A car hauler driver scheduling algorithm based on an integrated model

Abstract

The present invention discloses a car hauler driver scheduling algorithm based on an integrated mode, comprising the following steps: determining the magnitude relationship between the number N1 of outbound trip tasks and the number M1 of inbound task pools; if N1 < M1, then determining the magnitude relationship between the occupied storage locations Xi in the current buffer and the maximum available buffer capacity Xmax, and if Xi ≤ Xmax, then updating the inbound task pool in real time; when N1 ≥ M1, directly entering the integrated matching process; determining the magnitude relationship between the number M2 of inbound task pools and the number N2 of outbound trip tasks, and if M2 ≥ N2, directly entering the integrated matching process; the driver randomly selects an inbound vehicle or a vehicle in the visual retention area from the buffer; determining the magnitude relationship between the total number y of inbound vehicles and the total number z of outbound vehicles; the driver scans through a PDA and then conducts inbound operations. Through intelligent matching by the algorithm of the present invention, the command-based outbound operation is changed to a dynamic, timely and uniform outbound operation, thereby minimizing the ineffective round trips of personnel and vehicles, and at the same time avoiding the ineffective waiting and walking fatigue of the drivers.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics warehousing, and in particular to a dispatching algorithm for commercial vehicle drivers based on an integrated mode. Background Art

[0002] For logistics warehousing transportation, a reasonable arrangement of the processes for product offline warehousing and outbound can improve the overall logistics transportation efficiency. The existing processes generally are as follows: The driving shift is mainly responsible for moving the newly produced vehicles offline into the buffer area; the driving shift issues an inbound instruction by estimating the buffer area traffic. After the inbound driver scans the vehicle information, the vehicle is driven to the designated position in the commercial vehicle parking area and parked, and then the driver takes the shuttle bus back to the buffer area; after receiving the outbound instruction, the outbound driver takes the shuttle bus to the designated area and drives the designated vehicle to the shipping yard; the vehicle outbound priority is higher than the inbound priority. Before optimization, the parking lot arranged the vehicles adjacent to each other by model and popularity. The same model of vehicles was parked in the same lane, and the models with higher popularity were parked in the area closer to the shipping yard.

[0003] However, in this operation mode, the inbound and outbound processes of the drivers are independent of each other, and there is a non-value-added business process for the drivers who need to be sent out for outbound and picked up for inbound by the shuttle bus. Specifically, there are the following problems:

[0004] Problem 1: Process isolation leads to ineffective round trips: The inbound and outbound processes are independent of each other. The outbound of commercial vehicles is specified by the vehicle VIN code, and the outbound storage location is fixed. The inbound vehicles are randomly selected by the vehicles in the buffer area, and the inbound storage locations are arranged adjacent to each other by vehicle type. The two do not achieve area matching, and the driver must return to the starting point for the next inbound and outbound tasks; therefore, in order to accelerate the driver turnover rate, the shuttle bus needs to make round trips for connection, resulting in the non-value-added action of the driver's ineffective round trips and the waste of the shuttle bus connection.

[0005] Problem 2: Manual dispatching generates block scheduling: The driving shift dispatcher manually arranges the inbound and outbound tasks, resulting in a relatively random distribution of task time points. Taking the outbound task as the highest priority and considering the maximum number of passengers that the shuttle bus can carry, the existing inbound and outbound schedules are distributed in a "block" shape, with uneven scheduling, resulting in high inventory and low service; and it is easy for the drivers to be unevenly busy and idle.

[0006] Problem 3: The degree of intelligence is relatively low, the utilization rate of storage locations can be further improved, and there is a lack of an effective algorithm for inbound and outbound dispatching and command. Considering the inbound at night, usually the near-field storage area or near-field transfer is closed during the day, which is likely to cause waste of advantageous storage locations.

[0007] Problem 4: Connecting time and safety hazards: The shuttle bus makes multiple round trips to the storage area each time. However, there are a large number of commercial vehicles in the storage area, the frequency of inbound and outbound tasks is high, and the shuttle bus needs to pick up and drop off drivers. Since the location of the driver is unknown, the route of the shuttle bus is not fixed, the connection sequence is relatively random, and it takes a long time to pick up and drop off passengers and search in the middle. There are detours and significant safety hazards;

[0008] Problem 5: High labor cost: Since the number of inbound / outbound operations throughout the year is nearly several hundred thousand times, there are many production and shipping vehicles every day, and there are also dozens of vehicle drivers. The imbalance between production and sales demands easily leads to uneven workloads, increasing management difficulties, and the labor cost is rising year by year. Summary of the Invention

[0009] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the specification of this application, to avoid obscuring the purpose of this part, the abstract, and the title. However, such simplifications or omissions shall not be used to limit the scope of the present invention.

