CN108764562B - Self-service tax handling point deployment method based on trajectory analysis - Google Patents

Self-service tax handling point deployment method based on trajectory analysis Download PDF

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CN108764562B
CN108764562B CN201810508651.XA CN201810508651A CN108764562B CN 108764562 B CN108764562 B CN 108764562B CN 201810508651 A CN201810508651 A CN 201810508651A CN 108764562 B CN108764562 B CN 108764562B
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樊凯
徐兵兵
李铁军
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Abstract

The invention discloses a self-service tax handling point deployment method based on trajectory analysis, which comprises the following steps: firstly, gridding an urban road map to obtain the average time consumption among grids; extracting tax clerk tracks, and extracting a searching sub-track, a tax handling sub-track and other sub-tracks according to track information; the other sub-tracks are tracks of tax clerks for processing non-tax services before tax processing; and determining the optimal tax handling points through the extracted tracks, and calculating the number of tax handling machines required to be deployed at each tax handling point according to the queuing time of tax handling personnel. Compared with the prior art, the self-service tax payment point deployment method based on the trajectory analysis provides convenience for tax clerks to find self-service tax payment points nearby, and greatly reduces the time consumed by the tax clerks for finding self-service tax payment points.

Description

Self-service tax handling point deployment method based on trajectory analysis
Technical Field
The invention relates to the technical field of tax handling, in particular to a self-service tax handling point deployment method based on trajectory analysis.
Background
Along with the continuous increase of the number of enterprises, the number of enterprise tax clerks is continuously enlarged, and the traditional window tax trial has been more and more unable to meet the tax clerk's tax handling requirements. In order to meet the requirement of fast tax handling of tax handling personnel, self-service tax handling points are produced. However, at present, the self-service tax transaction points are mostly arranged inside tax bureaus or in busy places in urban areas. If the self-service tax administration points are intensively deployed, inconvenience is caused to most tax administration personnel. If the self-service tax administration point is deployed in a busy city area, on one hand, convenience cannot be provided for most tax administration personnel, and on the other hand, further traffic jam can be caused. How to select an appropriate place to deploy the self-service tax handling machine becomes an urgent problem.
Under a common condition, when tax handling personnel handles tax, the vehicle is driven to a tax handling window (or a self-service tax handling point) to handle the tax, and the corresponding track data can be acquired through a GPS (global positioning system) of the vehicle of the tax handling personnel. At present, the track data is deeply researched, very accurate analysis can be performed according to the track data, and therefore the self-service tax handling point deployment method based on the track analysis is provided on the basis of the track.
Disclosure of Invention
Aiming at the defects, the technical task of the invention is to provide a self-service tax handling point deployment method which is strong in practicability and based on trajectory analysis.
A self-service tax handling point deployment method based on trajectory analysis is realized by the following steps:
firstly, gridding an urban road map to obtain average time consumption among grids;
secondly, extracting a tax clerk track, and extracting a searching sub-track, a tax handling sub-track and other sub-tracks according to track information, wherein the track is composed of a series of points in space, the points comprise ID, longitude, latitude and timestamp information of the track, and the searching sub-track is used for searching a track of self-service tax handling points for the tax clerk; the tax handling sub-track is a track for starting to handle business at a self-service tax handling point by a tax handling person; the other sub-tracks are tracks of tax clerks for processing non-tax services before tax processing;
and thirdly, determining the optimal tax handling points through the extracted tracks, and calculating the number of tax handling machines required to be deployed at each tax handling point according to the queuing time of tax handling personnel.
The implementation process of the first step is as follows: firstly, dividing the road map into grids, obtaining the time consumed between each two adjacent grids, further obtaining an n multiplied by n matrix T, and calculating the shortest time between the two grids according to the matrix.
The specific operation process of the first step is as follows:
the average time-consuming matrix of the road grid is T, and two grids giTo gjThe average elapsed time between runs is as follows:
Figure BDA0001672262010000021
