CN115719193A - Logistics vehicle scheduling planning system of Internet of things - Google Patents
Logistics vehicle scheduling planning system of Internet of things Download PDFInfo
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- CN115719193A CN115719193A CN202211547726.8A CN202211547726A CN115719193A CN 115719193 A CN115719193 A CN 115719193A CN 202211547726 A CN202211547726 A CN 202211547726A CN 115719193 A CN115719193 A CN 115719193A
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Abstract
The invention discloses a logistics vehicle dispatching planning system of an Internet of things, which belongs to the field of logistics vehicle dispatching planning and solves the problems that how to avoid uneven distribution of transportation tasks, the logistics vehicles arrive at a transportation starting point untimely, and a plurality of logistics vehicles are easy to conflict and deadlock in the transportation process; the information acquisition module acquires road information, real-time position information and running state information of the logistics vehicles; the map building module is used for building a logistics map based on the transportation site; the task allocation module is used for generating and allocating a transportation task; the route planning module is used for planning the transportation route of the logistics vehicle; the database is used for storing the acquired information; the background management module is used for monitoring and managing the operation of the information acquisition module, the map construction module, the task distribution module, the route planning module, the database and the logistics vehicles in real time.
Description
Technical Field
The invention belongs to the field of logistics vehicle scheduling planning, and particularly relates to a logistics vehicle scheduling planning system of the Internet of things.
Background
Along with the development of society and science and technology, the commodity circulation transportation is scale gradually, and the work efficiency of commodity circulation transportation can both be promoted to a certain extent to the commodity circulation vehicle about the commodity circulation transportation at present, have adopted artifical vehicle and unmanned vehicle based on AGV dolly. Especially, the AGV trolley can realize accurate logistics transportation according to the map set in the earlier stage and the sensing technology of the AGV trolley, and manual operation is not needed.
At present, for a small-area logistics transportation site, a small number of AGV trolleys are generally used, and logistics vehicles are relatively simple to dispatch; if a large area of logistics transportation field appears, more AGV trolleys are needed to be adopted, uneven distribution of transportation tasks can easily occur, the AGV trolleys cannot arrive at the transportation starting point timely, and the conditions of conflict and deadlock easily occur in the transportation process of a plurality of AGV trolleys, so that the logistics transportation progress is slow.
Therefore, the invention provides a logistics vehicle scheduling and planning system of the Internet of things.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides the logistics vehicle scheduling and planning system of the Internet of things, which solves the problems that the distribution of transportation tasks is not uniform, the logistics vehicles arrive at a transportation starting point untimely, and a plurality of logistics vehicles are easy to conflict and deadlock in the transportation process.
In order to achieve the above object, an embodiment according to a first aspect of the present invention provides a logistics vehicle scheduling planning system of an internet of things, including: the system comprises an information acquisition module, a map construction module, a task distribution module, a route planning module, a database and a background management module;
the information acquisition module is used for acquiring all road information of the same area in a logistics distribution scene and sending the road information to the map construction module; the information acquisition module is also used for acquiring distribution demand information, acquiring real-time position information and running state information of all current logistics vehicles and sending the real-time position information and the running state information to the task distribution module;
the map building module is used for building a logistics map based on transportation sites according to all the acquired road information in the logistics distribution scene, and sending the logistics map to a database for storage;
the task allocation module is used for generating and allocating a transportation task; generating a transportation task list with a time window according to the distribution demand information acquired in real time and the initiated time sequence; selecting a logistics vehicle which is idle, has the current electric quantity larger than a preset electric quantity threshold value, has the minimum cross transportation station with a transportation route of other transportation tasks, has the shortest route distance to an initial distribution station of the current transportation task and the shortest arrival time as the current transportation task through a genetic algorithm, and sending the current transportation task and the logistics vehicle number to a route planning module for processing and storing in a database;
the route planning module is used for planning a transportation route of the logistics vehicle; generating a transportation route which has the least intersection with all on-line transportation task routes before the starting time of the current time window and is within the planned delivery time by combining a logistics map of a database according to the acquired corresponding transportation tasks and the logistics vehicle numbers, and sending the transportation route to the logistics vehicle with the current number; sending the corresponding transportation route to a database to be packaged and stored with the corresponding transportation task and the logistics vehicle number; the logistics vehicle acquires the transportation route through the vehicle-mounted terminal, and the logistics vehicle sequentially passes through the transportation sites with corresponding numbers according to the site information in the transportation route; when the logistics vehicle needs to enter a next transportation station, sending inquiry information of whether the logistics vehicle is idle in advance, if the logistics vehicle is idle, entering the next transportation station, otherwise, waiting, meanwhile, calculating the actual waiting time through a route planning module, if the actual waiting time is less than the preset deadlock waiting time, continuing waiting, otherwise, entering a next planned route for driving;
the database is used for storing the acquired information;
the background management module is used for monitoring and managing the operation of the information acquisition module, the map construction module, the task distribution module, the route planning module, the database and the logistics vehicles in real time.
