CN117252496A - Regional intelligent logistics coordination system - Google Patents
Regional intelligent logistics coordination system Download PDFInfo
- Publication number
- CN117252496A CN117252496A CN202310221262.XA CN202310221262A CN117252496A CN 117252496 A CN117252496 A CN 117252496A CN 202310221262 A CN202310221262 A CN 202310221262A CN 117252496 A CN117252496 A CN 117252496A
- Authority
- CN
- China
- Prior art keywords
- logistics
- target
- sending
- receiving
- day
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000005192 partition Methods 0.000 claims abstract description 144
- 230000007246 mechanism Effects 0.000 claims abstract description 25
- 238000012545 processing Methods 0.000 claims abstract description 18
- 230000005540 biological transmission Effects 0.000 claims description 16
- 238000013528 artificial neural network Methods 0.000 claims description 13
- 238000000034 method Methods 0.000 claims description 10
- 238000012549 training Methods 0.000 claims description 6
- 230000009471 action Effects 0.000 claims description 2
- 238000010276 construction Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 238000007781 pre-processing Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 230000004069 differentiation Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000001125 extrusion Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000003446 ligand Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Molecular Biology (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Evolutionary Computation (AREA)
- Computational Linguistics (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Strategic Management (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a zoned intelligent logistics coordination system, which comprises: the regional division device is used for performing regional treatment on the target city to obtain each logistics service region; the area judging mechanism is used for predicting the logistics receiving data and the logistics sending quantity of each logistics service partition in the day after the zero point; and the logistics coordination mechanism is used for adjusting the quantity of the logistics receiving resources and the quantity of the logistics sending resources of the current day in the target city range based on the received logistics receiving data and the logistics sending quantity aiming at each logistics service subarea. According to the invention, on the basis of carrying out the division processing of the logistics service subareas by adopting the customized regional division mode, the logistics service requirements of the logistics service subareas at the future moment can be intelligently judged according to the historical logistics information and the subarea configuration data of the surrounding logistics service subareas aiming at each logistics service subarea, so that the dynamic matching of the logistics service requirements and logistics service resources is realized.
Description
Technical Field
The invention relates to the field of intelligent logistics, in particular to a zoned intelligent logistics coordination system.
Background
The intelligent logistics is a modern logistics mode for realizing the fine, dynamic and visual management of each link of logistics through intelligent technical means such as intelligent software and hardware, the Internet of things and big data, improving the intelligent analysis decision and the automatic operation execution capacity of a logistics system and improving the logistics operation efficiency.
Some electronic enterprises propose to establish a supply chain with advanced, interconnected and intelligent characteristics in the future, and generate an intelligent supply chain concept of real-time information through sensors, RFID tags, brakes, GPS and other devices and systems, so that the Internet of things and a sensing network are integrated with the existing Internet more seriously, and the automation, visualization, controllability, intellectualization and networking of logistics are realized through fine, dynamic and scientific management, thereby improving the resource utilization rate and productivity level and creating comprehensive connotations of richer social values.
Meanwhile, the sensor is embedded and equipped into various objects such as a power grid, a railway, a bridge, a tunnel, a highway, a building, a water supply system, a dam, an oil gas pipeline and the like, and is commonly connected to form a so-called Internet of things, then the Internet of things is integrated with the existing Internet to realize the integration of a human society and a physical system, in the integrated network, a central computer group with super-strong capability exists, and the real-time management and control of personnel, machines, equipment and infrastructure in the integrated network can be implemented.
However, in the practical application of the smart logistics, it is found that, because the resources for performing the logistics management in each target city are limited, for example, the logistics distribution personnel, the logistics distribution vehicles or the logistics supporting facilities are limited, if the resources are evenly distributed to each subdivision region, the resources of some subdivision regions are relatively insufficient, and the resources of other subdivision regions are relatively excessive, so that the dilemma of material extrusion or resource idling is easily caused.
Prior art 1 discloses a method and apparatus for distributing a logistics task (application publication number: CN 115409328A), and a specific embodiment of the method includes: determining one or more cross-zone logistics tasks to be allocated, wherein the cross-zone logistics tasks indicate logistics addresses; determining a target dispatcher identifier capable of transregional dispatching according to the transregional white list; the cross-region white list correspondingly stores the logistics address and one or more distribution operator identifiers; and distributing the one or more transregional logistics tasks to the logistics sites corresponding to the target ligand identifiers. The implementation mode achieves the purpose of transregional logistics, dynamically expands the distribution and transportation range corresponding to a distribution and transportation operator, improves the transregional flexibility, and further improves the transregional logistics efficiency.
