CN114648169A - Cold chain delivery quality and storage management system based on big data - Google Patents
Cold chain delivery quality and storage management system based on big data Download PDFInfo
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- CN114648169A CN114648169A CN202210362282.4A CN202210362282A CN114648169A CN 114648169 A CN114648169 A CN 114648169A CN 202210362282 A CN202210362282 A CN 202210362282A CN 114648169 A CN114648169 A CN 114648169A
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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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
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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
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
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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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- 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
- G06Q10/0835—Relationships between shipper or supplier and carriers
- G06Q10/08355—Routing methods
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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
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
Abstract
The invention discloses a cold chain distribution quality and storage management system based on big data, which comprises: the order acquisition module is used for acquiring a distribution order; the classification module is used for classifying the distribution orders; the distribution task generating module is used for generating distribution tasks; the transportation monitoring module is used for monitoring goods in the vehicle and the vehicle in the transportation process; the en-route order adding and dispatching module is used for adding and dispatching the delivery orders in the transport en-route, and the delivery places of the added and dispatched delivery orders are located in the way which is not passed through; the goods transceiver module is used for carrying out goods handover with the freight vehicle at a receiving place or a delivery place of the additionally distributed delivery order. This application increases the goods that the dispatch module will be can be carried on the way along the way through the order on the way, has reduced the shipment cost, has reduced freight train idle load rate, has improved the transport rate of cold chain delivery, has increased the vehicle and has been long when going at highway section through goods transceiver module, has increased conveying efficiency and has reduced transit time, has guaranteed the quality of carrying the goods.
Description
Technical Field
The invention belongs to the field of cold chain distribution and storage, and particularly relates to a cold chain distribution quality and storage management system based on big data.
Background
Cold-chain transportation (Cold-chain transportation) refers to transportation in which the transported goods are kept at a constant temperature throughout the transportation process, regardless of the links of loading, unloading, transportation, changing transportation modes, changing packaging equipment, and the like.
The cold chain transportation mode can be road transportation, waterway transportation, railway transportation and air transportation, and also can be a comprehensive transportation mode formed by a plurality of transportation modes. Cold chain transportation is an important link of cold chain logistics, the cold chain transportation cost is high, a more complex mobile refrigeration technology and an insulation can manufacturing technology are included, and the cold chain transportation management contains more risks and uncertainties.
The existing cold chain transportation is to perform one-time distribution task deployment and distribution based on the delivery destination and temperature requirements, and due to the timeliness of distribution, the carriers are not fully loaded at times and need to start to transport, so that the transportation cost is greatly increased and is difficult to control; the automatic management level of the existing cold chain delivery is low, the route is basically planned manually, the change and optimization cannot be performed in real time according to delivery order information, the transportation speed is always critical for cold chain transportation, the existing grading transportation means of the cold chain transportation has the problem of unclear division of labor, the existing transportation method generally needs to transport goods to a refrigeration house of a receiving place for unloading, the goods are unloaded to the refrigeration house of the next receiving city before starting, and the vehicles delay the city commuting time after the lower speed on the way, so that the problems that the transportation and loading conditions cannot be regulated and controlled in the delivery process, much time is wasted in the delivery process, and a method is needed to solve the problems in the prior art.
Disclosure of Invention
The present invention provides a cold chain distribution quality and storage management system based on big data, so as to solve the problems of the prior art.
In order to achieve the above object, the present invention provides a cold chain delivery quality and storage management system based on big data, including:
the system comprises an order acquisition module, a classification module, a distribution task generation module, a loading module, a transportation monitoring module, an on-way order adding module and a cargo receiving and dispatching module;
the order acquisition module is used for acquiring a distribution order;
the classification module is used for classifying the distribution orders to obtain order classification conditions;
the distribution task generating module is used for generating distribution tasks based on the distribution orders and the order classification conditions;
the loading module is used for loading based on the distribution task;
the transportation monitoring module is used for monitoring goods in the vehicle and the vehicle in the transportation process;
the en-route order adding and dispatching module is used for adding and dispatching distribution orders in the transportation en-route, and the delivery places of the added and dispatched distribution orders are located in the way which is not passed through;
the goods transceiver module is used for carrying out goods handover with the freight vehicle at a receiving place or a delivery place of the additionally distributed delivery order.