Further, the logistics vehicle adopts an AGV to automatically guide the transport vehicle.
Furthermore, the map building module divides each road into a plurality of sections according to unit distance, and performs rasterization to form a reticular logistics map, wherein each node in the reticular map is a transportation station; the map building module also numbers all transportation sites in the logistics map.
Further, the distribution demand information includes distribution demand initiation time, initial distribution station position information, target distribution station position information, distribution plan deadline, and total amount of distributed items.
Further, the task allocation module sequentially processes according to the sequence of the initiation time of the distribution demand information, and calculates and obtains the same distribution demand information according to the specific distribution demand information, wherein the same distribution demand information needs several logistics vehicles for transportation and distribution; through calculation, if the current distribution demand information only needs one logistics vehicle for distribution and transportation, only one transportation task is needed for the current distribution demand information, and if the current distribution demand information needs a plurality of logistics vehicles for distribution and transportation, the current distribution demand information includes a plurality of corresponding transportation tasks.
Further, when the logistics vehicles with the number m enter a waiting state, the route planning module acquires all transportation tasks with time windows passing through the transportation stations with the number n from the database; wherein m represents the number of a logistics vehicle, m =1,2 \8230; n represents the transportation site number in the logistics map, n =1,2 \8230; \8230n;
screening transportation tasks needing to enter the transportation sites numbered n at the current time point, and sequencing the priorities of the logistics vehicles needing to enter the transportation sites numbered n at the current time point according to the sequence of the initial transportation time of the time window; calculating the actual waiting time for other logistics vehicles in front of the logistics vehicle with the number m to pass through the transportation station with the number n and wait to enter the transportation station with the number n, and presetting deadlock waiting time;
if the calculated actual waiting time is less than the deadlock waiting time, the route planning module sends feedback information of continuing waiting to the logistics vehicle with the number m;
if the calculated actual waiting time is more than or equal to the deadlock waiting time, the route planning module plans another transportation route which has the least intersection with other transportation task routes and is close to the other transportation task routes on the basis of the current station according to the transportation task corresponding to the logistics vehicle with the number of m, and sends the transportation route to the logistics vehicle with the number of m and the database.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, road information under a logistics distribution scene is collected through an information collection module and is sent to a map construction module for construction of a logistics map; the information acquisition module is used for acquiring distribution demand information, real-time position information and running state information of all current logistics vehicles and sending the information to the task distribution module to generate and distribute transportation tasks; the task allocation module sequentially processes according to the sequence of the initiation time of the distribution demand information, selects a logistics vehicle which is idle, has the current electric quantity larger than a preset electric quantity threshold value, has the minimum crossing transportation sites with the transportation routes of other transportation tasks, has the shortest route distance to the initial distribution site of the current transportation task and the shortest arrival time as the current transportation task through a genetic algorithm, and sends the current transportation task and the number of the logistics vehicle to the route planning module for processing and storing in a database; therefore, all the transportation task lists can be generated in a self-adaptive mode in the shortest time, and the corresponding transportation tasks are distributed to the corresponding logistics vehicles, so that the corresponding logistics vehicles can go to the initial distribution place in time.