The prior art 2 discloses a big data-based logistics information processing method and an artificial intelligent server (application publication number: CN115330319 a), which enables an artificial intelligent neural network according to a plurality of first distribution resource distribution information examples of a first intelligent logistics distribution environment to obtain a plurality of second distribution resource distribution information examples; training a first resource distribution differentiation analysis network for the second intelligent logistics distribution environment according to a plurality of third distribution resource distribution information examples of the second intelligent logistics distribution environment and the type differentiation keywords corresponding to the third distribution resource distribution information examples; and performing information selection processing according to the quantized trusted data on the plurality of second distribution resource distribution information examples; and training a second resource distribution differentiation analysis network according to the obtained second distribution resource distribution information example. According to the application, the distribution resource distribution information examples of different intelligent logistics distribution environments can be intelligently obtained, and further the accuracy and timeliness of the differential analysis of the distribution resource distribution information are improved.
Prior art 3 discloses an "intelligent logistics distribution management system" (application publication number: CN112785475 a) comprising: the system comprises a preprocessing server, a parcel distribution server, a database and a logistics distribution terminal, wherein the database is respectively in communication connection with the preprocessing server and the parcel distribution server; the logistics distribution terminal is respectively in communication connection with the preprocessing server and the parcel distribution server; the preprocessing server includes: the system comprises a data acquisition unit, a core distribution area unit, an area dividing unit and an area correcting unit. And the preprocessing server obtains a core distribution area according to the distribution data of the logistics distribution personnel, the distribution data of the package end position and the distribution data of the package start position. Dividing the package into a first distribution area and a second distribution area according to the distribution starting point position and the package distribution ending point position. The parcel distribution server distributes the parcels in the first distribution area and the second distribution area in sequence to obtain a plurality of logistics distribution schemes, and the logistics distribution schemes are sent to corresponding logistics distribution terminals.
Disclosure of Invention
Compared with the prior art, the regional intelligent logistics coordination system provided by the invention can intelligently judge the logistics service demands of logistics service partitions at future time according to the historical logistics information of surrounding logistics service partitions and the logistics service data of target cities on the basis of carrying out the division processing of each logistics service partition on the target cities for executing intelligent logistics management by adopting a customized regional division mode, thereby executing dynamic allocation of logistics resources in the range of the target cities, ensuring the dispatching efficiency of each logistics service partition and providing a reliable information basis.
According to an aspect of the present invention, there is provided a zoned intelligent logistics coordination system, the system comprising:
the regional division device is used for executing partition processing on the target city to obtain each logistics service partition, each logistics service partition comprises more than one city block, and the standard deviation of the distribution areas of the entities corresponding to each logistics service partition obtained by executing the partition processing on the target city is smaller than or equal to a set standard deviation threshold;
the timing service device is used for providing timing service and sending out a data acquisition request when the zero point of each day arrives;
the acquisition execution device is respectively connected with the timing service device and the cloud storage node and is used for acquiring the adjacent area logistics data of each day of a set number before the zero point from the cloud storage node aiming at the target logistics service partition when the data acquisition request is received;
the regional judgment mechanism is connected with the acquisition execution device and is used for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the current day after the zero point based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of adjacent areas before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, and outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number respectively;
the logistics coordination mechanism is connected with the area judgment mechanism and is used for adjusting the number of logistics receiving resources and the number of logistics sending resources on the same day in the range of the target city based on the received reference receiving number and the reference sending number;
when a data acquisition request is received, acquiring, for a target logistics service partition, each neighboring logistics data corresponding to each day of a set number before a zero point from the cloud storage node, wherein the neighboring logistics data comprises: the adjacent area logistics data corresponding to each day comprise logistics receiving data and logistics sending quantity respectively corresponding to all logistics service areas around the target logistics service area;
wherein adjusting the number of the current-day logistics reception resources and the number of the logistics transmission resources within the target city based on the received reference reception number and the reference transmission number comprises: the total number of the logistics receiving resources on the same day in the range of the target city and the total number of the logistics sending resources are respectively fixed values.