wherein v isijRepresents the sum of all meshes, t, that need to be passed between two meshesij(k) Representing the average time consumption of a single grid; correspondingly, the secondary grid g can be calculated according to the formulaiTo grid gjShortest path between CijAnd C is the shortest time consuming matrix.
Determining the optimal tax handling point in the third step refers to obtaining K newly-added self-service tax handling sites through knowing L existing self-service tax handling sites, roads and track sets, wherein the newly-added self-service tax handling sites are obtained by minimizing the time consumed by the tax handling personnel for searching the self-service tax handling sites, namely, the average consumed time for the tax handling personnel to search the self-service tax handling point for handling business is calculated, and the average consumed time is minimized.
The determination of the optimal tax processing point and the optimal tax processing machine number in the third step is realized by the following formulas:
Figure BDA0001672262010000022
Figure BDA0001672262010000023
Figure BDA0001672262010000024
Figure BDA0001672262010000025
Figure BDA0001672262010000026
Figure BDA0001672262010000027
wherein, WiRepresents a grid giThe middle tax clerk searches for tax handling point events; in formula 2), XijWhen 1 is taken out, it represents grid giMiddle tax clerk to grid gjTransacting business, when 0 is taken, the grid g is representediGrid g is not reached by middle tax clerkjHandling the business; cijRepresents a grid giTo grid gjThe shortest path; in formula 3), if yj1, denotes a grid gjSelf-service tax-handling sites exist, wherein the number K of newly-added sites plus the number L of original sites is required to be smaller than the total grid number, namely each grid has 1 tax-handling site at most; equation 4) shows if it is going to grid gjMiddle handling service, grid gjThe tax handling site must exist; formula 5) represents XijAnd yjThe value can only be 1 or 0; equation 6) shows if yj1, then grid gjThere are tax handling sites.
The third step is to solve integer linear programming problem, in the formula, firstly, X is more than or equal to 0ij，yjRelaxing the integer linear programming at most 1, namely converting the integer linear programming problem into a linear programming problem; then, the linear programming is rounded to obtain the final result.
Compared with the prior art, the self-service tax handling point deployment method based on the trajectory analysis has the following beneficial effects:
the self-service tax point deployment method based on the trajectory analysis provides convenience for tax clerks to find self-service tax points nearby, and greatly reduces the time consumed by the tax clerks for finding self-service tax points; the working pressure of the tax bureau is greatly relieved; the urban traffic pressure is relieved to a certain extent; the practicability is better, the application range is wide, and the popularization and application value is good.
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In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of the implementation of the method of the present invention.
Fig. 2 is a schematic diagram of road map meshing in the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments in order to make the technical field better understand the scheme of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
When analyzing track data of tax clerks, the tax clerks need to share the track data in the tax handling process, namely the GPS information of the tax clerks in the automobile (or other vehicles). And analyzing the self-sponsoring tax point deployment site according to the acquired track data. In the patent, we define the trace data of tax clerks, so that the trace data can be analyzed and used conveniently, and the definition is as follows:
definition 1: track (track). A track is composed of a series of spatial points that contain information such as the ID, longitude, latitude, and timestamp of the track.
For convenience of calculation, tax handling traces of tax clerks are divided into three types, and each trace comprises a time location (longitude and latitude) and a timestamp. The three trajectories are: finding sub-tracks, tax handling sub-tracks, other sub-tracks.
Definition 2: find the sub-track (Seeking). Finding a sub-track represents a track where a tax clerk drives or uses other vehicles to find self-service tax points. When finding the self-service tax transaction point, the stage of queuing for transaction also belongs to the stage of finding the sub-track.
Definition 3: tax sub-track (Tax sub-track). The tax handling sub-track indicates that the tax handling personnel starts the business handling stage at the self-service tax handling point.
Definition 4: other sub-tracks (Other sub-track). Other sub-tracks represent other tracks of tax clerks, such as tracks of going to other locations for other business before tax handling.
Definition 5: and averaging the time-consuming matrix T by the road grid. We define two grids giTo gjThe average elapsed time between runs is as follows:
Figure BDA0001672262010000041
wherein v isijRepresents the sum of all meshes, t, that need to be passed between two meshesij(k) Representing the average time consumption of a single grid. In this way we get the average time consumption between two grids.