Optionally, the delivery order includes a plurality of types of delivery information, and the delivery information includes a sender address, a receiver address, a type of goods, a weight of goods, a volume of goods, a temperature requirement for delivery, and a required delivery time.
Optionally, the classification module includes a temperature classification module, and the temperature classification module is configured to classify the delivery orders based on the delivered temperature demand, and obtain a plurality of temperature classification conditions as order classification conditions.
Optionally, in each of the temperature classification cases, a delivery route is generated based on the consignee address and the delivery time, and a delivery task is generated based on the delivery route and the delivery order.
Optionally, the generating a delivery route based on the consignee address and the arrival time includes:
obtaining a predicted delivery time based on the consignee address and the truck departure address, and taking the predicted delivery time as a first predicted delivery time if the predicted delivery time is within the range of the required delivery time;
generating a delivery route based on a number of the first estimated time of arrival and the consignee address.
Optionally, the loading module includes an origin loading module and a route loading module;
the initial loading module comprises a first loading module and a second loading module;
the first loading module is used for sorting the goods based on the goods receiving party address, and the farther the goods receiving party address is, the closer the goods are to the inside of the packing box, so that a first loading sequence is obtained;
the second loading module is used for placing the goods in the container from bottom to top according to the weight and the volume of the goods based on the first loading sequence, and the weight of the goods is considered preferentially;
the approach loading module is used for loading the goods received on the way.
Optionally, the transportation monitoring module includes: the cargo box monitoring module and the vehicle state monitoring module;
the container monitoring module is used for monitoring a real-time environment parameter value in the container, and if the real-time environment parameter value exceeds a preset standard environment parameter value, alarming and reminding;
the container monitoring module is also used for monitoring the free volume in the container after each loading and unloading;
the vehicle monitoring module is used for monitoring vehicle information, and the vehicle information comprises a vehicle real-time position and a vehicle real-time speed.
Optionally, the en-route order delivery module comprises a vehicle receiving calculation module, a goods delivery prediction module and an order delivery module;
the vehicle receiving calculation module is used for obtaining the time when the vehicle is expected to arrive at the address of the cargo sender on the way based on the vehicle information;
the goods delivery prediction module is used for calculating the time of delivering the goods to the address of the goods receiver;
the order adding and dispatching module is used for adding and dispatching orders for the vehicle when the sum of the time of the vehicle receiving calculation module and the time of the goods reaching the predicted module is less than the required reaching time, and the volume of the goods to be added and dispatched is less than the free volume in the container.
Optionally, the cargo transceiver module includes a receiving module and a transmitting module;
the receiving module is used for dispatching the goods receiving vehicle belonging to the area of the goods receiving address to receive goods when the vehicle reaches a high-speed port or a service area of the goods receiving address;
the sending module is used for sending the delivery vehicle belonging to the area where the delivery party address is located when the vehicle arrives at a high-speed port or a service area of the area where the delivery party address of the additionally-sent order is located on the way.
The invention has the technical effects that:
this application increases the goods that the dispatch module will be can be carried on the way along the way through the order on the way, has reduced the shipment cost, has reduced freight train idle load rate, has improved the transport rate of cold chain delivery, has increased the vehicle and has been long when going at highway section through goods transceiver module, has increased conveying efficiency and has reduced transit time, has guaranteed the quality of carrying the goods.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
fig. 1 is a schematic structural diagram in an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
As shown in fig. 1, the present embodiment provides a cold chain distribution quality and storage management system based on big data, including:
the system comprises an order acquisition module, a classification module, a distribution task generation module, a loading module, a transportation monitoring module, an on-way order adding module and a cargo receiving and dispatching module;
the order acquisition module is used for acquiring a distribution order;
the classification module is used for classifying the delivery orders to obtain order classification conditions;
the distribution task generating module is used for generating distribution tasks based on distribution orders and order classification conditions;
the loading module is used for loading based on the distribution task;
the transportation monitoring module is used for monitoring goods in the vehicle and the vehicle in the transportation process;
the en-route order adding and dispatching module is used for adding and dispatching the delivery orders in the transport en-route, and the delivery places of the added and dispatched delivery orders are located in the way which is not passed through;
the goods transceiver module is used for carrying out goods handover with the freight vehicle at a receiving place or a delivery place of the additionally distributed delivery order.