2. The route planning module is used for numbering the acquired corresponding transportation tasks and logistics vehicles, generating a transportation route which has the least intersection with all online transportation task routes before the starting time of the current time window and is within the planned delivery time by combining a logistics map of a database, and sending the transportation route to the logistics vehicle with the current number; sending the corresponding transportation route to a database, and packaging and storing the transportation route, the corresponding transportation task and the logistics vehicle number; the logistics vehicle acquires the transportation route through the vehicle-mounted terminal, and the logistics vehicle sequentially passes through the transportation sites with corresponding numbers according to the site information in the transportation route; when the logistics vehicle needs to enter a next transportation station, inquiring information about whether the logistics vehicle is idle needs to be sent to the corresponding transportation station in advance, if the logistics vehicle is idle, the logistics vehicle enters the next transportation station, otherwise, the logistics vehicle waits, meanwhile, the route planning module calculates the actual waiting time, if the actual waiting time is less than the preset deadlock waiting time, the logistics vehicle continues to wait, and if the actual waiting time is not less than the preset deadlock waiting time, the logistics vehicle enters a next planned route to run; therefore, the waiting time of the logistics vehicles can be reduced, and the situations of conflict and deadlock of the logistics vehicles in the transportation process are avoided, so that the logistics vehicles can operate according to the corresponding time windows.
3. The background management module carries out real-time monitoring management on the operation of the information acquisition module, the map construction module, the task distribution module, the route planning module, the database and the logistics vehicle, and if the operation is abnormal, the corresponding staff can timely handle the operation, so that the problems that the logistics vehicle is in system breakdown and fails to be timely found in the transportation process are solved.
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FIG. 1 is a schematic diagram of the system of the present invention.
Detailed Description
The technical solutions of the present invention will be described below clearly and completely in conjunction with the embodiments, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a logistics vehicle scheduling planning system of internet of things includes: the system comprises an information acquisition module, a map construction module, a task distribution module, a route planning module, a database and a background management module;
in the application, the information acquisition module is used for acquiring all road information of the same area in a logistics distribution scene and sending the road information to the map construction module;
the information acquisition module is also used for acquiring distribution demand information, acquiring real-time position information and running state information of all current logistics vehicles and sending the real-time position information and the running state information to the task distribution module;
in the embodiment of the invention, the logistics vehicle can adopt an AGV (automatic guided vehicle) which is mature in the prior art, namely an automatic guided vehicle; the AGV dolly has unmanned automatic guide function, can move under the scenes such as the part transportation of warehouse logistics transportation, workshop product processing, has reduced artifical transport, has improved conveying efficiency.
In the application, the map construction module is used for constructing a logistics map based on transportation sites according to all the acquired road information in the logistics distribution scene;
specifically, the map building module divides each road into a plurality of sections according to unit distance, and performs rasterization to form a mesh-shaped logistics map, wherein each node in the mesh-shaped map is a transportation station;
the map building module is also used for numbering all transportation sites in the logistics map;
and the map building module sends the successfully built logistics map to a database for storage.
In the application, the task allocation module is used for analyzing and processing the acquired distribution demand information, the real-time position information and the running state information of the logistics vehicles, generating a transportation task list with a time window and allocating the transportation task list to the corresponding logistics vehicles;
specifically, the task allocation module processes the acquired information as follows:
step A1: generating a transportation task list with a time window according to the distribution demand information acquired in real time and the initiated time sequence;
in the embodiment of the invention, the distribution demand information comprises distribution demand initiation time, initial distribution station position information, target distribution station position information, distribution plan deadline, total distribution article amount and the like;
the task allocation module sequentially processes according to the sequence of the initiation time of the distribution demand information, and calculates and obtains the same distribution demand information according to the specific distribution demand information, wherein the same distribution demand information needs several logistics vehicles for transportation and distribution; after calculation, if the current distribution demand information only needs one logistics vehicle for distribution and transportation, only one transportation task is needed for the current distribution demand information, and if the current distribution demand information needs a plurality of logistics vehicles for distribution and transportation, the current distribution demand information comprises a plurality of corresponding transportation tasks;
when the total quantity of the delivered goods of the delivery demand information is far larger than the carrying capacity of a single logistics vehicle and the delivery plan deadline is short, a plurality of transportation tasks can be distributed to the delivery demand information;
the task allocation module allocates time windows to all the transportation tasks obtained through calculation according to the time sequence initiated by the distribution demand information, so that the corresponding transportation tasks run according to the corresponding time windows;
step A2: selecting a proper logistics vehicle to go to an initial distribution site of the current transportation task for transportation and distribution through a genetic algorithm according to the generated transportation task list and the acquired real-time position information and running state information of all the logistics vehicles;
in the embodiment of the invention, the task allocation module judges whether all the logistics vehicles at the current time point are idle or not and whether the electric quantity is greater than a preset electric quantity threshold value or not, and screens out the logistics vehicles which are idle and have the current electric quantity greater than the preset electric quantity threshold value;
acquiring real-time position information of the screened logistics vehicles, and predicting and calculating all feasible routes of each screened logistics vehicle reaching an initial delivery station of the current transportation task and the running time of the corresponding route in real time according to a logistics map;
selecting a logistics vehicle which has the least cross transportation stations with the transportation routes of other transportation tasks, the shortest route distance to the initial distribution station of the current transportation task and the shortest arrival time through an elite reservation mechanism, and sending the current transportation task and the logistics vehicle number to a route planning module for processing and storing in a database;
accordingly, the other transportation task information distribution method is the same.
