CN112686439B - Intelligent automatic container terminal energy-saving comprehensive scheduling method - Google Patents
Intelligent automatic container terminal energy-saving comprehensive scheduling method Download PDFInfo
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Abstract
The invention provides an intelligent energy-saving comprehensive scheduling method for an automatic container terminal, which comprises the following steps: the method comprises the following steps of planning ship unloading operation, planning ship loading operation, planning a path at optimal time, constructing a scheduling model, analyzing a scheduling central point, simulating a transport vehicle and actually applying; the invention arranges the sequence of several ship unloading tasks in advance in the ship unloading operation, sends the sequence of the future ship unloading command to a shore bridge driver, sends the ship loading command to be completed in the future to an idle trailer in advance in the ship loading operation, distributes the ship loading sequence, and the field bridge driver distributes the trailer of the ship loading command in a self-operated way, and the shore bridge served by the next operation of one trailer is uncertain, so that the loading and unloading have sequence and randomness.
Description
Technical Field
The invention relates to the technical field of wharf dispatching, in particular to an intelligent energy-saving comprehensive dispatching method for an automatic container wharf.
Background
The development of port and wharf faces complicated and changeable environment, port resource scheduling is used as a core of port enterprise production, and is a very important link for wharf operation organization and arrangement process, in the operation process of loading and unloading scheduling, the scheduling of trailers is more important, and the operation of a loading and unloading ship is the main business of each container wharf and is also a direct reflection link for reflecting the operation capacity of the wharf. Along with the improvement of global economic situation, the container terminal not only meets the opportunity, but also meets various challenges, wherein if the operation efficiency of the terminal is improved to a certain extent under the existing hardware equipment, the container terminal becomes an issue to be solved by each large container terminal;
at present, during the operation process of loading and unloading a ship at a wharf, a trailer is fixedly bound with a shore bridge for operation, and the loading and unloading operation at the wharf is triggered and executed by the shore bridge, because the port operation has the characteristics of various operation types, crossed operation routes, wide operation range, large operation amount and the like, the traditional trailer scheduling mode has the problems of overlong trailer waiting time, overlong equipment operation waiting time, unbalanced site operation busy degree, trailer congestion points in a site, excessive empty-load running of the trailer and the like, so that the energy consumption is large, in the process of scheduling and transporting, the restriction on the transporting capacity mainly refers to the path from a resource point to a transfer station, and the problem of urgently solving the prior art is to reasonably plan the path.
Disclosure of Invention
The invention provides an intelligent energy-saving comprehensive scheduling method for an automatic container terminal, which is characterized in that the estimated operation duration is obtained by utilizing the estimated operation completion time point and the estimated operation start time point through the sequence and randomness in the loading and unloading process based on multiple loading and unloading operations, so that the optimal time planning path of each trailer is selected, the operation time is saved, the operation efficiency is improved, the energy is saved, meanwhile, the resource central point is determined, the shortest path from each resource point to each transfer station is determined, the transportation time is saved, and the transportation efficiency is optimized.
In order to realize the purpose of the invention, the invention is realized by the following technical scheme: an intelligent energy-saving comprehensive scheduling method for an automatic container terminal comprises the following steps:
the method comprises the following steps: ship unloading operation planning
The container is transported from the ship to the yard, at first, the system records the number of containers, the system judges the workload according to the number of containers on the same day, decides how many trailers are on duty, and marks the trailers on duty into the system, the shore bridge operator carries out the unloading operation, arranges the sequence of a plurality of subsequent unloading tasks in advance, and inputs the sequence into the system, the unloading sequence is planned according to the trailers on duty in the system, and is combined into an instruction to be sent to the shore bridge operator, the shore bridge operator arranges the shore bridge driver to complete the operation of the current instruction according to the instruction sent by the system, and simultaneously sends the sequence of the future unloading instruction to other shore bridge drivers;
step two: shipment planning
When a shore bridge entry worker carries out the shipping operation, a shipping instruction needing to be completed in the future is sent to the system in advance, the system distributes a shipping sequence to idle trailers, a field bridge driver receives the shipping instruction and distributes the shipping instruction to the trailers by self according to the sequence of the trailers under the field bridge, and in the process, the field bridge served by the next operation of one trailer is uncertain, and the system gives the position of the next operation;
step three: optimal time planning path
In the process of loading and unloading the ship, the completion instruction time point of the trailer is evaluated, namely the estimated time required by the trailer for transporting the container is completed, after the trailer completes the operation, the system allocates the starting position of the next instruction to the trailer, if the trailer completes the operation, the starting position is at a certain position of another site, for unloading the ship, the starting position is at a certain position of the site, and the estimated time required by the trailer to reach the operation starting position becomes the estimated operation starting time point;
