CN111754147A - Road division method, system, device and computer readable storage medium - Google Patents
Road division method, system, device and computer readable storage medium Download PDFInfo
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- CN111754147A CN111754147A CN201910240911.4A CN201910240911A CN111754147A CN 111754147 A CN111754147 A CN 111754147A CN 201910240911 A CN201910240911 A CN 201910240911A CN 111754147 A CN111754147 A CN 111754147A
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- 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
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
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- 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
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
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Abstract
The embodiment of the invention provides a road division method, a road division system, a road division device and a computer readable storage medium. The road division method comprises the following steps: dividing a distribution area into a plurality of distribution units; establishing an association relation between the order address and the delivery unit; respectively corresponding a plurality of pieces of order distribution data contained in the first order distribution data set to the plurality of distribution units based on the incidence relation; acquiring statistical information of order distribution data of each distribution unit; and combining the distribution units to obtain a plurality of road areas based on the statistical information. The road area division method for obtaining the road areas through the combined distribution units is not only beneficial to quickly adjusting the road areas, but also beneficial to the distribution personnel to keep the working efficiency because most distribution units contained in one road area are not changed and have little influence on the daily work of the distribution personnel.
Description
Technical Field
The invention relates to the field of logistics, in particular to a road division method, a road division system, a road division device and a computer readable storage medium.
Background
The planning of the existing distribution range mainly divides the road areas of distributors according to business requirements by site managers in combination with past experience, such as task allocation for single quantity conditions and timeliness requirements (such as units requiring daytime distribution) of a certain area.
However, due to various reasons such as service growth, personnel change, and site distribution range change, the road area of the distributor frequently changes, and the site invests a lot of manpower and material resources in road area maintenance to meet the service demand. With the increase of the logistics scale, manual maintenance of the road areas gradually fails to respond to the site requirements quickly, and in some cases, the updating of the road areas is not timely, which results in a delivery error of the pre-sorting system.
Disclosure of Invention
In view of this, embodiments of the present invention provide a road partition method to solve the problems existing in the existing road partition process.
In a first aspect, an embodiment of the present invention provides a road division method, including:
dividing a distribution area into a plurality of distribution units;
establishing an association relation between the order address and the delivery unit;
respectively corresponding a plurality of pieces of order distribution data contained in the first order distribution data set to the plurality of distribution units based on the incidence relation;
acquiring statistical information of order distribution data of each distribution unit; and
and combining the distribution units to obtain a plurality of road areas based on the statistical information.
Optionally, the method further comprises: and checking the order address of the order distribution data contained in the second order distribution data set based on the appropriate GIS data, and taking the order distribution data passing the checking as the order distribution data in the first order distribution data set.
Optionally, if an offset between the GIS data corresponding to the order address of the order distribution data included in the second order distribution data set and the GIS data put into place is smaller than a first set threshold, the order address of the order distribution data in the second order distribution data set is considered to be accurate.
Optionally, the method further comprises:
adopting a GIS technology to carry out forward analysis on the order address of the order distribution data contained in the second order distribution data set to obtain a forward analysis result, and adopting the GIS technology to carry out inverse analysis on the forward analysis result to obtain an inverse analysis address;
verifying the order address of the second order distribution data set by adopting the reverse resolution address; and
and if the similarity between the order address of the order distribution data of the second order distribution data set and the reverse resolution address exceeds a second set threshold, taking the order distribution data with the similarity exceeding the second set threshold as the order distribution data in the first order distribution data set.
Optionally, the method further comprises: and carrying out natural language processing on the reverse analysis address and the order address of the order distribution data of the second order distribution data set.
Optionally, the method further comprises: and acquiring the first order distribution data set from the second order distribution data set according to a first check result of the order address check of the order distribution data of the second order distribution data set by the appropriate GIS data and a second check result of the order address check of the order distribution data of the second order distribution data set by the GIS technology.
Optionally, the method further comprises: and obtaining the appropriate GIS data from the GIS track data of the distribution personnel.
Optionally, the method further comprises: and establishing a corresponding relation between the road areas and the distribution personnel.
Optionally, the dividing the distribution area into a plurality of distribution units includes:
converting the order address of the order distribution data contained in the third order distribution data set into corresponding GIS data; and
and dividing the distribution area into a plurality of distribution units according to the corresponding GIS data by adopting a clustering algorithm.
Optionally, the clustering algorithm is a k-means algorithm.
Optionally, the third order delivery data set includes order delivery data having a time period shorter than the time period of the order delivery data included in the first order delivery data set.
Optionally, the method further comprises: desensitizing the order delivery data in the first order delivery data set.