In the application, the route planning module is used for planning the transportation routes of all logistics vehicles, so that the corresponding logistics vehicles can reach corresponding target stations based on corresponding time windows;
specifically, the route planning module plans the transportation route of the logistics vehicle as follows:
step B1: the route planning module analyzes and calculates the acquired transportation tasks and the logistics vehicle serial numbers, generates a transportation route which has the least intersection with all on-line transportation task routes before the starting time of the current time window and is within the planned delivery time according to a logistics map in a database, and sends the transportation route to the logistics vehicle with the current serial number; sending the corresponding transportation route to a database, and packaging and storing the transportation route, the corresponding transportation task and the logistics vehicle number;
the transportation routes sequentially sort the serial numbers of the passing transportation stations according to the sequence;
and step B2: the logistics vehicle acquires the transportation route through the vehicle-mounted terminal, and the logistics vehicle sequentially passes through the transportation sites with corresponding numbers according to the site information in the transportation route;
step B21: when the logistics vehicle with the number m is ready to arrive at the transportation station with the number n, judging whether the logistics vehicle with the number m is idle in the transportation station with the number n when the logistics vehicle with the number m is at the last transportation station of the transportation route, namely sending inquiry information about whether the logistics vehicle with the number m is idle to the transportation station with the number n; wherein m represents the number of a logistics vehicle, m =1,2 \8230; n represents the transportation site number in the logistics map, n =1,2 \8230; \8230n;
if the information fed back by the transport station numbered n is idle, the logistics vehicle numbered m enters the transport station numbered n;
if the information fed back by the transportation station with the number n is not idle, the logistics vehicle with the number m enters a waiting state;
step B22: after the logistics vehicle with the number m enters a waiting state, the information of the transportation station blockage with the number m and the number n is sent to a route planning module;
step B23: the route planning module analyzes the acquired information of the transportation station blockage with the number m and the number n of the logistics vehicles; specifically, the route planning module acquires all transportation tasks with time windows passing through the transportation station numbered n from the database;
screening transportation tasks needing to enter the transportation sites numbered n at the current time point, and sequencing the priorities of the logistics vehicles needing to enter the transportation sites numbered n at the current time point according to the sequence of the initial transportation time of the time window; calculating the actual waiting time for other logistics vehicles in front of the logistics vehicle with the number m to pass through the transportation station with the number n and wait to enter the transportation station with the number n, and presetting deadlock waiting time;
if the calculated actual waiting time is less than the deadlock waiting time, the route planning module sends feedback information for continuing waiting to the logistics vehicle with the number of m;
if the calculated actual waiting time is larger than or equal to the deadlock waiting time, the route planning module plans another transportation route which has the least intersection with other transportation task routes and is closer to the other transportation task routes on the basis of the current station according to the transportation task corresponding to the logistics vehicle with the number of m, and sends the transportation route to the logistics vehicle with the number of m and the database.
In the application, the background management module is used for monitoring and managing the operation of the information acquisition module, the map construction module, the task distribution module, the route planning module, the database and the logistics vehicles in real time;
when any one of the two is in fault, sound and light alarm is carried out through the background management module and timely processed by corresponding staff.