step four: building a scheduling model
After a container is loaded and unloaded, a trailer transports the container to a plurality of resource points, the container is distributed to a transport vehicle through the resource points to be dispatched to a transfer station outside a wharf, global space-time data of wharf remote sensing images collected by satellites and aviation technologies are obtained by using a GPS common frequency point means, the global space-time data comprise a plurality of resource points in the wharf, the collected data are input to the cloud end of the Internet of things, the data are analyzed, classified, deduplicated, encrypted and stored, then a coordinate three-dimensional model corresponding to wharf roads, the resource points and the transfer station is constructed, and finally the overall model is cut to construct a complete three-dimensional GIS dispatching macro model;
step five: analyzing a dispatch center point
In a three-dimensional GIS scheduling macroscopic model, firstly analyzing the number of resource points in a wharf, then analyzing the number of paths from each resource point to each transfer station, then calculating the linear distance evaluation time of each resource point to each transfer station in a set region, sequencing all the resource points according to the length of the linear distance evaluation time of each transfer station, obtaining the resource point which has the widest radiation range and the least time consumption for a plurality of transfer stations in the set region, and setting the resource point as a scheduling central point to serve as the point with the largest resource bearing capacity;
step six: simulated transport vehicle
Simulating a transport vehicle in a three-dimensional GIS (geographic information System) scheduling macro model, setting the transportation speed of the transport vehicle, transporting the transport vehicle to a scheduling path for goods transportation to obtain the time used for simulation, further determining a scheduling central point, and simultaneously determining the shortest path from each resource point to each transfer station and a secondary short path, wherein the secondary short path is used as an alternative scheme;
step seven: practical application
And performing practical application according to the shortest path in the step six, recording the time consumption situation from each resource point to each transfer station in practice, verifying the practical feasibility of the main scheme, and replacing the shortest path and the secondary short path according to the path congestion situation to obtain the optimal scheme.
The further improvement lies in that: in the second step, the system gives the position of the next operation, which is specifically represented as follows: if it is ship unloading, the system gives the position of the destination shore bridge, and if it is ship loading, the system gives the position of ship loading bridge.
The further improvement is that: in the third step, the "predicted job completion time point" includes the trailer idle time interval.
The further improvement lies in that: and in the third step, the route is planned in the optimal time, and the principle that under the condition that the trailer is sufficient, the sum of all the time is minimum when no equipment is distributed, the shore bridge with the longest waiting time is distributed preferentially and after distribution is ensured.
The further improvement is that: in the fourth step, the specific process of constructing the coordinate three-dimensional model is as follows: the method comprises the steps of restoring a three-dimensional image of acquired data, stretching the model three-dimensionally through 3Dmax software, constructing a wharf dispatching path model, outputting a corresponding GIS space model, vectorizing parameter information of the GIS space model through ArcMAP software, loading each vectorized path layer into the wharf dispatching path model, visualizing the data in a 3D mode, and enhancing a display effect through symbolization.
The further improvement lies in that: and in the fourth step, the overall model is cut, so that the internal elements are individualized.
The further improvement lies in that: and in the sixth step, a plurality of simulated transport vehicles are set to be of the same type, and the transport speed of the simulated transport vehicles is set to accord with the highest speed per hour of the road.
The invention has the beneficial effects that: in the ship unloading operation, the sequence of a plurality of ship unloading tasks is arranged in advance, a shore bridge driver is arranged to complete the current operation, the sequence of a future ship unloading command is sent to other shore bridge drivers, in the ship loading operation, a ship loading command needing to be completed in the future is sent to an idle trailer in advance, the sequence of the ship loading is distributed to the field bridge driver, the field bridge driver automatically distributes trailers of the ship loading command according to the sequence of the trailers under the field bridge, the whole process is realized, the shore bridge served by the next operation of one trailer is uncertain, the system gives the position of the next operation, so that the loading and unloading are sequential and random, in multiple loading and unloading operations, the estimated operation duration is obtained by utilizing the estimated operation completion time point and the estimated operation starting time point, the optimal time planning path of each trailer is selected, the operation time is saved, the operation efficiency is improved, the energy is saved, meanwhile, in the process of dispatching and transportation, a GIS three-dimensional dispatching macroscopic model is established, the dispatching paths of a resource transfer station and a transfer station are simulated by the model, the shortest path of the resource is used as the most resource, the transfer amount of the resources is simulated, the shortest path of the transportation station is simulated, and the shortest path of each transport station is optimized, and the transport efficiency is saved.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
In order to further understand the present invention, the following detailed description will be made with reference to the following examples, which are only used for explaining the present invention and are not to be construed as limiting the scope of the present invention.