[0010] In view of the problems existing in the above-mentioned existing commercial vehicle driver scheduling algorithm based on an integrated mode, the present invention is proposed.

[0011] Therefore, the purpose of the present invention is to provide a commercial vehicle driver scheduling algorithm based on an integrated mode, which aims to improve the operational efficiency in the storage area, reduce safety risks, and reduce the ineffective round trips of personnel and vehicles.

[0012] To solve the above technical problems, the present invention provides the following technical solutions: A commercial vehicle driver scheduling algorithm based on an integrated mode, including the following steps:

[0013] Step 1: Before releasing the inbound task, set the real-time time for pulling commercial vehicles into the warehouse as t1, and the latest outbound lane time as tmin. At time t1, judge the size of the number of outbound lane tasks N1 and the number of inbound task pools M1. If N1 < M1, then judge the size of the occupied storage location Xi in the current buffer area and the maximum available buffer capacity Xmax. If Xi ≤ Xmax, then update the inbound task pool in real time. If Xi > Xmax, then release the inbound task according to the original process batch, and the shuttle bus picks up and drops off from the storage area;

[0014] Step 2: When N1 ≥ M1, directly enter the integrated matching process, and use the outbound task to pull the inbound task;

[0015] Step 3: Before releasing the outbound task, judge the size of the number of inbound task pools M2 and the number of outbound lane tasks N2 at the current outbound time t2. If M2 ≥ N2, then directly enter the integrated matching process and perform storage location matching in coordination with Step 2;

[0016] Step 4: The driver randomly selects a vehicle to be stored in the warehouse from the buffer area or a vehicle in the visual retention area. The logistics system pushes the information of the storage location in the warehouse, confirms the vehicle model of the commercial vehicle being transported currently, and preferentially selects the current commercial vehicle to be stored in the warehouse according to the vehicle model of the commercial vehicle being transported currently, and then other vehicles;

[0017] Step 5: Judge the size relationship between the total number y of vehicles to be stored in the warehouse and the total number z of vehicles to be shipped out. If y < z, in the storage state, allocate z drivers to enter the warehouse, where y drivers are responsible for driving, and the remaining z - y drivers go to the storage area together. In the shipping state, z drivers go out of the warehouse and reach the shipping sequence. If y ≥ z, in the storage state, allocate y drivers to enter the warehouse. In the shipping state: allocate y drivers to go out of the warehouse, where z drivers are responsible for driving, and the remaining y - z drivers without shipping tasks go to the shipping sequence together;

[0018] Step 6: The driver scans through the PDA and then enters the warehouse. After parking the vehicle at the designated storage location, confirm it on the PDA. Finally, z drivers have shipping tasks.

[0019] As a preferred solution of the commercial vehicle driver scheduling algorithm based on the integrated mode described in the present invention, wherein: in the process of step 3, if M2 < N2, judge whether it exceeds the latest shipping sequence time tmin at the current shipping time t2. If it does not exceed, update the shipping task pool. If it exceeds, directly release the shipping sequence task according to the original process batch, and the feeder vehicle will send it to the storage area.

[0020] As a preferred solution of the commercial vehicle driver scheduling algorithm based on the integrated mode described in the present invention, wherein: in the process of step 6, after the driver obtains the shipping task, go to the designated storage location, scan through the PDA and then carry out shipping. After completion, park the vehicle at the designated shipping sequence, confirm it on the PDA, and judge whether the vehicle has completed entering and leaving the warehouse;

[0021] If the task is completed, wait at a specific time for the feeder vehicle to pick up the driver and send him to the rest area. If not, the feeder vehicle will send the driver back to the buffer area and repeat step 4.

[0022] As a preferred solution of the commercial vehicle driver scheduling algorithm based on the integrated mode described in the present invention, wherein: in the process of step 1, when updating the storage task pool, it is necessary to put the vehicle models in the buffer area into the task pool.

[0023] As a preferred solution of the commercial vehicle driver scheduling algorithm based on the integrated mode described in the present invention, wherein: before updating the shipping task pool, according to the time, sequence, and order arrangement of the reservation queuing system, put the shipping tasks into the shipping task pool, and calculate the latest shipping time of each sequence task based on the geographic information data.

[0024] As a preferred solution of the car hauler driver scheduling algorithm based on the integrated mode of the present invention, in the process of step three, the best outbound vehicle is selected according to the AIC code, its location information and the surrounding vacant space information are determined, and the storage location information of the best matching inbound vehicle is found.

[0025] As a preferred solution of the car hauler driver scheduling algorithm based on the integrated mode of the present invention, in the process of step four, if the outbound vehicle is of other models and the buffer area already has the car hauler of the current model, the storage location of the current model car hauler is preferentially selected for inbound, otherwise it is randomly selected.