Thus, the invention has at least the following three beneficial technical advances:
firstly, carrying out division processing on each logistics service partition of a target city for executing intelligent logistics management by adopting a customized regional division mode to obtain a customized target for intelligent logistics coordination, wherein each logistics service partition obtained by the division processing comprises more than one city block, and the standard deviation of each entity distribution area corresponding to each logistics service partition is smaller than or equal to a set standard deviation threshold;
secondly, intelligently judging logistics receiving data and logistics sending quantity of the target logistics service partition in the day after the zero point based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set quantity of each day before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, and outputting the logistics receiving data and the logistics sending quantity as reference receiving quantity and reference sending quantity respectively, so that reliable judgment of future logistics receiving and sending data of each target logistics service partition is realized;
and thirdly, aiming at each target logistics service partition, adopting a logistics coordination mechanism to adjust the quantity of logistics receiving resources and the quantity of logistics sending resources of the target logistics service partition in the current day within the range of the target city based on the received reference receiving quantity and the reference sending quantity, thereby completing intelligent logistics management of the target city.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings, in which:
fig. 1 is a block diagram showing the construction of a zoned intelligent logistics coordination system in accordance with a first embodiment of the present invention.
Fig. 2 is a block diagram showing the construction of a zoned intelligent logistics coordination system in accordance with a second embodiment of the present invention.
Fig. 3 is a block diagram showing the construction of a zoned intelligent logistics coordination system in accordance with a third embodiment of the present invention.
Detailed Description
Embodiments of the zoned intelligent logistics coordination system of the present invention will be described in detail below with reference to the accompanying drawings.
First embodiment
Fig. 1 is a block diagram showing a construction of a zoned intelligent logistics coordination system in accordance with a first embodiment of the present invention, the system comprising:
the regional division device is used for executing partition processing on the target city to obtain each logistics service partition, each logistics service partition comprises more than one city block, and the standard deviation of the distribution areas of the entities corresponding to each logistics service partition obtained by executing the partition processing on the target city is smaller than or equal to a set standard deviation threshold;
the timing service device is used for providing timing service and sending out a data acquisition request when the zero point of each day arrives;
the acquisition execution device is respectively connected with the timing service device and the cloud storage node and is used for acquiring the adjacent area logistics data of each day of a set number before the zero point from the cloud storage node aiming at the target logistics service partition when the data acquisition request is received;
the regional judgment mechanism is connected with the acquisition execution device and is used for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the current day after the zero point based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of adjacent areas before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, and outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number respectively;
the logistics coordination mechanism is connected with the area judgment mechanism and is used for adjusting the number of logistics receiving resources and the number of logistics sending resources on the same day in the range of the target city based on the received reference receiving number and the reference sending number;
when a data acquisition request is received, acquiring, for a target logistics service partition, each neighboring logistics data corresponding to each day of a set number before a zero point from the cloud storage node, wherein the neighboring logistics data comprises: the adjacent area logistics data corresponding to each day comprise logistics receiving data and logistics sending quantity respectively corresponding to all logistics service areas around the target logistics service area;
wherein adjusting the number of the current-day logistics reception resources and the number of the logistics transmission resources within the target city based on the received reference reception number and the reference transmission number comprises: the total number of the logistics receiving resources on the same day in the target city range and the total number of the logistics sending resources are respectively fixed values;
the method for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point based on the entity distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of each day before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of the logistics service partitions in the target city, and respectively outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number comprises the following steps: the more the number of the city blocks included in the target logistics service partition is, the larger the value of the set number is;
wherein adjusting the number of the current-day logistics reception resources and the number of the logistics transmission resources within the target city based on the received reference reception number and the reference transmission number comprises: the more the received reference receiving quantity is, the more the quantity of the logistics receiving resources on the current day after adjustment is;
the method for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point based on the entity distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of each day before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of the logistics service partitions in the target city, and respectively outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number comprises the following steps: and executing the intelligent judgment action by adopting the trained deep neural network.
Second embodiment
Fig. 2 is a block diagram showing a construction of a zoned intelligent logistics coordination system in accordance with a second embodiment of the present invention, comprising:
the regional division device is used for executing partition processing on the target city to obtain each logistics service partition, each logistics service partition comprises more than one city block, and the standard deviation of the distribution areas of the entities corresponding to each logistics service partition obtained by executing the partition processing on the target city is smaller than or equal to a set standard deviation threshold;
the timing service device is used for providing timing service and sending out a data acquisition request when the zero point of each day arrives;
the acquisition execution device is respectively connected with the timing service device and the cloud storage node and is used for acquiring the adjacent area logistics data of each day of a set number before the zero point from the cloud storage node aiming at the target logistics service partition when the data acquisition request is received;
the regional judgment mechanism is connected with the acquisition execution device and is used for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the current day after the zero point based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of adjacent areas before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, and outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number respectively;
the logistics coordination mechanism is connected with the area judgment mechanism and is used for adjusting the number of logistics receiving resources and the number of logistics sending resources on the same day in the range of the target city based on the received reference receiving number and the reference sending number;
and the information storage chip is connected with the region dividing device and used for storing the positioning data of the entity geographic region corresponding to each logistics service partition.