The delivery order comprises a plurality of types of delivery information, and the delivery information comprises a delivery party address, a receiving party address, a cargo type, a cargo weight, a cargo volume, a temperature requirement for delivery and a required delivery time.
The classification module comprises a temperature classification module, and the temperature classification module is used for classifying distribution orders based on the temperature requirement of delivery and obtaining a plurality of temperature classification conditions as order classification conditions.
In each temperature classification case, a delivery route is generated based on the consignee address and the arrival time, and a delivery task is generated based on the delivery route and the delivery order.
The process of generating a delivery route based on the consignee address and the delivery time includes:
obtaining estimated delivery time based on the consignee address and the truck departure address, and taking the estimated delivery time as first estimated delivery time if the estimated delivery time is within the range of the required delivery time;
a delivery route is generated based on a number of first estimated delivery times and the consignee address.
The loading module comprises an initial loading module and a path loading module;
the starting point loading module comprises a first loading module and a second loading module;
the first loading module is used for sequencing the goods based on the addresses of the goods receivers, and the farther the address of the goods receiver is, the closer the goods are to the interior of the container, so that a first loading sequence is obtained;
the second loading module is used for placing the goods in the container from bottom to top according to the weight and the volume of the goods based on the first loading sequence, and the weight of the goods is considered preferentially;
and the ground loading module is used for loading the goods received on the way.
The transportation monitoring module includes: the cargo box monitoring module and the vehicle state monitoring module;
the container monitoring module is used for monitoring real-time environmental parameter values in the container, and if the real-time environmental parameter values exceed preset standard environmental parameter values, alarming and reminding are carried out;
the container monitoring module is also used for monitoring the free volume in the container after each loading and unloading;
the vehicle monitoring module is used for monitoring vehicle information, and the vehicle information comprises a vehicle real-time position and a vehicle real-time speed.
The en-route order adding and dispatching module comprises a vehicle receiving calculation module, a goods delivery prediction module and an order adding and dispatching module;
the vehicle receiving calculation module is used for obtaining the time when the vehicle is expected to arrive at the address of the cargo sender on the way based on the vehicle information;
the goods delivery prediction module is used for calculating the time of delivering the goods to the address of the goods receiver;
the order adding and dispatching module is used for adding and dispatching orders for the vehicle when the sum of the time of the vehicle receiving calculation module and the time of the goods arriving at the prediction module is less than the required arriving time, and the volume of the goods to be added and dispatched is less than the free volume in the container.
The goods receiving and transmitting module comprises a receiving module and a transmitting module;
the receiving module is used for dispatching the receiving vehicle belonging to the area of the receiver address to receive goods when the vehicle reaches a high-speed port or a service area of the receiver address;
the sending module is used for sending the delivery vehicle belonging to the area where the delivery party address is located when the vehicle arrives at a high-speed port or a service area of the area where the delivery party address of the on-way additional order is located.
This application increases the goods that the dispatch module will be can be carried on the way along the way through the order on the way, has reduced the shipment cost, has reduced freight train idle load rate, has improved the transport rate of cold chain delivery, has increased the vehicle and has been long when going at highway section through goods transceiver module, has increased conveying efficiency and has reduced transit time, has guaranteed the quality of carrying the goods.
The above description is only for the preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. A cold chain delivery quality and storage management system based on big data is characterized by comprising: the system comprises an order acquisition module, a classification module, a distribution task generation module, a loading module, a transportation monitoring module, an on-way order adding module and a cargo receiving and dispatching module; after departure
The order acquisition module is used for acquiring a distribution order;
the classification module is used for classifying the delivery orders to obtain order classification conditions;
the distribution task generating module is used for generating distribution tasks based on the distribution orders and the order classification conditions;
the loading module is used for loading based on the distribution task;
the transportation monitoring module is used for monitoring goods in the vehicle and the vehicle in the transportation process;
the en-route order adding and dispatching module is used for adding and dispatching delivery orders in the transport en-route, and the delivery places of the added and dispatched delivery orders are located in the way which is not passed through;
the goods transceiver module is used for carrying out goods handover with the freight vehicle at a receiving place or a delivery place of the additionally distributed delivery order.
