KR20200078318A - Situation-adapted Global Pooling System and Method for Transfer Vehicles in Automated Container Terminal - Google Patents

Abstract

Suggested are a situational adaptive global pooling system and method for a transporting vehicle in an automated container terminal. According to one embodiment of the present invention, the situational adaptive global pooling method for a transporting vehicle in an automated container terminal may comprise the steps of: receiving a request for work allocation from an idle transfer vehicle; searching an optimal combination of a pair of a transporting vehicle and work by using a transporting vehicle work allocation algorithm in a combination that a transporting vehicle, which is not currently performing work or is about to finish work, and a work to be processed soon based on the time when the request is received; and allocating work to a transporting vehicle if there is the work matching the transporting vehicle requesting work allocation in the optimal combination of the pair of the transporting vehicle and the work obtained as a result of search.

Description

Situation-adapted Global Pooling System and Method for Transfer Vehicles in Automated Container Terminal}

The embodiments below relate to a contextualized automated container terminal transport vehicle global pooling system and method, and more particularly, to a transport vehicle job assignment system and method in an automated container terminal that must achieve a low carbon target.

1 is a view for explaining the structure of a typical automated container terminal.

Referring to FIG. 1, the container terminal can be roughly divided into three areas: a quay wall area 110, a device length area 120, and a hinterland area 130. The quaywall region 110 is a place where the vessel is temporarily moored, and a loading operation of loading a container on a ship and a loading and unloading operation of a container on the ship occur. The device area 120 is a place where containers are temporarily stored before being exported or imported, and the hinterland area 130 is a place where external trucks transporting imported containers to land or carrying an export container coming from land to a terminal come and go. .

A transport vehicle, such as an automated guided vehicle in an automated container terminal, is responsible for transporting the import and export containers between the quay wall and the device cabinet. The transport vehicle receives the imported container from the quayside crane (QC) and transfers it to the device site, or receives the export container from the device site and passes it to the quayside crane (QC). At this time, the site assigns a container to be carefully operated so that the transport vehicle can exchange containers with the quarantine crane (QC) without delay as much as possible, because the quarantine crane (QC) processes the import and export containers without delay, That is, as the productivity of the terminal increases, the re-arrival time of the ship decreases, so that the terminal can service more ships, which leads to an increase in imports.

However, in recent years, as the pressure to achieve an eco-friendly terminal through reduction of carbon emissions increases, it is required not only to increase the productivity of the terminal, but also to suppress the carbon emission as much as possible. From a transport vehicle's point of view, to reduce carbon emissions, it is necessary to allocate work that minimizes the no-load mileage (ie, the distance traveled without a container), which also temporarily increases productivity. However, if you try to reduce excessively no-load mileage, you will experience a decrease in productivity because the number of work assignments violating the work deadline increases. Accordingly, there is an increasing need in the field for a transport vehicle operation method capable of achieving a required goal according to the current situation.

Korean Patent Publication No. 10-2016-0004052 relates to a system for generating a work command for controlling an unmanned transport vehicle, and generates a virtual work command on a predetermined layout, performs a return command, and is optimized through collected data. Describes the technology of the system to determine the equipment layout and calculate the optimal number of AGVs.

Korean Patent Publication No. 10-2016-0004052

The embodiments describe a situation-adaptive automated container terminal transport vehicle global pooling system and method, and more particularly, provide a transport vehicle job allocation technology in an automated container terminal that must achieve a low carbon target.

Embodiments in an automated container terminal capable of achieving a desired goal according to the current situation by allowing the user to operate the transport vehicle by selecting the current situation between the allocation algorithm for maximizing productivity and the allocation algorithm for minimizing carbon emissions. It is to provide a global pooling system and method of transportation vehicles.

In a situation-adaptive automated container terminal according to an embodiment, a global pulling method of a transport vehicle includes: receiving a request for work assignment from an idle transport vehicle; Based on the time at which the request was received, the optimal transport vehicle-work pair combination is searched using the transfer vehicle job allocation algorithm in the combination that matches the job to be processed and the transfer vehicle that is not currently working or the job is finished soon. To do; And assigning the job to the transfer vehicle when there is a job matching the transfer vehicle requesting job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search.