Third embodiment
Fig. 3 is a block diagram showing a construction of a zoned intelligent logistics coordination system in accordance with a third embodiment of the present invention, comprising:
the regional division device is used for executing partition processing on the target city to obtain each logistics service partition, each logistics service partition comprises more than one city block, and the standard deviation of the distribution areas of the entities corresponding to each logistics service partition obtained by executing the partition processing on the target city is smaller than or equal to a set standard deviation threshold;
the timing service device is used for providing timing service and sending out a data acquisition request when the zero point of each day arrives;
the acquisition execution device is respectively connected with the timing service device and the cloud storage node and is used for acquiring the adjacent area logistics data of each day of a set number before the zero point from the cloud storage node aiming at the target logistics service partition when the data acquisition request is received;
the regional judgment mechanism is connected with the acquisition execution device and is used for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the current day after the zero point based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of adjacent areas before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, and outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number respectively;
the logistics coordination mechanism is connected with the area judgment mechanism and is used for adjusting the number of logistics receiving resources and the number of logistics sending resources on the same day in the range of the target city based on the received reference receiving number and the reference sending number;
and the training execution mechanism is connected with the logistics coordination mechanism and is used for training the deep neural network for a plurality of times and sending the trained deep neural network to the logistics coordination mechanism.
Next, a further explanation of the specific structure of the zoned intelligent logistics coordination system of the present invention will be continued.
In a zoned intelligent logistics coordination system in accordance with various embodiments of the present invention:
adjusting the number of the current-day logistics receiving resources and the number of the logistics sending resources within the target city based on the received reference receiving number and the reference sending number comprises: the more the number of received reference transmissions, the more the number of logistics transmission resources on the same day after adjustment;
wherein adjusting the number of the current-day logistics reception resources and the number of the logistics transmission resources within the target city based on the received reference reception number and the reference transmission number comprises: the logistics receiving resource or the logistics transmitting resource is a logistics personnel performing a receiving/transmitting operation, a logistics vehicle performing the receiving/transmitting operation or a logistics supporting facility performing the receiving/transmitting operation.
And in a zoned intelligent logistics coordination system in accordance with various embodiments of the present invention:
based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to each day of the set number before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point, and respectively outputting the logistics receiving number and the reference sending number as reference receiving number and reference sending number, wherein the method comprises the following steps: taking the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of each day before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city as the item-by-item input content of the trained deep neural network;
the method for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point based on the entity distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of each day before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of the logistics service partitions in the target city, and respectively outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number comprises the following steps: the trained deep neural network is operated to obtain the logistics receiving data and the logistics sending quantity of the target logistics service partition output by the deep neural network in the day after the zero point.
In addition, in the zoned intelligent logistics coordination system, adjusting the number of the logistics reception resources and the number of the logistics transmission resources on the same day within the target city range based on the received reference reception number and the reference transmission number comprises: and (3) adopting a numerical simulation formula to express the numerical correspondence between the received reference receiving quantity and the reference transmitting quantity and the quantity of the logistics receiving resources and the quantity of the logistics transmitting resources on the current day after adjustment in the range of the target city.
By adopting the regional intelligent logistics coordination system, the technical problem that logistics service resources of all regions in the whole city range are difficult to consider in the prior art can be solved, and on the basis of carrying out the division processing of logistics service partitions by adopting a customized regional division mode, the logistics service requirements of the logistics service partitions at the future moment can be intelligently judged according to the historical logistics information and partition configuration data of the surrounding logistics service partitions aiming at each logistics service partition, so that the dynamic matching of the logistics service requirements and the logistics service resources is realized.