As shown in fig. 1, the embodiment provides an intelligent energy-saving comprehensive scheduling method for an automated container terminal, which includes the following steps:
the method comprises the following steps: ship unloading operation planning
The container is transported to the yard from the shipping, at first, the system records the container quantity, the system judges the workload according to the container quantity of the present day, determine how many trailers are on duty, and mark these trailers on duty into the system, the shore bridge entry worker unloads the ship, arrange the order of several ship unloading tasks in advance, and input the order into the system, the trailer on duty plans the ship unloading order in the system, and combine into the order to send to the shore bridge entry worker, the shore bridge entry worker arranges the shore bridge driver to finish the operation of the present order according to the order that the system sends, send the order of the ship unloading order of the future to other shore bridge drivers at the same time;
step two: shipment planning
When a shore bridge entry worker carries out the shipping operation, a shipping instruction needing to be finished in the future is sent to the system in advance, the system allocates a shipping sequence to idle trailers, a field bridge driver receives the shipping instruction and automatically allocates the shipping instruction to the trailers according to the sequence of the trailers under the field bridge, in the process, the field bridge served by the next operation of one trailer is uncertain, the system gives the position of the next operation, if the ship is unloaded, the system gives the position of a target shore bridge, and if the ship is shipped, the system gives the position of the shipping field bridge;
step three: optimal time planning path
In the process of loading and unloading the ship, the completion instruction time point of the trailer is evaluated, namely the predicted time required for completing the task of transporting the container by the trailer, after the trailer finishes the operation, the system allocates the starting position of the next instruction to the trailer, if the trailer is in the loading operation, the starting position is at a certain position of a field, for the unloading operation, the starting position is at a certain position of another field, and the predicted time required for the trailer to reach the operation starting position becomes the 'predicted operation starting time point', when the trailer allocation is carried out each time, a shore bridge and a field bridge of the operation are set as equipment, the 'predicted operation completion time point' between each trailer participating in the calculation and each equipment participating in the calculation is calculated, the 'predicted operation completion time point' contains the idle time interval of the trailer, a predicted operation ship time table is formed, the predicted operation ship time table is comprehensively judged, the 'predicted operation completion time point' = 'is predicted operation time, the optimal time path of each trailer is selected through the' predicted operation 'time point', and the optimal time path is selected, and the following principle that the optimal time distribution of the trailer is not guaranteed under the condition that all the equipment is allocated preferentially;
step four: building a scheduling model
After loading and unloading the container, a trailer transports the container to a plurality of resource points, the container is distributed to a transport vehicle through the resource points to be dispatched to a transfer station outside a wharf, global space-time data of wharf remote sensing images collected by a satellite and an aviation technology are obtained by utilizing a GPS common frequency point means, the global space-time data comprise a plurality of resource points in the wharf, the collected data are input to the cloud of the Internet of things, the data are analyzed, classified, deduplicated, encrypted and stored, a three-dimensional image is restored, the model is stretched and three-dimensionally through 3Dmax software, a wharf dispatching path model is constructed, a corresponding GIS space model is output, parameter information of the GIS space model is vectorized through ArcMAP software, each vectorized path layer is loaded into the wharf dispatching path model, the data are visualized in a 3D mode, the visualization effect is enhanced through symbolization, a coordinate three-dimensional model corresponding to a wharf road, the resource points and the transfer station is obtained, and finally the overall model is cut, so that the elements inside are unified, and a complete three-dimensional dispatching macroscopic model is constructed;
step five: analyzing a scheduling center point
In a three-dimensional GIS scheduling macroscopic model, firstly analyzing the number of resource points in a wharf, then analyzing the number of paths from each resource point to each transfer station, then calculating the linear distance evaluation time of each resource point to each transfer station in a set region, sequencing all the resource points according to the length of the linear distance evaluation time of each transfer station, obtaining the resource point which has the widest radiation range and the least time consumption for a plurality of transfer stations in the set region, and setting the resource point as a scheduling central point to serve as the point with the largest resource bearing capacity;
step six: simulated transport vehicle
Simulating transport vehicles in a three-dimensional GIS (geographic information System) scheduling macro model, setting a plurality of simulated transport vehicles to be of the same type, setting the transport speed of the simulated transport vehicles to accord with the highest speed per hour of a road, using the transport vehicles in a scheduling path for transporting goods, obtaining the time used for simulation, further determining a scheduling central point, and simultaneously determining the shortest path and the second shortest path from each resource point to each transfer station, wherein the second shortest path is used as an alternative scheme;
step seven: practical application
And practical application is carried out according to the shortest path in the step six, the time consumption situation of each resource point to each transfer station in practice is recorded, the practical feasibility of the main scheme is verified, the shortest path and the secondary short path are replaced according to the path congestion situation, and the optimal scheme is obtained.