If there is no job matching the transfer vehicle that requested the job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search, the job may not be allocated.

The transfer vehicle work allocation algorithm may search for the optimal transfer vehicle-work pair combination using a Hungarian algorithm.

Searching for an optimal transfer vehicle-work pair combination using the transfer vehicle work assignment algorithm may include: outputting a score by evaluating possible transfer vehicle-work pairs according to various predetermined criteria using a scoring function; And obtaining a combination having the lowest or highest total score among all combinations of the possible transport vehicles-work pairs through a Hungarian algorithm.

The scoring function may score the score by evaluating the possible transport vehicle-work pairs according to a plurality of predetermined criteria, and design the criteria differently according to a set user goal.

The scoring function may score points according to differently designed criteria as the user selects a target that is currently needed among goals that minimize carbon emissions and goals that maximize work productivity.

The scoring function, which aims to minimize the carbon emission, may be designed to minimize the carbon emission by using the average no-load driving time of the transport vehicle as a carbon emission index.

The scoring function, which aims to maximize the work productivity, may be designed to maximize the work productivity by using the number of container processes per hour of the quayside crane QC as a productivity index.

In a situation-adaptive automated container terminal according to another embodiment, a transport vehicle global pooling system includes: an input unit for requesting work assignment from an idle transport vehicle; Based on the time when the request was received, search for the optimal combination of the transport vehicle-work pair using the transport vehicle work allocation algorithm in the combination that matches the transport vehicle that is not currently being performed or the work that is about to be completed and the job to be processed Transfer vehicle work allocation algorithm unit; And a job allocation unit for allocating the job to the transfer vehicle when there is a job matching the transfer vehicle requesting job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search.

The job allocating unit may not allocate the job if there is no job matching the transfer vehicle requesting job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search.

The transfer vehicle work assignment algorithm unit includes: a score assignment function unit that evaluates possible transfer vehicles-work pairs according to various predetermined criteria using a scoring function and outputs a score; And a Hungarian algorithm unit that obtains a combination having the lowest or highest total score among all combinations of the possible transport vehicles-work pairs through the Hungarian algorithm.

The scoring function may score the score by evaluating the possible transport vehicle-work pairs according to a plurality of predetermined criteria, and design the criteria differently according to a set user goal.

The scoring function may score points according to differently designed criteria as the user selects a target that is currently needed among goals that minimize carbon emissions and goals that maximize work productivity.

The scoring function, which aims to minimize the carbon emission, may be designed to minimize the carbon emission by using the average no-load driving time of the transport vehicle as a carbon emission index.

The scoring function, which aims to maximize the work productivity, may be designed to maximize the work productivity by using the number of container processes per hour of the quayside crane QC as a productivity index.

According to the embodiments, among the allocation algorithms that maximize productivity and the allocation algorithms that minimize carbon emissions, an automated container capable of achieving a desired goal according to the current situation by allowing a user to select and operate the transport vehicle according to the current situation It is possible to provide a global pooling system and method for transport vehicles in a terminal.

1 is a view for explaining the structure of a typical automated container terminal.
2 is a diagram for describing a global pooling method according to an embodiment.
3 is a view for explaining a global pooling system for a situation-adaptive automated container terminal transport vehicle according to an embodiment.
4 is a flowchart illustrating a global pooling method of a situation-adaptive automated container terminal transport vehicle according to an embodiment.
FIG. 5 is a block diagram illustrating a global pooling system for a situation-adaptive automated container terminal transport vehicle according to an embodiment.
6 is a view for explaining a method for obtaining a transport vehicle-working optimal combination using a Hungarian algorithm according to an embodiment.

Hereinafter, embodiments will be described with reference to the accompanying drawings. However, the described embodiments may be modified in various other forms, and the scope of the present invention is not limited by the embodiments described below. In addition, various embodiments are provided to more fully describe the present invention to those skilled in the art. The shape and size of elements in the drawings may be exaggerated for a more clear description.