Optionally, the statistical information is a daily average order number of each delivery unit, and the combining the plurality of delivery units to obtain a plurality of road regions based on the statistical information includes:
and combining the adjacent distribution units together according to the preset road area number and the daily average order number of each distribution unit to form the plurality of road areas.
Optionally, the method further comprises: providing a visual interface, and dividing the plurality of road areas by dragging the plurality of delivery units on the visual interface.
According to a second aspect of the embodiments of the present invention, there is provided a road division system, including:
a delivery unit dividing module for dividing the delivery area into a plurality of delivery units;
the address correlation module is used for establishing a correlation between the order address and the delivery unit;
a distribution data corresponding module, configured to respectively correspond, based on the association relationship, a plurality of pieces of order distribution data included in the first order distribution data set to the plurality of distribution units;
the distribution data statistical module is used for acquiring statistical information of the order distribution data of each distribution unit; and
and the distribution unit combination module is used for combining the distribution units to obtain a plurality of road areas based on the statistical information.
Optionally, the method further comprises: and the first checking module is used for checking the order address of the order distribution data contained in the second order distribution data set based on the GIS data, and taking the order distribution data passing the checking as the order distribution data in the first order distribution data set.
Optionally, the method further comprises: the second checking module is used for carrying out forward analysis on the order address of the order distribution data contained in the second order distribution data set by adopting a GIS technology to obtain a forward analysis result, and carrying out inverse analysis on the forward analysis result by adopting the GIS technology to obtain an inverse analysis address; verifying the order address of the second order distribution data set by adopting the reverse resolution address; and if the similarity between the order address of the order distribution data of the second order distribution data set and the reverse resolution address exceeds a second set threshold, taking the order distribution data with the similarity exceeding the second set threshold as the order distribution data in the first order distribution data set.
Optionally, the method further comprises: and the natural language processing module is used for carrying out natural language processing on the reverse analysis address and the order address of the order distribution data of the second order distribution data set.
Optionally, the delivery unit dividing module includes:
converting the order address of the order distribution data contained in the third order distribution data set into corresponding GIS data; and
and dividing the distribution area into a plurality of distribution units according to the corresponding GIS data by adopting a clustering algorithm.
Optionally, the third order delivery data set includes order delivery data having a time period shorter than the time period of the order delivery data included in the first order delivery data set.
Optionally, the statistical information is a daily average order number of each delivery unit, and the delivery unit combination module includes:
and combining the adjacent distribution units together according to the preset road area number and the daily average order number of each distribution unit to form the plurality of road areas.
In a third aspect of the clustering algorithm, an embodiment of the present invention provides a computer-readable storage medium, where computer instructions are stored, and when the computer instructions are executed, the road partitioning method is implemented.
In a fourth aspect, an embodiment of the present invention provides a road division apparatus, including:
a memory for storing computer instructions;
a processor coupled to the memory, the processor configured to perform a road zoning method implementing any of the above based on computer instructions stored by the memory.
The embodiment of the invention has the following advantages or beneficial effects: the road area division method for obtaining the road areas through the combined distribution units is not only beneficial to quickly adjusting the road areas, but also beneficial to the distribution personnel to keep the working efficiency because most distribution units contained in one road area are not changed and have little influence on the daily work of the distribution personnel.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing embodiments of the present invention with reference to the following drawings, in which:
fig. 1 is a flowchart illustrating a road division method according to a first embodiment of the present invention;
FIG. 2 is a diagram showing delivery areas, delivery units, and road zones on a geographic information system;
fig. 3 is an exemplary flowchart of step S101 in the first embodiment of the present invention;
fig. 4 is a flowchart illustrating a road division method according to a second embodiment of the present invention;
fig. 5 is a flowchart illustrating a road division method according to a third embodiment of the present invention;
FIG. 6 illustrates steps S503-S505 for further illustrating a third embodiment of the present invention;
fig. 7 is a structural diagram of a road division system according to a fourth embodiment of the present invention;
fig. 8 is a structural diagram of a road division apparatus according to a sixth embodiment of the present invention.
Detailed Description
The present invention will be described below based on examples, but the present invention is not limited to only these examples. In the following detailed description of the present invention, certain specific details are set forth. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details. Well-known methods, procedures, and procedures have not been described in detail so as not to obscure the present invention. The figures are not necessarily drawn to scale.