The intelligent energy-saving comprehensive dispatching method for the automatic container terminal arranges the sequence of a plurality of ship unloading tasks in advance in the ship unloading operation, arranges a land bridge driver to complete the current operation, and sends the sequence of the future ship unloading instructions to other land bridge drivers, in the ship loading operation, sends the ship loading instructions to be completed in the future to idle trailers in advance, and distributes the ship loading sequence, and the land bridge driver automatically distributes the trailers of the ship loading instructions according to the sequence of the trailers under the land bridge first, the whole process is realized, the land bridge served by the next operation of one trailer is uncertain, and the system gives the position of the next operation, so that the loading and unloading are sequential and random.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. An intelligent energy-saving comprehensive dispatching method for an automatic container terminal is characterized by comprising the following steps:
the method comprises the following steps: ship unloading operation planning
The container is transported from the ship to the yard, at first, the system records the number of containers, the system judges the workload according to the number of containers on the same day, decides how many trailers are on duty, and marks the trailers on duty into the system, the shore bridge operator carries out the unloading operation, arranges the sequence of a plurality of subsequent unloading tasks in advance, and inputs the sequence into the system, the unloading sequence is planned according to the trailers on duty in the system, and is combined into an instruction to be sent to the shore bridge operator, the shore bridge operator arranges the shore bridge driver to complete the operation of the current instruction according to the instruction sent by the system, and simultaneously sends the sequence of the future unloading instruction to other shore bridge drivers;
step two: shipment planning
When a shore bridge entry worker carries out the shipping operation, a shipping instruction needing to be completed in the future is sent to the system in advance, the system allocates a shipping sequence to idle trailers, a field bridge driver receives the shipping instruction and allocates the shipping instruction to the trailers by self according to the sequence of the trailers arriving at the field bridge, and in the process, the field bridge served by the next operation of one trailer is uncertain, and the system gives the position of the next operation;
step three: optimal time planning path
In the process of loading and unloading the ship, the completion instruction time point of the trailer is evaluated, namely the estimated time required by the trailer for transporting the container is completed, after the trailer completes the operation, the system allocates the starting position of the next instruction to the trailer, if the trailer completes the operation, the starting position is at a certain position of a field, for unloading the ship, the starting position is at a certain position of another field, and the estimated time required by the trailer to reach the operation starting position becomes the estimated operation starting time point, when the trailer is allocated each time, a shore bridge and a field bridge of the operation are set as equipment, the estimated operation completion time point between each trailer participating in the calculation and each equipment participating in the calculation is calculated, and an estimated operation completion ship time table is formed, the estimated operation completion time table is comprehensively judged, the estimated operation completion time point- "the estimated operation starting time point" = "the estimated operation duration", and the optimal time planning path of each trailer is selected through the "estimated operation duration";
step four: building a scheduling model
After a container is loaded and unloaded, a trailer transports the container to a plurality of resource points, the container is distributed to a transport vehicle through the resource points to be dispatched to a transfer station outside a wharf, global space-time data of wharf remote sensing images collected by a satellite and an aviation technology are obtained by using a GPS common frequency point means, the global space-time data comprise a plurality of resource points in the wharf, the collected data are input to the cloud of the Internet of things, the data are analyzed, classified, deduplicated, encrypted and stored, then a coordinate three-dimensional model corresponding to wharf roads, the resource points and the transfer station is constructed, and finally the overall model is cut to construct a complete three-dimensional GIS dispatching macroscopic model;
step five: analyzing a scheduling center point
In a three-dimensional GIS scheduling macroscopic model, firstly analyzing the number of resource points in a wharf, then analyzing the number of paths from each resource point to each transfer station, then calculating the linear distance evaluation time of each resource point to each transfer station in a set region, sequencing all the resource points according to the length of the linear distance evaluation time of each transfer station, obtaining the resource point which has the widest radiation range and the least time consumption for a plurality of transfer stations in the set region, and setting the resource point as a scheduling central point to serve as the point with the largest resource bearing capacity;
step six: simulated transport vehicle
Simulating a transport vehicle in a three-dimensional GIS (geographic information System) scheduling macro model, setting the transportation speed of the transport vehicle, transporting the transport vehicle to a scheduling path for goods transportation to obtain the time used for simulation, further determining a scheduling central point, and simultaneously determining the shortest path from each resource point to each transfer station and a secondary short path, wherein the secondary short path is used as an alternative scheme;
step seven: practical application
And performing practical application according to the shortest path in the step six, recording the time consumption situation from each resource point to each transfer station in practice, verifying the practical feasibility of the main scheme, and replacing the shortest path and the secondary short path according to the path congestion situation to obtain the optimal scheme.