Thus, the invention has at least the following three beneficial technical advances:
firstly, carrying out division processing on each logistics service partition of a target city for executing intelligent logistics management by adopting a customized regional division mode to obtain a customized target for intelligent logistics coordination, wherein each logistics service partition obtained by the division processing comprises more than one city block, and the standard deviation of each entity distribution area corresponding to each logistics service partition is smaller than or equal to a set standard deviation threshold;
secondly, intelligently judging logistics receiving data and logistics sending quantity of the target logistics service partition in the day after the zero point based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set quantity of each day before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, and outputting the logistics receiving data and the logistics sending quantity as reference receiving quantity and reference sending quantity respectively, so that reliable judgment of future logistics receiving and sending data of each target logistics service partition is realized;
and thirdly, aiming at each target logistics service partition, adopting a logistics coordination mechanism to adjust the quantity of logistics receiving resources and the quantity of logistics sending resources of the target logistics service partition in the current day within the range of the target city based on the received reference receiving quantity and the reference sending quantity, thereby completing intelligent logistics management of the target city.
Although the invention has been described with reference to the structures disclosed herein, the invention is not limited to the details given and this application is intended to cover such modifications or variations as fall within the purpose of the improvement or the scope of the following claims.
Claims (10)
1. A zoned intelligent logistics coordination system, the system comprising:
the regional division device is used for executing partition processing on the target city to obtain each logistics service partition, each logistics service partition comprises more than one city block, and the standard deviation of the distribution areas of the entities corresponding to each logistics service partition obtained by executing the partition processing on the target city is smaller than or equal to a set standard deviation threshold;
the timing service device is used for providing timing service and sending out a data acquisition request when the zero point of each day arrives;
the acquisition execution device is respectively connected with the timing service device and the cloud storage node and is used for acquiring the adjacent area logistics data of each day of a set number before the zero point from the cloud storage node aiming at the target logistics service partition when the data acquisition request is received;
the regional judgment mechanism is connected with the acquisition execution device and is used for intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the current day after the zero point based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of adjacent areas before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, and outputting the logistics receiving data and the logistics sending number as the reference receiving number and the reference sending number respectively;
the logistics coordination mechanism is connected with the area judgment mechanism and is used for adjusting the number of logistics receiving resources and the number of logistics sending resources on the same day in the range of the target city based on the received reference receiving number and the reference sending number;
when a data acquisition request is received, acquiring, for a target logistics service partition, each neighboring logistics data corresponding to each day of a set number before a zero point from the cloud storage node, wherein the neighboring logistics data comprises: the adjacent area logistics data corresponding to each day comprise logistics receiving data and logistics sending quantity respectively corresponding to all logistics service areas around the target logistics service area;
wherein adjusting the number of the current-day logistics reception resources and the number of the logistics transmission resources within the target city based on the received reference reception number and the reference transmission number comprises: the total number of the logistics receiving resources on the same day in the range of the target city and the total number of the logistics sending resources are respectively fixed values.
2. The zoned intelligent logistics coordination system of claim 1, wherein:
based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to each day of the set number before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point, and respectively outputting the logistics receiving number and the reference sending number as reference receiving number and reference sending number, wherein the method comprises the following steps: the more the number of the city blocks included in the target logistics service partition, the larger the value of the set number.
3. The zoned intelligent logistics coordination system of claim 2, wherein:
adjusting the number of the current-day logistics receiving resources and the number of the logistics sending resources within the target city based on the received reference receiving number and the reference sending number comprises: the more reference received quantity is, the more the quantity of the logistics receiving resources on the current day after adjustment is.
4. The zoned intelligent logistics coordination system of claim 3 wherein:
based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to each day of the set number before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point, and respectively outputting the logistics receiving number and the reference sending number as reference receiving number and reference sending number, wherein the method comprises the following steps: and executing the intelligent judgment action by adopting the trained deep neural network.
5. The zoned intelligent logistics coordination system of claim 4, further comprising:
and the information storage chip is connected with the region dividing device and used for storing the positioning data of the entity geographic region corresponding to each logistics service partition.
6. The zoned intelligent logistics coordination system of claim 4, further comprising:
and the training execution mechanism is connected with the logistics coordination mechanism and is used for training the deep neural network for a plurality of times and sending the trained deep neural network to the logistics coordination mechanism.
7. The zoned intelligent logistics coordination system of any one of claims 4-6, wherein:
adjusting the number of the current-day logistics receiving resources and the number of the logistics sending resources within the target city based on the received reference receiving number and the reference sending number comprises: the more reference transmissions are received, the more the number of logistics transmission resources on the same day after adjustment.