Referring to fig. 1, fig. 1 is a flowchart illustrating a road division method according to a first embodiment of the present invention. In this embodiment, the distribution area is first divided into distribution units, and then the road areas are divided based on the distribution units. Fig. 2 shows distribution areas, distribution units and road areas on a geographical information system. Referring to fig. 2, the distribution area 10 is, for example, a distribution range corresponding to a distribution station, and has a corresponding boundary on the geographic information system. The distribution area 10 is divided into a plurality of distribution units such as 1001-1007. Adjacent dispensing units combine to form a roadway. In the figure, the road zones and the distribution areas are marked with solid lines, and the distribution units are marked with dashed lines. As can be seen from the figure, the road section 100 is composed of the distribution units 1001 and 1007. The distribution units 1001 and 1007 are different in area. This is described in more detail below with respect to the embodiment of fig. 1.
In step S101, the delivery area is divided into a plurality of delivery units.
As shown in fig. 2, the delivery area may be divided into a plurality of delivery units based on a geographic information system. For example, all valid delivery addresses of historical order delivery data in a delivery area are counted, the delivery area is divided into a plurality of delivery units according to the valid delivery addresses, the valid delivery addresses on each delivery unit are approximately equivalent, or the valid delivery addresses with strong correlation are distributed in the same delivery unit. The effective delivery address with stronger relevance is an effective delivery address which is within a set threshold from a set central point. It should be noted that the areas of the plurality of dispensing units resulting from this division of the dispensing units may not be equal.
In step S102, an association is established between the order address and the delivery unit.
The order address may be from the order data, and the order address is stored in the order address dataset at the same time as the order data is generated. And then converting the order address into GIS data (including longitude and latitude information), and determining the association relationship between the order address and the distribution units according to the longitude and latitude information of the order address and the GIS fence information of each distribution unit.
In step S103, the plurality of pieces of order delivery data included in the first order delivery data set are associated with the plurality of delivery units, respectively, based on the association relationship.
And according to the association relationship between the order address and the delivery unit, realizing the association relationship between the order delivery data contained in the first order delivery data set and the delivery unit.
In step S104, statistical information of order distribution data of each distribution unit is acquired.
In step S105, a plurality of delivery units are combined to obtain a plurality of delivery route areas based on the statistical information.
Since the order distribution data included in the first order distribution data set is mapped to the plurality of distribution units one by one in step S103, the number of order distribution data in each distribution unit can be counted in step S104, and the plurality of distribution units are divided into a plurality of road sections in step S105 based on the statistical information of the order distribution data in each distribution unit. Typically, the daily average number of orders per delivery unit is used as an indicator to measure the delivery unit's capacity. The daily average order quantity may be calculated based on historical order delivery data for the current 30 or 60 days. The daily average order quantity is adopted to smooth the fluctuation of real-time order distribution data. Although the invention is not so limited. And after the road area division is completed, establishing a corresponding relation between the road area and distribution personnel. In practical activities, the road areas for which the dispatchers are responsible are arranged as required.
The embodiment of the invention is suitable for various road area dividing scenes. For example, when the traffic volume increases, since the newly increased traffic volume is not uniformly distributed in the currently existing road areas, the currently existing road areas need to be adjusted. Since the delivery units are kept unchanged, the statistical information of the order delivery data on the existing delivery units is recalculated, and the delivery units included in each road area are adjusted accordingly.
The road area dividing method for obtaining the road areas by combining the distribution units in the embodiment is not only beneficial to quickly adjusting the road areas, but also beneficial to the distribution personnel to keep the working efficiency because most distribution units contained in one road area are not changed and have little influence on the daily work of the distribution personnel.
It should be noted that the original order distribution data of the e-commerce system retains a large amount of sensitive data, such as user name, user detailed address, mobile phone number, etc., which are not necessary in the present invention, so that the original order distribution data can be desensitized and the sensitive information can be hidden or filtered out. Desensitized order delivery data generally contains the following fields: order number, order address, and time of receipt.
Fig. 3 is an exemplary flowchart of step S101 in the first embodiment of the present invention. The present embodiment describes how one delivery area is divided into a plurality of delivery units. The method specifically comprises the following steps.
In step S1011, a third order delivery data set of the delivery area is acquired.
In step S1012, the order address of the order distribution data of the third order distribution data set is converted into corresponding GIS data.
In step S1013, the distribution area is divided into a plurality of distribution units according to the GIS data corresponding to the order address of the order distribution data of the third order distribution data set.
The third order delivery data set of the present embodiment generally selects short-term historical order delivery data, such as historical order delivery data for one year, and the first order delivery data set of step S102 generally selects long-term historical order delivery data, such as all historical order delivery data. The first order delivery data set and the third order delivery data set are preferably historical order delivery data that has been desensitized and/or pre-processed. Preprocessing includes, for example, cleaning out some of the order delivery data that has been cancelled, replenishing missing information in the order address, and so forth. Supplementing missing information in the order address, for example, if the order address in the order delivery data is not a complete zip code address, which includes information such as province, city, district name, building number, etc., the information of the corresponding level of the order address in the order delivery data is completely supplemented.
