:
S1, one or is chosen more according to the information of acquisition to the personnel's progress information collection for taking parking behavior in survey region A characteristic divides crowd, so that it is determined that service group classification number m;
S2, parking characteristics investigation is carried out to different service group classifications respectively, and obtains parking characteristics index;
S3, building linear programming model, measure and supply according to demand magnitude relation, choose adaptable objective function, and combine about Beam condition solves the planning Berth number C for obtaining each category services crowdi
S4, to planning Berth number CiIt is ranked up, using maximum planning Berth number as current service crowd i;
The all purposes that S5, statistics current service crowd i can be reached, and to destination frequency of occurrences FijIt is ranked up, with The destination of the maximum frequency of occurrences is current destination j;
S6, the Berth number N that current service crowd i should be configured in current destination j is calculatedij, Nij=Ci·Fij, then calculate current Parking stall service group i to be allocated and current destination j distance Dijk, and to calculate obtain distance be ranked up, choose away from From shorter preceding NijA berth allocation gives current service crowd;
S7, whether traverse with judging all purposes and finish, finished if not traversing, the frequency of occurrences conduct of selected and sorted second The new maximum frequency of occurrences, and determine new current destination, go to step S6;If traversal finishes, into next step;
S8, judge whether all service groups traverse and finish, finished if not traversing, the planning Berth number of selected and sorted second It as new planning Berth number, and determines new current service crowd, goes to step S5;If traversal finishes, result is exported.
2. a kind of parking position distribution method based on different crowd demand according to claim 1, which is characterized in that institute Stating service group classification number is m, and m is positive integer, and i=1,2 ..., m.
3. a kind of parking position distribution method based on different crowd demand according to claim 1, which is characterized in that institute Stating information includes gender, age, occupation, monthly income.
4. a kind of parking position distribution method based on different crowd demand according to claim 1, which is characterized in that institute Stating parking characteristics index includes to obtain existing parking stall sum Z, the parking demand N of the i-th class personneli, parking position turnover Rate αi, berth wantage LiWith the idle amount M in berthi
5. a kind of parking position distribution method based on different crowd demand according to claim 4, which is characterized in that institute State parking position turnover rate αiAre as follows:
αi=Si/Ti,
Wherein, SiFor the practical parking capacity for investigating the i-th class of phase crowd, and TiFor the practical parking position quantity of the i-th class crowd.
6. a kind of parking position distribution method based on different crowd demand according to claim 4, which is characterized in that institute State berth wantage LiAre as follows:
Lii·Ni-Ci,
Wherein, aiFor parking position turnover rate, ai=Si/Ti;SiFor the practical parking capacity of poll cycle the i-th class personnel, TiIt is i-th The practical parking position quantity of class crowd, NiFor the parking demand of the i-th class personnel;
The idle amount M in the berthiAre as follows:
Mi=max { Ci-Ni, 0 },
Wherein, CiFor the planning berth number of the i-th class crowd.
7. a kind of parking position distribution method based on different crowd demand according to claim 6, which is characterized in that step In rapid S3,
The objective function of the linear programming model are as follows:
Wherein constraint condition are as follows:
Wherein, m is service group classification sum, and m >=1 and m are positive integer;I is the i-th class crowd, 1≤i≤m;CiFor the i-th class people The planning berth number of group, Ci≥0;Z is existing parking position sum.
8. a kind of parking position distribution method based on different crowd demand according to claim 7, which is characterized in that institute The objective function of linear programming model is stated to be chosen according to relation between supply and demand, specifically: when demand is greater than or equal to supply amount, Then objective function are as follows:
When demand is less than supply amount, then objective function are as follows:
CN201910150870.XA 2019-02-28 2019-02-28 Parking berth distribution method based on different crowd demands Active CN109829658B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910150870.XA CN109829658B (en) 2019-02-28 2019-02-28 Parking berth distribution method based on different crowd demands

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910150870.XA CN109829658B (en) 2019-02-28 2019-02-28 Parking berth distribution method based on different crowd demands

Publications (2)

Publication Number Publication Date
CN109829658A true CN109829658A (en) 2019-05-31
CN109829658B CN109829658B (en) 2023-06-20

Family

ID=66864849

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910150870.XA Active CN109829658B (en) 2019-02-28 2019-02-28 Parking berth distribution method based on different crowd demands

Country Status (1)