8. The zoned intelligent logistics coordination system of claim 7, wherein:
adjusting the number of the current-day logistics receiving resources and the number of the logistics sending resources within the target city based on the received reference receiving number and the reference sending number comprises: the logistics receiving resource or the logistics transmitting resource is a logistics personnel performing a receiving/transmitting operation, a logistics vehicle performing the receiving/transmitting operation or a logistics supporting facility performing the receiving/transmitting operation.
9. The zoned intelligent logistics coordination system of any one of claims 4-6, wherein:
based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to each day of the set number before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point, and respectively outputting the logistics receiving number and the reference sending number as reference receiving number and reference sending number, wherein the method comprises the following steps: and taking the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to the set number of days before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city as the item-by-item input contents of the trained deep neural network.
10. The zoned intelligent logistics coordination system of claim 9, wherein:
based on the physical distribution area of the target logistics service partition, the logistics data of each adjacent area corresponding to each day of the set number before the zero point, the total number of all logistics service partitions around the target logistics service partition and the total number of logistics service partitions in the target city, intelligently judging the logistics receiving data and the logistics sending number of the target logistics service partition in the day after the zero point, and respectively outputting the logistics receiving number and the reference sending number as reference receiving number and reference sending number, wherein the method comprises the following steps: the trained deep neural network is operated to obtain the logistics receiving data and the logistics sending quantity of the target logistics service partition output by the deep neural network in the day after the zero point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310221262.XA CN117252496B (en) | 2023-03-09 | Regional intelligent logistics coordination system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310221262.XA CN117252496B (en) | 2023-03-09 | Regional intelligent logistics coordination system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117252496A true CN117252496A (en) | 2023-12-19 |
| CN117252496B CN117252496B (en) | 2024-07-26 |
Family
ID=
Citations (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108090643A (en) * | 2016-11-21 | 2018-05-29 | 莫元劲 | Express logistics dispatching method and device |
| CN109002902A (en) * | 2018-06-11 | 2018-12-14 | 华东理工大学 | Subregion multistage fresh agricultural products dynamic vehicle method for optimizing route |
| CN109003028A (en) * | 2018-07-17 | 2018-12-14 | 北京百度网讯科技有限公司 | Method and apparatus for dividing logistics region |
| CN109377084A (en) * | 2018-11-15 | 2019-02-22 | 跨越速运集团有限公司 | Dispatch server and Intelligent logistics dispatching service system based on the dispatch server |
| CN109426885A (en) * | 2017-08-28 | 2019-03-05 | 北京小度信息科技有限公司 | Order allocation method and device |
| CN109829667A (en) * | 2017-11-23 | 2019-05-31 | 菜鸟智能物流控股有限公司 | Method and device for predicting parcel volume of logistics node |
| US20200005420A1 (en) * | 2017-06-21 | 2020-01-02 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for transportation capacity dispatch |
| KR102095735B1 (en) * | 2019-05-20 | 2020-04-01 | 김성묵 | Logistics vender system using cargo based on region and distribution method thereof |
| KR102146569B1 (en) * | 2019-12-16 | 2020-08-20 | 손정진 | Client-customized delivery scheduling system |
| CN111754175A (en) * | 2020-06-28 | 2020-10-09 | 湖州佳东物流设备有限公司 | Logistics scheduling method |
| CN112149935A (en) * | 2019-06-28 | 2020-12-29 | 坎德拉（深圳）科技创新有限公司 | Logistics piece dispatching method, dispatching server, system and storage medium |
| CN112365217A (en) * | 2020-12-07 | 2021-02-12 | 吉林大学 | Method for extracting spatial aggregation characteristics of logistics clusters entering factory |