Definition 6: the shortest time consuming matrix C. From definition 5 we can calculate the slave grid giTo grid gjShortest path between Cij。
As shown in fig. 1 and fig. 2, a self-service tax transaction point deployment method based on trajectory analysis includes three parts: 1. city map, 2 tax clerk track, 3 tax office place. Through the algorithm analysis adopted by the patent, the deployment position of the optimal tax handling point can be obtained. And further, the number of tax handling machines required to be deployed at each tax handling point can be analyzed according to the queuing time of tax handling personnel.
To get the final result, the self-service machine tax place, we will go through three steps:
firstly, gridding an urban road map to obtain average time consumption among grids;
secondly, extracting a tax clerk track, and extracting a searching sub-track, a tax handling sub-track and other sub-tracks according to track information, wherein the track is composed of a series of points in space, the points comprise ID, longitude, latitude and timestamp information of the track, and the searching sub-track is used for searching a track of self-service tax handling points for the tax clerk; the tax handling sub-track is a track for starting to handle business at a self-service tax handling point by a tax handling person; the other sub-tracks are tracks of tax clerks for processing non-tax services before tax processing;
and thirdly, determining the optimal tax handling points through the extracted tracks, and calculating the number of tax handling machines required to be deployed at each tax handling point according to the queuing time of tax handling personnel.
The implementation process of the first step is as follows: firstly, dividing the road map into grids, obtaining the time consumed between each two adjacent grids, further obtaining an n multiplied by n matrix T, and calculating the shortest time between the two grids according to the matrix.
At present, the problem is that L existing self-service tax administration sites, roads and track sets are known, and K new self-service tax administration sites are obtained. Further, our problem becomes: how to minimize the time taken for tax clerks to find self-service tax stations. This problem is typical of NP-Hard, assuming that each tax clerk goes to their nearest self-service tax site. Therefore, we only need to calculate the average time for the tax clerk to find the self-service tax point to handle the business. Finally, our problem translates into minimizing this average time consumption. As shown in formula (1), in order to find the average time spent by the self-service tax administration site for tax administration personnel, what we need to do is to deploy the self-service tax administration machine at a reasonable place to minimize the value of formula (1).
Figure BDA0001672262010000051
Figure BDA0001672262010000052
Figure BDA0001672262010000053
Figure BDA0001672262010000054
Figure BDA0001672262010000055
Figure BDA0001672262010000056
Wherein, WiRepresents a grid giThe middle tax clerk searches for tax handling point events; as in formula (2), XijWhen 1 is taken out, it represents grid giMiddle tax clerk to grid gjTransacting business, when 0 is taken, the grid g is representediGrid g is not reached by middle tax clerkjHandling the business; cijRepresents a grid giTo grid gjThe shortest path. If yj1, denotes a grid gjSelf-service tax handling sites exist. The number of the newly added sites K plus the number of the original sites L is smaller than the total number of grids, namely each grid has at most 1 tax-handling site. Equation (4) shows that the grid g is reachedjMiddle handling service, grid gjA tax office site must exist. Formula (5) represents XijAnd yjValues can only be 1 or 0. Formula (6) indicates if yj1, then grid gjThere are tax handling sites.
The above problem turns into solving the integer linear programming problem. To solve this problem, first, we allow 0 ≦ Xij，yjAnd (3) relaxing the integer linear programming at most 1, namely converting the integer linear programming problem into a linear programming problem. Then, the linear programming is rounded to obtain the final result. At this time, the time complexity of the linear programming problem assuming the optimum integer is
Figure BDA0001672262010000057
The time complexity of obtaining K + L final self-service tax handling sites by adopting the method does not exceed that of obtaining K + L final self-service tax handling sites
Figure BDA0001672262010000058
To this end, we solved the NP-Hard problem within a time complexity of no more than 4 times the optimal solution.
The present invention can be easily implemented by those skilled in the art from the above detailed description. It should be understood, however, that the intention is not to limit the invention to the particular embodiments described. On the basis of the disclosed embodiments, a person skilled in the art can combine different technical features at will, thereby implementing different technical solutions.
In addition to the technical features described in the specification, the technology is known to those skilled in the art.