In this embodiment, dividing the distribution area into a plurality of distribution units according to the GIS data may be performed as follows: and marking the GIS data on a geographic information system, and classifying the GIS data which is relatively close to the geographic information system into a distribution unit by adopting a clustering algorithm. The clustering algorithm does not need to set the number of the delivery units, and can determine the number of the delivery units only according to the actual physical state.
In some embodiments, the clustering algorithm method is a k-means algorithm. The K-means algorithm is a typical clustering algorithm based on distance, and the distance is used as an evaluation index of similarity, that is, the closer the distance between two objects is, the greater the similarity of the two objects is.
Fig. 4 is a flowchart illustrating a road division method according to a second embodiment of the present invention.
In step S401, the delivery area is divided into a plurality of delivery units.
In step S402, an association is established between the order address and the delivery unit.
In step S403, the order address of the order distribution data included in the second order distribution data set is checked based on the GIS data to obtain the first order distribution data set.
In step S404, the plurality of pieces of order distribution data included in the first order distribution data set are associated with the plurality of distribution units, respectively, based on the association relationship.
In step S405, statistics of a first order delivery data set on a plurality of delivery units are obtained.
In step S406, a plurality of delivery units are combined to obtain a plurality of delivery route areas based on the statistical information.
Steps S401 to S402 and S404 to S406 are the same as steps S101 to S105 in fig. 1, and are not described again here.
In step S403, the appropriate GIS data is GIS data obtained when the distribution personnel arrive at the package, and generally includes longitude and latitude information and appropriate time. The appropriate GIS data can come from distribution personnel, and when the distribution personnel deliver the packages, the current longitude and latitude information and the current time are uploaded through a terminal carried by the distribution personnel to serve as the appropriate GIS data. The appropriate-delivery GIS data can also come from a delivery robot or an unmanned aerial vehicle, and when the unmanned aerial vehicle or the delivery robot delivers the package, the current longitude and latitude information and the time are uploaded to serve as the appropriate-delivery GIS data.
In step S402, the order address in the second order distribution data set is checked based on the GIS data to determine whether the order address resolution GIS is correct, and the second order distribution data set in which the correct order address is resolved is classified as the first order distribution data set. Specifically, the offset between the latitude and longitude when the order is properly placed and the latitude and longitude of the order address conversion is calculated, and whether the order address is accurate or not is judged according to the offset. If the offset exceeds a set threshold, the order address resolution GIS is considered possibly inaccurate. In one example, the offset is calculated using the following equation:
wherein lat1, lng1 represents latitude and longitude of point A, lat2, lng2 represents latitude and longitude of point B, 6378.137 is earth radius, and unit is kilometer. Point a is the place of successful placement and point B is the order address. In this embodiment, the ratio of the offset to the delivery distance may also be used to determine whether the second order delivery data set is accurate. Similarly, if the ratio exceeds a set threshold, the order address is deemed inaccurate.
Fig. 5 is a flowchart illustrating a road division method according to a third embodiment of the present invention. The method specifically comprises the following steps.
In step S501, a delivery area is divided into a plurality of delivery units.
In step S502, an association relationship is established between the order address and the delivery unit
In step S503, the order address of the order distribution data included in the second order distribution data set is verified based on the GIS data to obtain a first verification result.
In step S504, the GIS technique is used to perform forward analysis on the order address of the order distribution data included in the second order distribution data set to obtain a forward analysis result, the GIS technique is used to perform inverse analysis on the forward analysis result to obtain an inverse analysis address, and a second verification result is obtained according to the order address and the inverse analysis address in the order distribution data.
In step S505, a first order delivery data set is obtained from the second order delivery data set according to the first verification result and the second verification result.
In step S506, the plurality of pieces of order distribution data included in the first order distribution data set are associated with the plurality of distribution units, respectively, based on the association relationship.
In step S507, statistical information of the first order delivery data set on the plurality of delivery units is acquired.
In step S508, a plurality of delivery units are combined to obtain a plurality of delivery route regions based on the statistical information.
Steps S501-S502 are the same as steps S101-S102 of fig. 1, and steps S506-S508 are the same as steps S103-S105 of fig. 1, and thus are not described again. In steps S503-S505, the two verification methods are combined to obtain a verification result, and the first order distribution data set is obtained from the second order distribution data set according to the verification result.
In step S503, the order address in the second order distribution data set is verified based on the GIS data, and a first verification result is obtained. The GIS data for proper delivery is GIS data for delivery personnel to reach the package, and generally includes longitude and latitude information and proper delivery time. The appropriate GIS data can come from distribution personnel, and the terminal carried by the distribution personnel uploads GIS track data at regular time and acquires the appropriate GIS data from the GIS track data.