The following embodiments are directed to a transport vehicle global pulling system and method in a situation-adaptive automated container terminal, and can provide a transport vehicle job allocation technology in an automated container terminal that must achieve a low-carbon target.

2 is a diagram for describing a global pooling method according to an embodiment.

Referring to FIG. 2, for explaining a global pooling method according to an embodiment, FIG. 2A shows an existing local pooling method, and FIG. 2B shows a global pooling method according to an embodiment.

A situation-adaptive automated container terminal transport vehicle global pooling system according to an embodiment is a transport vehicle work allocation system in an automated container terminal that must achieve a low-carbon target, and includes an allocation algorithm that maximizes productivity and an allocation algorithm that minimizes carbon emissions. With all of them, the user can select one of two algorithms to suit the current situation so that the transport vehicle can be operated. In addition, the embodiments may use a global pooling method of allocating work for all transport vehicles, not a local pooling method of assigning work by designating work groups for each quayside crane (QC) for flexible work assignment to achieve a goal. You can.

A situation-adaptive automated container terminal transport vehicle global pooling system according to an embodiment is a transport vehicle work assignment system that allocates a container to work to a transport vehicle so as to achieve the target as much as possible when a user sets a work assignment goal. Users can set goals by selecting one of the goals that maximize terminal productivity and those that minimize carbon emissions. A work allocation algorithm that achieves the goal of maximizing terminal productivity can be designed to take and maximize the number of container handling per hour of a quayside crane (QC) as a productivity indicator. In addition, an algorithm that achieves the goal of minimizing carbon emissions can be designed to use the average no-load driving time of the transport vehicle as a carbon emission index and minimize it.

3 is a view for explaining a global pooling system for a situation-adaptive automated container terminal transport vehicle according to an embodiment.

Referring to FIG. 3, the global pooling system 300 for a situation-adaptive automated container terminal transport vehicle according to an embodiment may be operated as follows. When the transport vehicle is in an idle state, a work assignment may be requested to the transport vehicle global pooling system 300. The global pooling system 300 of the transport vehicle is based on the time when the request is received, and the target of the most user among the combinations of the transport vehicle with no work currently being performed or the work to be processed soon is matched (minimize carbon emissions or work) Hungarian algorithms can be used to find combinations that can best achieve maximum productivity.

If there is a job matching the transfer vehicle that has requested the job assignment in the transport vehicle global pooling system 300 in the combination thus found, the job can be assigned to the transfer vehicle that has requested the job allocation. If there is no matched task, no task is assigned.

4 is a flowchart illustrating a global pooling method of a situation-adaptive automated container terminal transport vehicle according to an embodiment.

Referring to FIG. 4, a global pooling method of a transport vehicle in a situation-adaptive automated container terminal according to an embodiment is a step of receiving a request for work allocation from an idle transport vehicle (S110), based on a time when the request is received, and Searching for an optimal transfer vehicle-work pair combination using a transfer vehicle job allocation algorithm in a combination of matching a transfer vehicle with no work being performed or a job to be processed soon and a job to be processed soon (S120) and obtaining it as a search result When there is a job matched to the transfer vehicle that requested the job allocation in the optimal transfer vehicle-job pair combination, it may be made by including the step (S130) of allocating the job to the transfer vehicle.

If there is no job matching the transfer vehicle that requested the job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search, the job may not be allocated.

Hereinafter, each step of the global pulling method of a transport vehicle in a situation-adaptive automated container terminal according to an embodiment will be described.

The global pulling method of a transport vehicle in a situation-adaptive automated container terminal according to an embodiment may be described in more detail through a global pulling system of a transport vehicle in a situation-adaptive automated container terminal according to an embodiment.

FIG. 5 is a block diagram illustrating a global pooling system for a situation-adaptive automated container terminal transport vehicle according to an embodiment.

5, the situation-adaptive automated container terminal transport vehicle global pooling system 500 according to an embodiment includes an input unit 510, a transport vehicle work allocation algorithm unit 520, and a work allocation unit 530. You can. Here, the transfer vehicle work allocation algorithm unit 520 may include a scoring function unit 521 and a Hungarian algorithm unit 522.