[0026] As a preferred solution of the car hauler driver scheduling algorithm based on the integrated mode of the present invention, the storage location to be inbound, the scanning time, the parking lane number, and the outbound waiting status will be displayed on the driver's handheld PDA interface.

[0027] Advantages of the present invention:

[0028] Through intelligent matching by the algorithm of the present invention, the command-based outbound is changed to dynamic, timely and uniform outbound, thereby minimizing the ineffective round trips of personnel and vehicles. At the same time, the ineffective waiting and walking fatigue of drivers are avoided, and the working efficiency of the integrated mode is greatly improved compared with the traditional inbound and outbound mode;

[0029] By reducing the ineffective round trips, the present invention can effectively save the number of drivers required for the task and the moving mileage of the shuttle vehicles, reduce the labor cost, and at the same time significantly reduce the fuel consumption of the shuttle vehicles. And through the integrated inbound, the night shift inbound is cancelled, and the drivers work concentratedly during the day, avoiding problems such as shift scheduling and night safety caused by double shifts;

[0030] The improvement of the present invention in the safety of the storage area is very obvious. By optimizing the operation steps in the storage area and reducing the round trips of the shuttle vehicles in the storage area, not only the operation efficiency in the storage area is improved, but also the safety risk can be reduced and the customer satisfaction can be enhanced. Brief Description of the Drawings

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. Among them:

[0032] Figure 1 It is a flow chart of a car hauler driver scheduling algorithm based on the integrated mode proposed by the present invention. Detailed Embodiments

[0033] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the specific embodiments of the present invention in detail with reference to the accompanying drawings of the specification.

[0034] In the following description, many specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may be implemented in other ways different from those described herein. Those skilled in the art can make similar generalizations without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0035] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation manner of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that excludes other embodiments.

[0036] Thirdly, the present invention is described in detail in conjunction with schematic diagrams. When detailing the embodiments of the present invention, for the convenience of explanation, the cross-sectional views showing the device structure will be enlarged locally in a non-general proportion, and the schematic diagrams are only examples and should not limit the scope of protection of the present invention herein. In addition, in actual production, three-dimensional spatial dimensions including length, width, and depth should be included. Embodiment 1

[0037] Refer to Figure 1 , which is the first embodiment of the present invention, and provides a driver scheduling algorithm for commercial vehicles based on an integrated mode. This algorithm includes the following steps:.

[0038] Step 1: Before releasing the inbound task, set the real-time time for pulling inbound commercial vehicles as t1, and the latest outbound lane time as tmin. At time t1, judge the size of the number of outbound lane tasks N1 and the number of inbound task pools M1. If N1 < M1, then judge the size of the occupied warehouse positions Xi in the current buffer area and the maximum available buffer capacity Xmax. If Xi ≤ Xmax, update the inbound task pool in real time. If Xi > Xmax, release the inbound task according to the original process batch, and the feeder vehicle will pick up from the storage area. It should be noted that when updating the inbound task pool, the commercial vehicle models in the buffer area need to be put into the task pool.

[0039] Step 2: When N1 ≥ M1, directly enter the integrated matching process, and the outbound task will pull the inbound task;

[0040] Step 3: Before releasing the outbound task, determine the size relationship between the quantity M2 in the inbound task pool and the quantity N2 of the outbound lane tasks at the current outbound time t2. If M2 ≥ N2, directly proceed with the integrated matching process and cooperate with Step 2 for storage location matching, that is, select the best outbound vehicle according to the AIC code, determine its location information and the surrounding vacant space information, and find the storage location information of the best-matched inbound vehicle. If M2 < N2, determine whether the current outbound time t2 exceeds the latest outbound lane time tmin. If it does not exceed, update the outbound task pool. If it exceeds, directly release the outbound lane tasks in batches according to the original process and send them to the storage area by the shuttle vehicle. It should be noted that before updating the outbound task pool, place the outbound tasks into the outbound task pool according to the time, lane, and sequence arrangement of the reservation queuing system, and calculate the latest outbound time for each lane task based on the geographical information data;

[0041] Step 4: The driver randomly selects an inbound vehicle from the buffer area or a vehicle in the visual retention area. The logistics system pushes the inbound storage location information, confirms the vehicle model of the current commodity vehicle being transported, and preferentially selects the current commodity vehicle for inbound according to the vehicle model of the currently transported commodity vehicle. Secondly, select other vehicles. If the outbound vehicle is of other models and the buffer area already has a commodity vehicle of the current model, preferentially select the storage location of the current model commodity vehicle for inbound. Otherwise, randomly select;

[0042] Step 5: Judge the size relationship between the total number y of inbound vehicles and the total number z of outbound vehicles. If y < z, in the inbound state, allocate z drivers to enter the warehouse, where y drivers are responsible for driving (i.e., the y drivers with inbound tasks), and the remaining z - y drivers go to the storage area together. In the outbound state, z drivers go out of the warehouse and reach the outbound lane;