In step S504, the GIS technique is used to perform forward analysis on the order address of the order distribution data included in the second order distribution data set to obtain a forward analysis result, the GIS technique is used to perform inverse analysis on the forward analysis result to obtain an inverse analysis address, and a second check result is obtained according to the order address and the inverse analysis address of the order distribution data included in the second order distribution data set. The positive analysis is to obtain longitude and latitude information according to the order address, and the reverse analysis is to obtain the order address according to the longitude and latitude information. In step S504, it is determined whether the order address is accurate by reverse resolution after the forward resolution. In some embodiments, an order address may be considered accurate if the similarity of the reverse-resolved address and the order address is greater than a set threshold. The reverse-resolution address and the order address are generally matched by Natural Language Processing (NLP), for example, the similarity obtained by natural language processing is higher in the privet west of beijing and the privet west of beijing.
In step S505, the first verification result and the second verification result are combined to obtain the first order distribution data set from the second order distribution data set.
Based on steps S503 and S504, two verification results are obtained for the order address, and the first order delivery data set is obtained from the second order delivery data set according to the two verification results. For example, if the first check result is that the order address is accurate, and the second check result is that the order address is accurate, the corresponding second order delivery data set may be used as the first order delivery data set. For another example, if the first check result is that the order address is accurate, and the second check result is that the order address is inaccurate, the manual intervention is performed to judge and correct, so as to obtain the first order distribution data set.
In summary, in the embodiments of the present invention, the order address is verified by using the appropriate GIS data, the order address is transformed by forward and inverse analysis of the GIS technology, the order address is verified according to the inverse analysis address, the first order distribution data set is obtained according to the two verification results, the order address is ensured to be accurate by double verification, and then the road areas are divided according to the statistical information of the first order distribution data set, so that the accuracy of road area division is ensured, and the capacity of each divided road area is ensured to be approximately equivalent.
Fig. 6 shows steps S503-S505 for further explaining the third embodiment of the present invention. In the embodiment, the verification A and the verification B are simultaneously carried out, and the final verification result is determined by synthesizing the verification results of the verification A and the verification B twice. Firstly, obtaining a proper time 402 and a distributor track 401, performing data cleaning (namely 403) on the distributor track 401 to obtain proper GIS data 404, wherein the proper GIS data comprises proper longitude and latitude information and proper time, converting an order address 400 in a second order distribution data set to obtain corresponding GIS data 405, verifying A the proper GIS data 404 and the GIS data 405, and if the two are close to each other, for example, smaller than a set threshold value, considering the order address to be accurate, namely 406, if the two are not close to each other, for example, larger than the set threshold value, considering the order address to be inaccurate, namely 407. Meanwhile, forward analysis (501) is carried out on the order address 408 to obtain GIS data 409, reverse analysis (502) is carried out on the GIS data 409 to obtain a reverse analysis address 410, Natural Language Processing (NLP) (411) is carried out on the order address 408 and the reverse analysis address 410, verification is carried out through a verification B, if the similarity of the order address 408 and the reverse analysis address 410 exceeds 80%, the order address is considered to be accurate (412), otherwise, the order address is considered to be inaccurate (413), and the verification results of the verification A and the verification B are comprehensively verified to obtain four results: 1) the A-determination is accurate and the B-determination is accurate, i.e., 414 on the graph, where the order address is generally considered to be accurate, the second order delivery data set may be taken as the first order delivery data set in the first embodiment; 2) if decision a is accurate and decision B is not accurate, i.e. 415 on the graph, the address is generally considered to be highly accurate and contains an alias, i.e. 419 on the graph, and the order delivery data is modified by 422 manually to be used as a first order delivery data set; 3) if the determination a is inaccurate and the determination B is accurate, i.e., 416 on the graph, it is considered that the address with higher accuracy may be wrong, i.e., 420 on the graph, and the order distribution data is modified manually, i.e., 422, to be used as a first order distribution data set; 4) decision a is inaccurate and decision B is inaccurate-417 on the graph-the order delivery data is not categorized as the first order delivery data set.
Optionally, the present embodiment may further provide a visualization interface, and divide the road area based on the visualization interface. As shown in fig. 2, based on a geographic information system, the divided distribution units are marked on the geographic information system, and statistical information of the distribution units is marked on each distribution unit, so that a manager can combine one or more distribution units together to obtain a road area. On the other visual interface, the distribution units are similar to the individual modules, and the road areas are combined by dragging the distribution units. There are, of course, other limitations in the assembly process, such as the ability to only combine adjacent dispensers. The visual interface has strong application scenes and brings great convenience to managers. The management personnel can continuously combine and separate the distribution units on the visual interface to obtain the scheme of optimal road division.