In step S110, the input unit 510 may be requested to allocate work from an idle transport vehicle.

In step S120, the transfer vehicle job allocation algorithm unit 520 is a transfer vehicle job in a combination of matching a job to be processed and a transfer vehicle that is not currently being performed or a job that is currently being performed, based on the time when the request is received. The allocation algorithm can be used to find the optimal transport vehicle-work pair combination. Here, the transfer vehicle work allocation algorithm can search for an optimal transfer vehicle-work pair combination using a Hungarian algorithm.

In step S130, when there is a job matched with the transfer vehicle that requested the job allocation in the optimal transfer vehicle-job pair combination obtained as the search result, the job allocation unit 530 may assign the job to the transfer vehicle. . On the other hand, if there is no job matching the transfer vehicle that requested the job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search, the job allocation unit 530 may not allocate the job.

The transfer vehicle work allocation algorithm unit 520 may include a scoring function unit 521 and a Hungarian algorithm unit 522.

The scoring function unit 521 may output a score by evaluating possible transfer vehicle-work pairs according to various predetermined criteria using the scoring function. The scoring function can score possible scores by evaluating possible transport vehicle-work pairs according to several predetermined criteria, and design the criteria differently according to a set user goal.

More specifically, the scoring function may score according to differently designed criteria as the user selects a target that is currently required among goals that minimize carbon emissions and goals that maximize work productivity. The scoring function aimed at minimizing carbon emissions can be designed to minimize carbon emissions by using the average no-load travel time of the transport vehicle as a carbon emission index. In addition, the scoring function aimed at maximizing work productivity may be designed to maximize work productivity by using the number of container processes per hour of the quayside crane QC as a productivity index.

The Hungarian algorithm unit 522 may obtain a combination having the lowest or highest total score among all combinations of transport vehicles-work pairs possible through the Hungarian algorithm.

Below, the transfer vehicle work allocation algorithm will be described in more detail.

6 is a view for explaining a method for obtaining a transport vehicle-working optimal combination using a Hungarian algorithm according to an embodiment.

Referring to FIG. 6, in order to use the Hungarian algorithm, the system may use a scoring function that calculates a score for a transport vehicle requesting work assignment and a work pair to be assigned to the transport vehicle. The scoring function evaluates and scores a transport vehicle-work pair according to various criteria, and the criteria may be designed differently according to a target set by a user (minimizing carbon emission or maximizing work productivity). The scoring function can receive a transfer vehicle-work pair as input and output a score for it. Using the scoring function, after scoring all transfer vehicles-work pairs, the Hungarian algorithm can obtain the best possible combination of all transfer vehicle-work pairs.

Here, the Hungarian algorithm used in the system may operate to prefer a low score of the combination. The obtained transport vehicle-optimal combination of jobs can be used to assign jobs to the transfer vehicle. The process of obtaining the optimal combination of transport vehicle-work using the Hungarian algorithm can be represented as in FIG. 6.

In particular, the transfer vehicle-work pair scoring function can be expressed as follows.

There are two scoring functions, one for achieving the goal of minimizing carbon emissions and one for maximizing work productivity, and the user can select the currently required goal and perform work assignment. The expression of the scoring function can be expressed as follows.

[Equation 1]

는 각 평가 기준 값의 가중치이다. 평가 기준이 n 개가 있다면 그 가중치도 n 개가 존재할 수 있다. 이 때, 시스템에서 사용하는 평가 기준은 다음의 표 1과 같이 나타낼 수 있다.Here, C is a value according to the evaluation criteria,

Is the weight of each evaluation criterion value. If there are n evaluation criteria, there may be n weights. At this time, the evaluation criteria used in the system can be represented as in Table 1 below.

[Table 1]

Next, a scoring function can be designed according to a user's goal. To this end, a number of simulation experiments can be used to derive a scoring function optimized for each user's goal.

The scoring function to achieve the goal of minimizing carbon emissions can be expressed as the following equation.

[Equation 2]

In addition, a scoring function for achieving a goal of maximizing work productivity may be expressed as follows.