Claims (4)

1. A self-service tax handling point deployment method based on trajectory analysis is characterized by comprising the following implementation processes:
firstly, gridding an urban road map to obtain average consumed time among grids;
secondly, extracting a track of the tax clerk, and extracting a searching sub-track, a tax clerk sub-track and other sub-tracks according to track information, wherein the track is composed of a series of points on the space, the points comprise ID, longitude, latitude and timestamp information of the track, and the searching sub-track is used for searching a track of self-service tax clerks; the tax handling sub-track is a track for starting to handle business at a self-service tax handling point by a tax handling person; the other sub-tracks are tracks of tax clerks for processing non-tax services before tax processing;
determining the optimal tax handling points through the extracted tracks, and calculating the number of tax handling machines required to be deployed at each tax handling point according to the queuing time of tax handling personnel;
determining the optimal tax handling point in the third step means that K newly-added self-service tax handling sites are obtained by knowing L existing self-service tax handling sites, roads and track sets, and the newly-added self-service tax handling sites are obtained by minimizing the time consumed by the tax handling personnel for searching the self-service tax handling sites, namely, the average consumed time of the tax handling personnel for searching the self-service tax handling point for handling business is calculated, and the average consumed time is minimized;
the determination of the optimal tax processing point and the optimal tax processing machine number in the third step is realized by the following formulas:
Figure FDA0003359375850000011
Figure FDA0003359375850000012
Figure FDA0003359375850000013
Figure FDA0003359375850000014
Figure FDA0003359375850000015
Figure FDA0003359375850000016
wherein, WiRepresents a grid giThe middle tax clerk searches for tax handling point events; in formula 2), XijWhen 1 is taken out, it represents grid giMiddle tax clerk to grid gjTransacting business, when 0 is taken, the grid g is representediGrid g is not reached by middle tax clerkjHandling the business; cijRepresents a grid giTo grid gjThe shortest path; in formula 3), if yj1, denotes a grid gjSelf-service tax-handling sites exist, wherein the number K of newly-added sites plus the number L of original sites is required to be smaller than the total grid number, namely each grid has 1 tax-handling site at most; equation 4) shows if it is going to grid gjMiddle handling service, grid gjThe tax handling site must exist; formula 5) represents XijAnd yjThe value can only be 1 or 0; equation 6) shows if yj1, then grid gjThere are tax handling sites.
2. The self-service tax point deployment method based on trajectory analysis according to claim 1, wherein the implementation procedure of the first step is as follows: firstly, dividing the road map into grids, obtaining the time consumed between each two adjacent grids, further obtaining an n multiplied by n matrix T, and calculating the shortest time between the two grids according to the matrix.
3. The self-service tax point deployment method based on trajectory analysis according to claim 2, wherein the specific operation process of the first step is as follows:
the average time-consuming matrix of the road grid is T, and two grids giTo gjThe average elapsed time between runs is as follows:
Figure FDA0003359375850000021
wherein v isijRepresents the sum of all meshes, t, that need to be passed between two meshesij(k) Representing the average time consumption of a single grid; correspondingly, the secondary grid g can be calculated according to the formulaiTo grid gjShortest path between CijAnd C is the shortest time consuming matrix.
4. The self-service tax point deployment method based on trajectory analysis as claimed in claim 1, wherein the formula implemented in step three is to solve an integer linear programming problem, in which formula first X is greater than or equal to 0ij，yjRelaxing the integer linear programming at most 1, namely converting the integer linear programming problem into a linear programming problem; then, the linear programming is rounded to obtain the final result.
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105389647A (en) * 2015-10-20 2016-03-09 国网辽宁省电力有限公司鞍山供电公司 NSGA-II-based electricity fee payment place site-selecting method
CN106203717A (en) * 2016-07-15 2016-12-07 浪潮软件集团有限公司 Tax hall intelligent navigation method based on data analysis
CN106202471A (en) * 2016-07-18 2016-12-07 上海河广信息科技有限公司 Business hall candidate point screening technique and system
WO2017201949A1 (en) * 2016-05-24 2017-11-30 华为技术有限公司 Method and device for selecting location
CN107481511A (en) * 2017-08-16 2017-12-15 深圳先进技术研究院 A kind of method and system for calculating candidate bus station
CN107491895A (en) * 2017-08-30 2017-12-19 国信优易数据有限公司 A kind of shared bicycle parks determination method and device a little

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105389647A (en) * 2015-10-20 2016-03-09 国网辽宁省电力有限公司鞍山供电公司 NSGA-II-based electricity fee payment place site-selecting method
WO2017201949A1 (en) * 2016-05-24 2017-11-30 华为技术有限公司 Method and device for selecting location
CN106203717A (en) * 2016-07-15 2016-12-07 浪潮软件集团有限公司 Tax hall intelligent navigation method based on data analysis
CN106202471A (en) * 2016-07-18 2016-12-07 上海河广信息科技有限公司 Business hall candidate point screening technique and system
CN107481511A (en) * 2017-08-16 2017-12-15 深圳先进技术研究院 A kind of method and system for calculating candidate bus station
CN107491895A (en) * 2017-08-30 2017-12-19 国信优易数据有限公司 A kind of shared bicycle parks determination method and device a little

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