Fig. 7 is a structural diagram of a road division system according to a fourth embodiment of the present invention. The road division system 700 includes: a delivery unit division module 701, an address association module 702, a delivery data correspondence module 703, a delivery data statistics module 704, and a delivery unit combination module 705.
The delivery unit dividing module 701 is configured to divide a delivery area into a plurality of delivery units. The address association module 702 is used to establish an association between an order address and a delivery unit. The distribution data corresponding module 703 is configured to, based on the association relationship, respectively correspond the multiple pieces of order distribution data included in the first order distribution data set to multiple distribution units. The distribution data statistics module 703 is configured to obtain statistics information of the order distribution data of each distribution unit. The distribution unit combination module 704 is configured to combine the plurality of distribution units to obtain a plurality of road regions based on the statistical information.
In the road area dividing system, a distribution area is divided into a plurality of distribution units, an association relationship is established between the distribution units and order addresses, so that order distribution data are associated to the distribution units, then the quantity of the associated order distribution data on each distribution unit is counted, and the distribution units are divided into a plurality of road areas based on the counted value. In the system, the road area division method for obtaining the road areas by combining the distribution units is not only beneficial to quickly adjusting the road areas, but also beneficial to the distribution personnel to keep the work efficiency because most distribution units contained in one road area are not changed and have little influence on the daily work of the distribution personnel.
In some embodiments, the road division system further includes a first verification module, configured to verify an order address of the order distribution data included in the second order distribution data set based on the GIS data, and use the order distribution data that passes the verification as the order distribution data in the first order distribution data set.
In some embodiments, the road division system further includes a second check module, configured to perform forward analysis on an order address of the order distribution data included in the second order distribution data set by using a GIS technology to obtain a forward analysis result, and perform inverse analysis on the forward analysis result by using the GIS technology to obtain an inverse analysis address; verifying the order address of the second order distribution data set by adopting the reverse analysis address; and if the similarity between the order address of the order distribution data of the second order distribution data set and the reverse resolution address exceeds a second set threshold, taking the order distribution data with the similarity exceeding the second set threshold as the order distribution data in the first order distribution data set.
In some embodiments, the road partition system includes a combination of the first check module and the first check module, that is, the first order distribution data is obtained from the second order distribution data set according to the first check result and the second check result.
In some embodiments, the distribution unit dividing module is configured to convert an order address of the order distribution data included in the third order distribution data set into corresponding GIS data, and then divide the distribution area into a plurality of distribution units according to the corresponding GIS data by using a clustering algorithm. It should be noted that the time period for dividing the order delivery data of the third order delivery data set of the delivery unit is generally shorter than the time period for dividing the order delivery data included in the first order delivery data set of the road section. For example, the third order delivery data set is historical order delivery data for the current year, and the first order delivery data set and the second order delivery data set take all of the historical order delivery data. The delivery units identified by the third order delivery data set generally remain unchanged. Since the address information on the delivery units does not typically change easily, the delivery units do not need to be modified frequently. It should be clear here that the change of the building where the address is located does not mean that the address information changes, for example, a flat house changes into a tall building, but the corresponding address information does not change, but it is possible to describe the address information differently.
In some embodiments, the statistical information in the order delivery data statistics module 703 is the daily average order number per delivery unit, and the delivery unit combination module 704 includes: and combining the adjacent distribution units together according to the preset road area number and the daily average order number of each distribution unit to form a plurality of road areas.
In some embodiments, the road zoning system further comprises: and the visualization module is used for providing a visualization interface, and dividing a plurality of road areas by dragging a plurality of distribution units on the visualization interface.
It should be understood that the first order delivery data set, the second order delivery data set, and the third order delivery data set are used herein only to differentiate between different order delivery data and do not represent a priority or level differentiation.
Fig. 8 is a structural diagram of a road division apparatus according to a sixth embodiment of the present invention. The apparatus shown in fig. 8 is only an example and should not limit the functionality and scope of use of embodiments of the present invention in any way.
Referring to fig. 8, the apparatus includes a processor 801, a memory 802, and an input-output device 803 connected by a bus. The memory 802 includes a Read Only Memory (ROM) and a Random Access Memory (RAM), and various computer instructions and data required to perform system functions are stored in the memory 802, and the processor 801 reads the various computer instructions from the memory 802 to perform various appropriate actions and processes. An input/output device including an input portion of a keyboard, a mouse, and the like; an output section including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section including a hard disk and the like; and a communication section including a network interface card such as a LAN card, a modem, or the like. The memory 802 also stores the following computer instructions to perform the operations specified by the apparatus of an embodiment of the invention: dividing a distribution area into a plurality of distribution units; establishing an association relation between the order address and the delivery unit; respectively corresponding a plurality of pieces of order distribution data contained in the first order distribution data set to a plurality of distribution units based on the incidence relation; acquiring statistical information of order distribution data of each distribution unit; and combining the distribution units to obtain a plurality of road areas based on the statistical information
Accordingly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that, when executed, implement the operations specified by the above-described method.