[Equation 3]

Hereinafter, the Hungarian algorithm will be described in more detail, for example.

The input of the Hungarian algorithm can be vehicle V, task J. At this time, the size of the vehicle V and the job J must be the same.

The vehicle-work score matrix is the score matrix of all vehicle-cost pairs and can be expressed as

[Equation 4]

The output of the Hungarian algorithm can output a list of the least expensive vehicle-work pairs.

The operation of the Hungarian algorithm can be expressed as follows.

First, it is possible to create a matrix of vehicle V for rows, task J for columns, and c(i, j) for elements in column j of each i.

Second, you can subtract the smallest element from that row from every row of elements.

Third, you can subtract the smallest element from that column from every column.

Finally, the following process can be repeated until all vehicles with a value of 0 match different tasks. That is, you can find the smallest of the non-zero element values and subtract them from all elements in the row. Then, you can add all of the elements in the column where the negative element is created by the size of the negative number.

Example

It is assumed that as input to the Hungarian algorithm, scores are given for two vehicles, three jobs, and a vehicle-job.

At this time, the following matrix can be generated by adding one temporary vehicle to match the number of vehicles and the number of tasks. Here, the work score for the temporary vehicle can be set to zero.

The operation of the Hungarian algorithm can be expressed as follows.

First, it is possible to create a matrix consisting of a vehicle V in a row, task J in a column, and c(i, j) in each i-column j-column, and can be expressed as follows.

[Table 2]

Second, the smallest element in the row can be subtracted from the elements in all rows, and can be expressed as follows.

[Table 3]

Third, the smallest element in the column can be subtracted from the elements in all columns, and can be expressed as: Here, since the value of the smallest element in the column is 0, there is no change.

[Table 4]

Finally, the following process can be repeated until all vehicles with a value of 0 match different tasks. In other words, you can find the smallest value among non-zero elements, and subtract the value from all elements in the row.

[Table 5]

Then, all the elements in the column where the negative element is generated can be added as much as the size of the negative number, and can be expressed as follows.

[Table 6]

Different jobs can be matched to all vehicles with a value of zero. That is, vehicle 1-task 3, vehicle 2-task 1, temporary vehicle-task 2 may be matched.

[Table 7]

Here, the work assignment of the temporary vehicle can be excluded.

Accordingly, as output of the Hungarian algorithm, task 3 can be assigned to vehicle 1 and task 1 can be assigned to vehicle 2.

The device described above may be implemented with hardware components, software components, and/or combinations of hardware components and software components. For example, the devices and components described in the embodiments include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor (micro signal processor), a microcomputer, a field programmable array (FPA), It may be implemented using one or more general purpose computers or special purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. The processing device may run an operating system (OS) and one or more software applications running on the operating system. Further, the processing device may access, store, manipulate, process, and generate data in response to the execution of the software. For convenience of understanding, a processing device may be described as one being used, but a person having ordinary skill in the art, the processing device may include a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that may include. For example, the processing device may include a plurality of processors or a processor and a controller. In addition, other processing configurations, such as parallel processors, are possible.

The software may include a computer program, code, instruction, or a combination of one or more of these, and configure the processing device to operate as desired, or process independently or collectively You can command the device. Software and/or data may be interpreted by a processing device, or to provide instructions or data to a processing device, of any type of machine, component, physical device, virtual equipment, computer storage medium or device. Can be embodied in The software may be distributed on networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, or the like alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiments or may be known and usable by those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs, DVDs, and magnetic media such as floptical disks. Includes hardware devices specifically configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language code that can be executed by a computer using an interpreter, etc., as well as machine language codes produced by a compiler.