2. The intelligent automatic container terminal energy-saving comprehensive scheduling method of claim 1, wherein the method comprises the following steps: in the third step, the "predicted job completion time point" includes the trailer idle time interval.
3. The intelligent energy-saving comprehensive dispatching method for the automatic container terminal according to claim 1, characterized in that: and in the third step, planning a path in the optimal time, and meeting the following principle that under the condition that the trailer is sufficient, no unallocated equipment is ensured, the shore bridge with the longest waiting time is allocated preferentially, and the sum of all time after allocation is minimum.
4. The intelligent automatic container terminal energy-saving comprehensive scheduling method of claim 1, wherein the method comprises the following steps: in the fourth step, the specific process of constructing the coordinate three-dimensional model is as follows: the method comprises the steps of restoring a three-dimensional image of acquired data, stretching the model through 3Dmax software to form a wharf scheduling path model, outputting a corresponding GIS space model, vectorizing parameter information of the GIS space model through ArcMAP software, loading each vectorized path layer into the wharf scheduling path model, visualizing the data in a 3D mode, and enhancing a display effect through symbolization.
5. The intelligent automatic container terminal energy-saving comprehensive scheduling method of claim 1, wherein the method comprises the following steps: and in the fourth step, the overall model is cut, so that the internal elements are individualized.
6. The intelligent energy-saving comprehensive dispatching method for the automatic container terminal according to claim 1, characterized in that: and in the sixth step, a plurality of simulated transport vehicles are set to be of the same type, and the transport speed of the simulated transport vehicles is set to accord with the highest speed per hour of the road.
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| CN113460734B (en) * | 2021-06-29 | 2022-07-29 | 国能黄骅港务有限责任公司 | Shipment material operation amount control method, device and system |
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| CN113486293B (en) * | 2021-09-08 | 2021-12-03 | 天津港第二集装箱码头有限公司 | Intelligent horizontal transportation system and method for full-automatic side loading and unloading container wharf |
| CN113825282B (en) * | 2021-09-23 | 2023-10-17 | 中交第三航务工程勘察设计院有限公司 | Intelligent control method, control equipment and control system for dock lighting |
| CN113837692B (en) * | 2021-09-23 | 2023-10-03 | 广州智湾科技有限公司 | Intelligent scheduling decision method and decision system for port operation site vehicles |
| CN114509996A (en) * | 2022-01-10 | 2022-05-17 | 阿里云计算有限公司 | Equipment operation time length prediction and instruction scheduling method, equipment and storage medium |
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| CN115456474B (en) * | 2022-10-13 | 2023-11-10 | 深圳中科天巡信息技术有限公司 | Port operation scheduling method and system based on artificial intelligence |
| CN115973806B (en) * | 2023-01-09 | 2023-07-21 | 交通运输部广州打捞局 | Roll-on-roll-off ship method, device, system and storage medium |
| CN116596288B (en) * | 2023-07-18 | 2023-12-19 | 广州港数据科技有限公司 | Container terminal internal trailer scheduling method and system based on mobile edge calculation |
| CN117361169B (en) * | 2023-11-14 | 2024-05-31 | 中交机电工程局有限公司 | Unmanned shipment system of intelligent identification control |
| CN118097454B (en) * | 2024-04-26 | 2024-07-12 | 尔特数据科技(江苏)有限公司 | Method and system for measuring congestion condition of container terminal of port by satellite image |
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| JP6904373B2 (en) * | 2018-05-08 | 2021-07-14 | Ｊｆｅスチール株式会社 | Ship allocation plan creation method, operation method by that method, and ship allocation plan creation device |
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| CN109685435A (en) * | 2018-11-07 | 2019-04-26 | 上海图森未来人工智能科技有限公司 | Ship unloading, shipment control system and related system and device |
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