The flowcharts and block diagrams in the figures and block diagrams illustrate the possible architectures, functions, and operations of the systems, methods, and apparatuses according to the embodiments of the present invention, and may represent a module, a program segment, or merely a code segment, which is an executable instruction for implementing a specified logical function. It should also be noted that the executable instructions that implement the specified logical functions may be recombined to create new modules and program segments. The blocks of the drawings, and the order of the blocks, are thus provided to better illustrate the processes and steps of the embodiments and should not be taken as limiting the invention itself.
The various modules or units of the system may be implemented in hardware, firmware or software. The software includes, for example, a code program formed using various programming languages such as JAVA, C/C + +/C #, SQL, and the like. Although the steps and sequence of steps of the embodiments of the present invention are presented in method and method diagrams, the executable instructions of the steps implementing the specified logical functions may be re-combined to create new steps. The sequence of the steps should not be limited to the sequence of the steps in the method and the method illustrations, and can be modified at any time according to the functional requirements. Such as performing some of the steps in parallel or in reverse order.
Systems and methods according to the present invention may be deployed on a single server or on multiple servers. For example, different modules may be deployed on different servers, respectively, to form a dedicated server. Alternatively, the same functional unit, module or system may be deployed in a distributed fashion across multiple servers to relieve load stress. The server includes but is not limited to a plurality of PCs, PC servers, blades, supercomputers, etc. on the same local area network and connected via the Internet.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (23)
1. A road division method, comprising:
dividing a distribution area into a plurality of distribution units;
establishing an association relation between the order address and the delivery unit;
respectively corresponding a plurality of pieces of order distribution data contained in the first order distribution data set to the plurality of distribution units based on the incidence relation;
acquiring statistical information of order distribution data of each distribution unit; and
and combining the distribution units to obtain a plurality of road areas based on the statistical information.
2. The road division method according to claim 1, further comprising: and checking the order address of the order distribution data contained in the second order distribution data set based on the appropriate GIS data, and taking the order distribution data passing the checking as the order distribution data in the first order distribution data set.
3. The road division method according to claim 2, wherein if an offset between GIS data corresponding to an order address of order distribution data included in the second order distribution data set and the GIS data is smaller than a first set threshold, the order address of the order distribution data in the second order distribution data set is considered to be accurate.
4. The road division method according to claim 1, further comprising:
adopting a GIS technology to carry out forward analysis on the order address of the order distribution data contained in the second order distribution data set to obtain a forward analysis result, and adopting the GIS technology to carry out inverse analysis on the forward analysis result to obtain an inverse analysis address;
verifying the order address of the second order distribution data set by adopting the reverse resolution address; and
and if the similarity between the order address of the order distribution data of the second order distribution data set and the reverse resolution address exceeds a second set threshold, taking the order distribution data with the similarity exceeding the second set threshold as the order distribution data in the first order distribution data set.
5. The road division method according to claim 4, further comprising: and carrying out natural language processing on the reverse analysis address and the order address of the order distribution data of the second order distribution data set.
6. The road division method according to claim 1, further comprising: and acquiring the first order distribution data set from the second order distribution data set according to a first check result of the order address check of the order distribution data of the second order distribution data set by the appropriate GIS data and a second check result of the order address check of the order distribution data of the second order distribution data set by the GIS technology.
7. The road division method according to claim 1, further comprising: and obtaining the appropriate GIS data from the GIS track data of the distribution personnel.
8. The road division method according to claim 1, further comprising: and establishing a corresponding relation between the road areas and the distribution personnel.
9. The road division method of claim 1 wherein the dividing the distribution area into a plurality of distribution units comprises:
converting the order address of the order distribution data contained in the third order distribution data set into corresponding GIS data; and
and dividing the distribution area into a plurality of distribution units according to the corresponding GIS data by adopting a clustering algorithm.
10. The road partitioning method according to claim 9, wherein said clustering algorithm is a k-means algorithm clustering algorithm.
11. The road division method according to claim 9, wherein a time period of order delivery data included in the third order delivery data set is shorter than a time period of order delivery data included in the first order delivery data set.
12. The road division method according to claim 1, further comprising: desensitizing the order delivery data in the first order delivery data set.