2. The system of claim 1, wherein the delivery order includes a plurality of delivery information, the delivery information including a consignor address, a consignee address, a type of goods, a weight of goods, a volume of goods, a temperature requirement for delivery, and a required delivery time.
3. The system of claim 2, wherein the classification module comprises a temperature classification module configured to classify delivery orders based on the temperature requirements of the delivery, obtaining a number of temperature classifications as order classifications.
4. The system of claim 3, wherein in each of said temperature classification scenarios, a delivery route is generated based on said consignee address and said arrival time, and a delivery mission is generated based on said delivery route and said delivery order.
5. The system of claim 4, wherein generating a delivery route based on the consignee address and the arrival time comprises:
obtaining a predicted delivery time based on the consignee address and the truck departure address, and taking the predicted delivery time as a first predicted delivery time if the predicted delivery time is within the range of the required delivery time;
generating a delivery route based on a number of the first estimated time of arrival and the consignee address.
6. The system of claim 2, wherein the loading modules include an origin loading module and an approach loading module;
the initial loading module comprises a first loading module and a second loading module;
the first loading module is used for sequencing the cargos based on the receiver address, and the farther the receiver address is, the closer the cargos are to the interior of the cargo box, so that a first loading sequence is obtained;
the second loading module is used for placing the goods in the container from bottom to top according to the weight and the volume of the goods based on the first loading sequence, and the weight of the goods is considered preferentially;
the approach loading module is used for loading the goods received on the way.
7. The system of claim 1, wherein the transportation monitoring module comprises: the cargo box monitoring module and the vehicle state monitoring module;
the container monitoring module is used for monitoring real-time environment parameter values in the container, and if the real-time environment parameter values exceed preset standard environment parameter values, alarming and reminding are carried out;
the container monitoring module is also used for monitoring the free volume in the container after each loading and unloading;
the vehicle monitoring module is used for monitoring vehicle information, and the vehicle information comprises a vehicle real-time position and a vehicle real-time speed.
8. The system of claim 2 or 7, wherein the en-route order-increasing module comprises a vehicle pick-up calculation module, a goods delivery prediction module, and an order-increasing module;
the vehicle receiving calculation module is used for obtaining the time when the vehicle is expected to arrive at the address of the cargo sender on the way based on the vehicle information;
the goods delivery prediction module is used for calculating the time of delivering the goods to the address of the goods receiver;
the order adding and dispatching module is used for adding and dispatching orders for the vehicle when the sum of the time of the vehicle receiving calculation module and the time of the goods reaching the predicted module is less than the required reaching time, and the volume of the goods to be added and dispatched is less than the free volume in the container.
9. The system of claim 2, wherein the cargo transceiver module comprises a receiving module and a transmitting module;
the receiving module is used for dispatching the goods receiving vehicle belonging to the area of the goods receiving address to receive goods when the vehicle reaches a high-speed port or a service area of the goods receiving address;
the sending module is used for sending the delivery vehicle belonging to the area where the delivery party address is located when the vehicle arrives at a high-speed port or a service area of the area where the delivery party address of the additionally-sent order is located on the way.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210362282.4A CN114648169A (en) | 2022-04-07 | 2022-04-07 | Cold chain delivery quality and storage management system based on big data |
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| CN202210362282.4A CN114648169A (en) | 2022-04-07 | 2022-04-07 | Cold chain delivery quality and storage management system based on big data |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117635008A (en) * | 2024-01-24 | 2024-03-01 | 誉农智汇(成都)农业科技发展集团有限公司 | Cold-chain logistics monitoring and management system and method based on Internet of things |
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- 2022-04-07 CN CN202210362282.4A patent/CN114648169A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117635008A (en) * | 2024-01-24 | 2024-03-01 | 誉农智汇(成都)农业科技发展集团有限公司 | Cold-chain logistics monitoring and management system and method based on Internet of things |
| CN117635008B (en) * | 2024-01-24 | 2024-04-05 | 誉农智汇(成都)农业科技发展集团有限公司 | Cold-chain logistics monitoring and management system and method based on Internet of things |
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