The working principle of the invention is as follows: in the invention, road information under a logistics distribution scene is collected through an information collection module and is sent to a map construction module for construction of a logistics map; the information acquisition module is used for acquiring distribution demand information and real-time position information and running state information of all current logistics vehicles and sending the information to the task distribution module for generating and distributing transportation tasks; the task allocation module sequentially processes according to the sequence of the initiation time of the distribution demand information, selects idle logistics vehicles, the current electric quantity of which is greater than a preset electric quantity threshold value, the number of the logistics vehicles which have the minimum crossing transportation sites with the transportation routes of other transportation tasks, the shortest route distance to the initial distribution site of the current transportation task and the shortest arrival time as the current transportation tasks through a genetic algorithm, and sends the current transportation tasks and the logistics vehicle numbers to the route planning module for processing and the database for storage; the route planning module is used for numbering the acquired corresponding transportation tasks and logistics vehicles, generating a transportation route which has the least intersection with all online transportation task routes before the starting time of the current time window and is within the planned delivery time by combining a logistics map of a database, and sending the transportation route to the logistics vehicle with the current number; sending the corresponding transportation route to a database, and packaging and storing the transportation route, the corresponding transportation task and the logistics vehicle number; the logistics vehicle acquires the transportation route through the vehicle-mounted terminal, and the logistics vehicle sequentially passes through the transportation sites with corresponding numbers according to the site information in the transportation route; when the logistics vehicle needs to enter a next transportation station, inquiring information about whether the logistics vehicle is idle needs to be sent to the corresponding transportation station in advance, if the logistics vehicle is idle, the logistics vehicle enters the next transportation station, otherwise, the logistics vehicle waits, meanwhile, the route planning module calculates the actual waiting time, if the actual waiting time is less than the preset deadlock waiting time, the logistics vehicle continues to wait, and if the actual waiting time is not less than the preset deadlock waiting time, the logistics vehicle enters a next planned route to run; the background management module carries out real-time monitoring management on the operation of the information acquisition module, the map construction module, the task distribution module, the route planning module, the database and the logistics vehicle, and if the operation is abnormal, the operation is timely processed by corresponding staff.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and there may be other divisions when the actual implementation is performed; the modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of the embodiment.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (6)
1. The logistics vehicle scheduling planning system of the Internet of things is characterized by comprising: the system comprises an information acquisition module, a map construction module, a task distribution module, a route planning module, a database and a background management module;
the information acquisition module is used for acquiring all road information of the same area in a logistics distribution scene and sending the road information to the map construction module; the information acquisition module is also used for acquiring distribution demand information, acquiring real-time position information and running state information of all current logistics vehicles and sending the real-time position information and the running state information to the task distribution module;
the map construction module is used for constructing a logistics map based on transportation sites according to all the road information in the acquired logistics distribution scene, and sending the logistics map to the database for storage;
the task allocation module is used for generating and allocating a transportation task; generating a transportation task list with a time window according to the distribution demand information acquired in real time and the initiated time sequence; selecting a logistics vehicle which is idle, has the current electric quantity larger than a preset electric quantity threshold value, has the minimum crossing transportation sites with transportation routes of other transportation tasks, has the shortest route distance to an initial distribution site of the current transportation task and the shortest arrival time as the current transportation task, and sending the current transportation task and the logistics vehicle number to a route planning module for processing and a database for storing through a genetic algorithm;
the route planning module is used for planning a transportation route of the logistics vehicle; generating a transportation route which has the least intersection with all on-line transportation task routes before the starting time of the current time window and is within the planned delivery time by combining a logistics map of a database according to the acquired corresponding transportation tasks and the logistics vehicle numbers, and sending the transportation route to the logistics vehicle with the current number; sending the corresponding transportation route to a database, and packaging and storing the transportation route, the corresponding transportation task and the logistics vehicle number; the logistics vehicle acquires a transportation route through the vehicle-mounted terminal, and the logistics vehicle sequentially passes through transportation stations with corresponding numbers according to station information in the transportation route; when the logistics vehicle needs to enter the next transportation station, sending inquiry information about whether the logistics vehicle is idle or not in advance, if the logistics vehicle is idle, entering the next transportation station, and if the logistics vehicle is not idle, waiting, and meanwhile, calculating actual waiting time through a route planning module, if the actual waiting time is less than preset deadlock waiting time, continuing waiting, and if the actual waiting time is not less than preset deadlock waiting time, entering the next planned route for running;
the database is used for storing the acquired information;
the background management module is used for monitoring and managing the operation of the information acquisition module, the map construction module, the task distribution module, the route planning module, the database and the logistics vehicles in real time.
2. The logistics vehicle dispatching planning system of the internet of things of claim 1, wherein the logistics vehicle adopts an AGV automatic guided vehicle.