As described above, although the embodiments have been described by a limited embodiment and drawings, those skilled in the art can make various modifications and variations from the above description. For example, the described techniques are performed in a different order than the described method, and/or the components of the described system, structure, device, circuit, etc. are combined or combined in a different form from the described method, or other components Alternatively, proper results can be achieved even if replaced or substituted by equivalents.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (15)

In the method of global pooling of transport vehicles in a situation-adaptive automated container terminal,
Receiving a work assignment request from an idle transport vehicle;
Based on the time at which the request was received, the optimal transport vehicle-work pair combination is searched using the transfer vehicle job allocation algorithm in the combination that matches the job to be processed and the transfer vehicle that is not currently working or the job is finished soon. To do; And
Allocating the job to the transfer vehicle if there is a job matching the transfer vehicle requesting job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search
Containing, a global pooling method of transport vehicles. According to claim 1,
If there is no job matching the transfer vehicle requesting job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search, the job is not allocated
Characterized in that, the transport vehicle global pooling method. According to claim 1,
The transfer vehicle work allocation algorithm,
Using the Hungarian algorithm to find the optimal transport vehicle-work pair combination
Characterized in that, the transport vehicle global pooling method. According to claim 1,
The step of searching for an optimal transfer vehicle-work pair combination using the transfer vehicle job allocation algorithm is:
A possible transfer vehicle using a scoring function-evaluating work pairs according to a plurality of predetermined criteria and outputting a score; And
Obtaining a combination with the lowest or highest total score among all combinations of the above possible transport vehicles-working pairs through Hungarian algorithm
Containing, a global pooling method of transport vehicles. According to claim 4,
The scoring function,
The possible transport vehicle-the work pairs are evaluated according to several predetermined criteria, scored, and the criteria are designed differently according to the set user's goal
Characterized in that, the transport vehicle global pooling method. According to claim 4,
The scoring function,
Scoring by differently designed criteria as the user selects the current need among the goals that minimize carbon emissions and those that maximize work productivity
Characterized in that, the transport vehicle global pooling method. The method of claim 6,
The scoring function aimed at minimizing the carbon emissions,
Designed to minimize the above-mentioned carbon emission by using the average no-load driving time of the transport vehicle as a carbon emission index
Characterized in that, the transport vehicle global pooling method. The method of claim 6,
The scoring function that aims to maximize the work productivity,
Designed to maximize the productivity of the above by using the number of container handling per hour of the quayside crane (QC) as a productivity index
Characterized in that, the transport vehicle global pooling method. In a situation-adaptive automated container terminal, in a transport vehicle global pulling system,
An input unit for requesting work assignment from an idle transport vehicle;
Based on the time at which the request was received, the optimal transport vehicle-work pair combination is searched using the transfer vehicle job allocation algorithm in the combination that matches the job to be processed and the transfer vehicle that is not currently working or the job is finished soon. Transfer vehicle work allocation algorithm unit; And
When there is a job matched to the transfer vehicle that requested the job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search, a job allocation unit that allocates the job to the transfer vehicle
Including, transport vehicle global pooling system. The method of claim 9,
The work assignment unit,
If there is no job matching the transfer vehicle requesting job allocation in the optimal transfer vehicle-job pair combination obtained as a result of the search, the job is not allocated
Characterized by, the transport vehicle global pooling system. The method of claim 9,
The transfer vehicle work allocation algorithm unit,
A transport vehicle capable of using a scoring function-a scoring function unit for evaluating work pairs according to various predetermined criteria and outputting a score; And
The Hungarian algorithm unit that obtains the combination with the lowest or highest total score among all combinations of the possible transport vehicles-working pairs through Hungarian algorithm
Including, transport vehicle global pooling system. The method of claim 11,
The scoring function,
The possible transport vehicle-the work pairs are evaluated according to several predetermined criteria, scored, and the criteria are designed differently according to the set user's goal
Characterized by, the transport vehicle global pooling system. The method of claim 11,
The scoring function,
Scoring by differently designed criteria as the user selects the current need among the goals that minimize carbon emissions and those that maximize work productivity
Characterized by, the transport vehicle global pooling system. The method of claim 13,
The scoring function aimed at minimizing the carbon emissions,
Designed to minimize the above-mentioned carbon emission by using the average no-load driving time of the transport vehicle as a carbon emission index
Characterized by, the transport vehicle global pooling system. The method of claim 13,
The scoring function that aims to maximize the work productivity,
Designed to maximize the productivity of the above by using the number of container handling per hour of the quayside crane (QC) as a productivity index
Characterized by, the transport vehicle global pooling system.

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