| CN112685385A (en) * | 2020-12-31 | 2021-04-20 | 广西中科曙光云计算有限公司 | Big data platform for smart city construction |
| CN112703457A (en) * | 2018-05-07 | 2021-04-23 | 强力物联网投资组合2016有限公司 | Method and system for data collection, learning and machine signal streaming for analysis and maintenance using industrial internet of things |
| CN113191589A (en) * | 2021-03-29 | 2021-07-30 | 湖州宏威新能源汽车有限公司 | Allocation method for automatically driving logistics vehicle |
| CN113704298A (en) * | 2020-05-20 | 2021-11-26 | 菜鸟智能物流控股有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN113935561A (en) * | 2020-07-13 | 2022-01-14 | 顺丰科技有限公司 | Method, device and system for distributing and dispatching tasks and computer readable storage medium |
| CN114493418A (en) * | 2021-12-28 | 2022-05-13 | 上海东普信息科技有限公司 | Party allocation method, device, computer equipment and storage medium |
| CN114548880A (en) * | 2022-03-07 | 2022-05-27 | 广汽丰田汽车有限公司 | Logistics planning method, equipment, device and storage medium |
| CN114596040A (en) * | 2022-05-09 | 2022-06-07 | 浙江口碑网络技术有限公司 | Logistics area division method and device, storage medium and electronic equipment |
| CN114819852A (en) * | 2022-05-24 | 2022-07-29 | 黄小兵 | Logistics planning system and method for smart city |
| CN115239223A (en) * | 2022-06-09 | 2022-10-25 | 上海东普信息科技有限公司 | Allocation center task scheduling method, device, equipment and storage medium |
| CN115310799A (en) * | 2022-07-30 | 2022-11-08 | 东南大学 | Method for three-stage evaluation of urban logistics space-time evolution logistics efficiency |
| CN115439028A (en) * | 2022-11-08 | 2022-12-06 | 苏州美集供应链管理股份有限公司 | Transportation resource optimization system and method following dynamic change of data |
| CN115456538A (en) * | 2022-09-20 | 2022-12-09 | 北京联合大学 | Multi-vehicle multi-region urban cold chain low-carbon logistics distribution method |
| CN115719110A (en) * | 2022-11-11 | 2023-02-28 | 轩创(广州)网络科技有限公司 | Traffic resource dynamic optimization method and system based on geographic information |
Patent Citations (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108090643A (en) * | 2016-11-21 | 2018-05-29 | 莫元劲 | Express logistics dispatching method and device |
| US20200005420A1 (en) * | 2017-06-21 | 2020-01-02 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for transportation capacity dispatch |
| CN109426885A (en) * | 2017-08-28 | 2019-03-05 | 北京小度信息科技有限公司 | Order allocation method and device |
| CN109829667A (en) * | 2017-11-23 | 2019-05-31 | 菜鸟智能物流控股有限公司 | Method and device for predicting parcel volume of logistics node |
| CN112703457A (en) * | 2018-05-07 | 2021-04-23 | 强力物联网投资组合2016有限公司 | Method and system for data collection, learning and machine signal streaming for analysis and maintenance using industrial internet of things |
| CN109002902A (en) * | 2018-06-11 | 2018-12-14 | 华东理工大学 | Subregion multistage fresh agricultural products dynamic vehicle method for optimizing route |
| CN109003028A (en) * | 2018-07-17 | 2018-12-14 | 北京百度网讯科技有限公司 | Method and apparatus for dividing logistics region |
| CN109377084A (en) * | 2018-11-15 | 2019-02-22 | 跨越速运集团有限公司 | Dispatch server and Intelligent logistics dispatching service system based on the dispatch server |
| KR102095735B1 (en) * | 2019-05-20 | 2020-04-01 | 김성묵 | Logistics vender system using cargo based on region and distribution method thereof |
| CN112149935A (en) * | 2019-06-28 | 2020-12-29 | 坎德拉（深圳）科技创新有限公司 | Logistics piece dispatching method, dispatching server, system and storage medium |
| KR102146569B1 (en) * | 2019-12-16 | 2020-08-20 | 손정진 | Client-customized delivery scheduling system |
| CN113704298A (en) * | 2020-05-20 | 2021-11-26 | 菜鸟智能物流控股有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN111754175A (en) * | 2020-06-28 | 2020-10-09 | 湖州佳东物流设备有限公司 | Logistics scheduling method |
| CN113935561A (en) * | 2020-07-13 | 2022-01-14 | 顺丰科技有限公司 | Method, device and system for distributing and dispatching tasks and computer readable storage medium |
| CN112365217A (en) * | 2020-12-07 | 2021-02-12 | 吉林大学 | Method for extracting spatial aggregation characteristics of logistics clusters entering factory |
| CN112685385A (en) * | 2020-12-31 | 2021-04-20 | 广西中科曙光云计算有限公司 | Big data platform for smart city construction |
| CN113191589A (en) * | 2021-03-29 | 2021-07-30 | 湖州宏威新能源汽车有限公司 | Allocation method for automatically driving logistics vehicle |