Country Link
CN (1) CN109829658B (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112652174A (en) * 2020-12-18 2021-04-13 中标慧安信息技术股份有限公司 Parking service control method and system based on face verification
CN113593289A (en) * 2021-06-25 2021-11-02 桂林电子科技大学 Method and system for sensing in-road parking conflict avoiding scheduling based on available parking position
CN113744553A (en) * 2020-05-27 2021-12-03 富泰华工业(深圳)有限公司 Parking space dynamic configuration method and device and computer readable storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104933480A (en) * 2015-06-10 2015-09-23 江苏省城市规划设计研究院 Parking supply-demand regulate and control coefficient based parking facility supply level prediction method
CN105829831A (en) * 2013-11-12 2016-08-03 三菱电机株式会社 Method for predicting destinations during travel
CN106408991A (en) * 2015-07-28 2017-02-15 何尧 Parking lot dynamic pricing method based on demand characteristics and parking lot utilization rate
CN107203523A (en) * 2016-03-16 2017-09-26 阿里巴巴集团控股有限公司 A kind of method and device of the attribute information in determination geographical position
CN109191896A (en) * 2018-10-17 2019-01-11 南京邮电大学 Personalized parking stall recommended method and system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105829831A (en) * 2013-11-12 2016-08-03 三菱电机株式会社 Method for predicting destinations during travel
CN104933480A (en) * 2015-06-10 2015-09-23 江苏省城市规划设计研究院 Parking supply-demand regulate and control coefficient based parking facility supply level prediction method
CN106408991A (en) * 2015-07-28 2017-02-15 何尧 Parking lot dynamic pricing method based on demand characteristics and parking lot utilization rate
CN107203523A (en) * 2016-03-16 2017-09-26 阿里巴巴集团控股有限公司 A kind of method and device of the attribute information in determination geographical position
CN109191896A (en) * 2018-10-17 2019-01-11 南京邮电大学 Personalized parking stall recommended method and system

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
叶奕辰等: "基于多目标优化的校园停车功能泊位规划", 《山西农经》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113744553A (en) * 2020-05-27 2021-12-03 富泰华工业(深圳)有限公司 Parking space dynamic configuration method and device and computer readable storage medium
CN112652174A (en) * 2020-12-18 2021-04-13 中标慧安信息技术股份有限公司 Parking service control method and system based on face verification
CN113593289A (en) * 2021-06-25 2021-11-02 桂林电子科技大学 Method and system for sensing in-road parking conflict avoiding scheduling based on available parking position
CN113593289B (en) * 2021-06-25 2023-02-28 桂林电子科技大学 Method and system for sensing in-road parking conflict avoidance scheduling based on available parking position state

Also Published As

Publication number Publication date
CN109829658B (en) 2023-06-20

Similar Documents

Publication Publication Date Title
Jiang et al. Optimal allocation of shared parking slots considering parking unpunctuality under a platform-based management approach
CN104951894B (en) Hospital&#39;s disease control intellectual analysis and assessment system
CN109829658A (en) A kind of parking position distribution method based on different crowd demand
CN107844915A (en) A kind of automatic scheduling method of the call center based on traffic forecast
CN109272364A (en) Automatic Valuation Modelling modeling method
CN106503869A (en) A kind of public bicycles dynamic dispatching method that is predicted based on website short-term needs
CN109636137A (en) Electric automobile charging station planning and distributing method and system based on step analysis
CN102081754B (en) Multi-expert dynamic coordination judging method and intellectualized aid decision support system
Barras et al. An operational urban development model of Cheshire
CN113327424B (en) Traffic demand prediction method and device and electronic equipment
CN113780808A (en) Vehicle service attribute decision optimization method based on flexible bus connection system line
CN108734413A (en) A kind of high ferro station road network evaluation method and device
CN107729555A (en) A kind of magnanimity big data Distributed Predictive method and system
CN110459050A (en) A kind of short-term bus passenger flow prediction technique based on hybrid decision tree
CN112418699A (en) Resource allocation method, device, equipment and storage medium
CN116629738A (en) Logistics path optimization method, related method, device, equipment and medium
CN112949997A (en) System and method for community portrayal in urban planning design
Kireyeva et al. A study on the distribution of information and high technology clusters: Kazakhstan's experience
Benzarti et al. Modelling approaches for the home health care districting problem
Węgrzyn Does experience exert impact on a public-private partnership performance? The case of Poland
Pezzella et al. A system approach to the optimal health-care districting
CN110288125A (en) It is a kind of based on the commuting method for establishing model of mobile phone signaling data and application
CN114091886A (en) Intelligent dispatching method and system for field operation of power supply station area
Schoepfle et al. A fast, network-based, hybrid heuristic for the assignment of students to schools
CN112417286A (en) Method and system for analyzing influence factors gathered by regional culture industry

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