3. The logistics vehicle scheduling planning system of the internet of things according to claim 1, wherein the map construction module divides each road into a plurality of sections according to unit distance, and forms a mesh logistics map by rasterization, wherein each node in the mesh map is a transportation station; the map building module also numbers all transportation sites in the logistics map.
4. The logistics vehicle scheduling planning system of the internet of things as claimed in claim 1, wherein the delivery demand information comprises delivery demand initiation time, initial delivery station position information, target delivery station position information, delivery plan deadline time, and total amount of delivered items.
5. The logistics vehicle scheduling planning system of the internet of things according to claim 1, wherein the task allocation module sequentially processes according to the sequence of the initiation time of the delivery demand information, and calculates and obtains the same delivery demand information according to specific delivery demand information, and several logistics vehicles are required for transportation and delivery; through calculation, if the current distribution demand information only needs one logistics vehicle for distribution and transportation, only one transportation task is needed for the current distribution demand information, and if the current distribution demand information needs a plurality of logistics vehicles for distribution and transportation, the current distribution demand information includes a plurality of corresponding transportation tasks.
6. The logistics vehicle scheduling planning system of the internet of things as claimed in claim 1, wherein when the logistics vehicle with the number m enters a waiting state, the route planning module obtains all transportation tasks with time windows passing through the transportation station with the number n from the database; wherein m represents the number of a logistics vehicle, m =1,2 \8230; n represents the transportation site number in the logistics map, n =1,2 \8230; \8230n;
screening the transportation tasks of the transportation sites with the number n required to enter at the current time point, and sequencing the priority of the logistics vehicles of the transportation sites with the number n required to enter at the current time point according to the sequence of the initial transportation time of the time window; calculating the actual waiting time for other logistics vehicles in front of the logistics vehicle with the number m to pass through the transportation station with the number n and wait to enter the transportation station with the number n, and presetting deadlock waiting time;
if the calculated actual waiting time is less than the deadlock waiting time, the route planning module sends feedback information of continuing waiting to the logistics vehicle with the number m;
if the calculated actual waiting time is more than or equal to the deadlock waiting time, the route planning module plans another transportation route which has the least intersection with other transportation task routes and is close to the other transportation task routes on the basis of the current station according to the transportation task corresponding to the logistics vehicle with the number of m, and sends the transportation route to the logistics vehicle with the number of m and the database.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116579699A (en) * | 2023-07-14 | 2023-08-11 | 天津鸿飞达科技有限公司 | Wisdom logistics distribution system based on car goods are in coordination |
| CN117010581A (en) * | 2023-09-12 | 2023-11-07 | 山东未来网络研究院(紫金山实验室工业互联网创新应用基地) | Logistics path planning method and system based on industrial Internet identification analysis |
| CN117151576A (en) * | 2023-10-30 | 2023-12-01 | 青岛宇方机器人工业股份有限公司 | Logistics vehicle dispatching management system and method |
| CN117635000A (en) * | 2023-11-22 | 2024-03-01 | 中建材智能自动化研究院有限公司 | LMS production logistics scheduling method based on industrial Internet |
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- 2022-12-05 CN CN202211547726.8A patent/CN115719193A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116579699A (en) * | 2023-07-14 | 2023-08-11 | 天津鸿飞达科技有限公司 | Wisdom logistics distribution system based on car goods are in coordination |
| CN116579699B (en) * | 2023-07-14 | 2023-09-19 | 天津鸿飞达科技有限公司 | Wisdom logistics distribution system based on car goods are in coordination |
| CN117010581A (en) * | 2023-09-12 | 2023-11-07 | 山东未来网络研究院(紫金山实验室工业互联网创新应用基地) | Logistics path planning method and system based on industrial Internet identification analysis |
| CN117010581B (en) * | 2023-09-12 | 2024-02-09 | 山东未来网络研究院(紫金山实验室工业互联网创新应用基地) | Logistics path planning method and system based on industrial Internet identification analysis |
| CN117151576A (en) * | 2023-10-30 | 2023-12-01 | 青岛宇方机器人工业股份有限公司 | Logistics vehicle dispatching management system and method |
| CN117151576B (en) * | 2023-10-30 | 2024-01-09 | 青岛宇方机器人工业股份有限公司 | Logistics vehicle dispatching management system and method |
| CN117635000A (en) * | 2023-11-22 | 2024-03-01 | 中建材智能自动化研究院有限公司 | LMS production logistics scheduling method based on industrial Internet |
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