13. The road planning method of claim 1, wherein the statistical information is a daily average order number of each delivery unit, and wherein combining the plurality of delivery units to obtain a plurality of road areas based on the statistical information comprises:
and combining the adjacent distribution units together according to the preset road area number and the daily average order number of each distribution unit to form the plurality of road areas.
14. The road planning method according to claim 13, further comprising: providing a visual interface, and dividing the plurality of road areas by dragging the plurality of delivery units on the visual interface.
15. A road zoning system comprising:
the distribution unit dividing module is used for dividing the distribution area into a plurality of distribution units;
the address association module is used for establishing an association relationship between the order address and the delivery unit;
a distribution data corresponding module, configured to respectively correspond, based on the association relationship, a plurality of pieces of order distribution data included in the first order distribution data set to the plurality of distribution units;
the distribution data statistical module is used for acquiring statistical information of the order distribution data of each distribution unit; and
and the distribution unit combination module is used for combining the distribution units to obtain a plurality of road areas based on the statistical information.
16. The road zoning system according to claim 15, further comprising: and the first checking module is used for checking the order address of the order distribution data contained in the second order distribution data set based on the GIS data, and taking the order distribution data passing the checking as the order distribution data in the first order distribution data set.
17. The road zoning system according to claim 15, further comprising: the second checking module is used for carrying out forward analysis on the order address of the order distribution data contained in the second order distribution data set by adopting a GIS technology to obtain a forward analysis result, and carrying out inverse analysis on the forward analysis result by adopting the GIS technology to obtain an inverse analysis address; verifying the order address of the second order distribution data set by adopting the reverse resolution address; and if the similarity between the order address of the order distribution data of the second order distribution data set and the reverse resolution address exceeds a second set threshold, taking the order distribution data with the similarity exceeding the second set threshold as the order distribution data in the first order distribution data set.
18. The road zoning system according to claim 17, further comprising: and the natural language processing module is used for carrying out natural language processing on the reverse analysis address and the order address of the order distribution data of the second order distribution data set.
19. The road zoning system according to claim 15, wherein the delivery unit dividing module comprises:
converting the order address of the order distribution data contained in the third order distribution data set into corresponding GIS data; and
and dividing the distribution area into a plurality of distribution units according to the corresponding GIS data by adopting a clustering algorithm.
20. The road zoning system according to claim 19, wherein a time period of the order delivery data comprised in the third order delivery data set is shorter than a time period of the order delivery data comprised in the first order delivery data set.
21. The road planning system of claim 15 wherein the statistical information is a daily average number of orders per delivery unit, the delivery unit combining module comprising:
and combining the adjacent distribution units together according to the preset road area number and the daily average order number of each distribution unit to form the plurality of road areas.
22. A computer-readable storage medium storing computer instructions which, when executed, implement the road zoning method according to any of the claims 1 to 14.
23. A road division apparatus, characterized by comprising:
a memory for storing computer instructions;
a processor coupled to the memory, the processor configured to perform implementing the road partitioning method of any of claims 1 to 14 based on computer instructions stored by the memory.
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| CN201910240911.4A CN111754147A (en) | 2019-03-28 | 2019-03-28 | Road division method, system, device and computer readable storage medium |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112288377A (en) * | 2020-12-15 | 2021-01-29 | 浙江口碑网络技术有限公司 | Order processing method and device, storage medium and electronic equipment |
| CN113822510A (en) * | 2020-11-09 | 2021-12-21 | 北京京东振世信息技术有限公司 | Logistics information processing method, server and client |
| WO2023221448A1 (en) * | 2022-05-17 | 2023-11-23 | 北京京东叁佰陆拾度电子商务有限公司 | Order allocation method and apparatus, and storage medium |
-
2019
- 2019-03-28 CN CN201910240911.4A patent/CN111754147A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113822510A (en) * | 2020-11-09 | 2021-12-21 | 北京京东振世信息技术有限公司 | Logistics information processing method, server and client |
| CN113822510B (en) * | 2020-11-09 | 2024-03-01 | 北京京东振世信息技术有限公司 | Logistics information processing method, server side and client side |
| CN112288377A (en) * | 2020-12-15 | 2021-01-29 | 浙江口碑网络技术有限公司 | Order processing method and device, storage medium and electronic equipment |
| CN112288377B (en) * | 2020-12-15 | 2022-03-29 | 浙江口碑网络技术有限公司 | Order processing method and device, storage medium and electronic equipment |
| WO2023221448A1 (en) * | 2022-05-17 | 2023-11-23 | 北京京东叁佰陆拾度电子商务有限公司 | Order allocation method and apparatus, and storage medium |
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