| CN114493418A (en) * | 2021-12-28 | 2022-05-13 | 上海东普信息科技有限公司 | Party allocation method, device, computer equipment and storage medium |
| CN114548880A (en) * | 2022-03-07 | 2022-05-27 | 广汽丰田汽车有限公司 | Logistics planning method, equipment, device and storage medium |
| CN114596040A (en) * | 2022-05-09 | 2022-06-07 | 浙江口碑网络技术有限公司 | Logistics area division method and device, storage medium and electronic equipment |
| CN114819852A (en) * | 2022-05-24 | 2022-07-29 | 黄小兵 | Logistics planning system and method for smart city |
| CN115239223A (en) * | 2022-06-09 | 2022-10-25 | 上海东普信息科技有限公司 | Allocation center task scheduling method, device, equipment and storage medium |
| CN115310799A (en) * | 2022-07-30 | 2022-11-08 | 东南大学 | Method for three-stage evaluation of urban logistics space-time evolution logistics efficiency |
| CN115456538A (en) * | 2022-09-20 | 2022-12-09 | 北京联合大学 | Multi-vehicle multi-region urban cold chain low-carbon logistics distribution method |
| CN115439028A (en) * | 2022-11-08 | 2022-12-06 | 苏州美集供应链管理股份有限公司 | Transportation resource optimization system and method following dynamic change of data |
| CN115719110A (en) * | 2022-11-11 | 2023-02-28 | 轩创(广州)网络科技有限公司 | Traffic resource dynamic optimization method and system based on geographic information |
Non-Patent Citations (2)
| Title |
|---|
| 肖亮;: "基于物联网技术的物流园区供应链集成管理平台构建", 电信科学, no. 04, 15 April 2011 (2011-04-15) * |
| 葛显龙;薛桂琴;: "基于前摄性调度的车辆路径问题", 计算机集成制造***, no. 08, 9 May 2018 (2018-05-09) * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108449286A (en) | Network bandwidth resources distribution method and device | |
| CN105471759A (en) | Network traffic scheduling method and apparatus for data centers | |
| CN102819950A (en) | Carrying aid decision making system and method for traffic tool | |
| CN111738409B (en) | Resource scheduling method and related equipment thereof | |
| CN112550044B (en) | Charging station load adjustment method, system, device, equipment and storage medium | |
| CN105702017A (en) | Vehicle scheduling method and device | |
| CN111695726A (en) | Bus scheduling schedule updating method and device | |
| CN111353663A (en) | Task allocation method, device, equipment and storage medium thereof | |
| CN115271556B (en) | Robot task scheduling method and device, readable storage medium and electronic equipment | |
| CN115862823B (en) | Intelligent scheduling method and system for equipment based on mobile network | |
| CN113420195A (en) | Method and system for determining fault type of intelligent electric meter | |
| CN117252496B (en) | Regional intelligent logistics coordination system | |
| CN116737804B (en) | Gas data hierarchical processing method and system based on intelligent gas Internet of things | |
| CN117252496A (en) | Regional intelligent logistics coordination system | |
| CN105260245A (en) | Resource scheduling method and device | |
| CN115640986B (en) | Robot scheduling method, device, equipment and medium based on rewards | |
| CN112819228A (en) | Task processing method and device, storage medium and electronic equipment | |
| CN116683444A (en) | Power grid management system applying AI intelligent agent | |
| CN114138453B (en) | Resource optimization allocation method and system suitable for edge computing environment | |
| CN114372661A (en) | Logistics sorting method, device and equipment based on region division and storage medium | |
| CN107591000A (en) | A kind of logistic car command methods and system based on traffic big data | |
| CN113538887A (en) | Intelligent bus terminal system | |
| Karimi et al. | Intelligent and Decentralized Resource Allocation in Vehicular Edge Computing Networks | |
| CN112116170A (en) | Method and device for automatically planning work route | |
| CN111915064B (en) | Method and device for adjusting and simulating public transport network |
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 | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20240705 Address after: Room 105, Building 1, No. 3 Baima Huangjin 1st Road, Nancheng Street, Dongguan City, Guangdong Province, 523000 Applicant after: Guangdong Lianyu Logistics Co.,Ltd. Country or region after: China Address before: Room 611, Building 1, No. 98 Yingchun East Road, Hailing Industrial Park, Taizhou City, Jiangsu Province, 225300 Applicant before: Jiangsu Qibo Cold Chain Technology Co.,Ltd. Country or region before: China |
|
| GR01 | Patent grant |