[0043] If y ≥ z, in the inbound state, allocate y drivers to enter the warehouse (y drivers have inbound tasks). In the outbound state: allocate y drivers to go out of the warehouse, where z drivers drive (i.e., the z drivers with outbound tasks), and the remaining y - z drivers without outbound tasks go to the outbound lane together;

[0044] Step 6: The driver scans through the PDA and then enters the warehouse. After parking the vehicle at the designated storage location, confirm through the PDA. The handheld PDA interface of the driver will display the storage location to be entered, the scanning time, the parking lane, and the outbound status. Finally, during the use of the z drivers with outbound tasks, that is, after the driver obtains the outbound task, go to the designated storage location, scan with the PDA and then go out of the warehouse. After completion, park the vehicle at the designated outbound lane and confirm through the PDA to judge whether the vehicle has completed the inbound and outbound process; If the task is completed, wait at a specific time for the shuttle vehicle to pick up the driver and send them to the rest area. If not, the shuttle vehicle will send the driver back to the buffer area and repeat Step 4;

[0045] Through intelligent algorithm matching, the present invention changes the instruction-based storage out into a dynamic and timely uniform storage out, thereby minimizing the ineffective round trips of personnel and vehicles. At the same time, it avoids the ineffective waiting and walking fatigue of drivers. Moreover, the working efficiency of the integrated method is greatly improved compared with that of the traditional storage in and out method. Reducing the ineffective round trips can effectively save the number of drivers required for the task and the moving mileage of the shuttle vehicles, reduce the labor cost, and at the same time significantly reduce the fuel consumption of the shuttle vehicles. And through the integrated storage in, the night shift storage in is cancelled, and the drivers work concentratedly during the day, avoiding problems such as shift scheduling and night safety caused by double shifts. The improvement in the safety of the storage area is very obvious. Optimizing the operation steps in the storage area and reducing the round trips of the shuttle vehicles in the storage area can not only improve the operation efficiency in the storage area, but also reduce the safety risks and enhance the customer satisfaction.

[0046] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A car carrier driver scheduling algorithm based on an integrated mode, characterized in that: It includes the following steps: Step 1: Before releasing the inbound task, set the real-time time for pulling inbound car carriers as t1, and the latest outbound lane time as tmin. At time t1, judge the size of the outbound lane task quantity N1 and the inbound task pool quantity M1. If N1 < M1, then judge the size of the currently occupied storage location Xi in the buffer area and the maximum available buffer capacity Xmax. If Xi ≤ Xmax, then update the inbound task pool in real time. If Xi > Xmax, then release the inbound task according to the original process batch, and the shuttle vehicle picks up and transports from the storage area; Step 2: When N1 ≥ M1, directly enter the integrated matching process, and use the outbound task to pull the inbound task; Step 3: Before releasing the outbound task, judge at the current outbound time t2: the size of the inbound task pool quantity M2 and the outbound lane task quantity N2. If M2 ≥ N2, then directly enter the integrated matching process, and perform storage location matching in coordination with Step 2; Step 4: The driver randomly selects an inbound vehicle or a vehicle in the visual retention area from the buffer area. The logistics system pushes the inbound storage location information, confirms the vehicle model of the currently transported car carrier, and preferentially selects the current car carrier for inbound according to the vehicle model of the currently transported car carrier, and then other vehicles; Step 5: Judge the size relationship between the total number of inbound vehicles y and the total number of outbound vehicles z. If y < z, then in the inbound state, allocate z drivers to enter the warehouse, where y drivers are responsible for driving, and the remaining z - y drivers go to the storage area together. In the outbound state, z drivers go out of the warehouse and reach the outbound lane; If y ≥ z, in the inbound state, allocate y drivers to enter the warehouse. In the outbound state: allocate y drivers to go out of the warehouse, where z drivers drive, and the remaining y - z drivers without outbound tasks go to the outbound lane together; Step 6: The driver scans through the PDA and then enters the warehouse, and then parks the vehicle at the designated storage location and confirms through the PDA. Finally, z drivers have outbound tasks.

2. A car carrier driver scheduling algorithm based on an integrated mode according to claim 1, characterized in that: During the process of Step 3, if M2 < N2, then judge whether the current outbound time t2 exceeds the latest outbound lane time tmin. If it does not exceed, then update the outbound task pool. If it exceeds, directly release the outbound lane task according to the original process batch, and the shuttle vehicle sends it to the storage area.

3. A car carrier driver scheduling algorithm based on an integrated mode according to claim 2, characterized in that: During the process of Step 6, after the driver obtains the outbound task, go to the designated storage location, scan with the PDA and then go out of the warehouse. After completion, park the vehicle at the designated outbound lane and confirm on the PDA to judge whether the vehicle has completed inbound and outbound; If the task is completed, wait at a specific time for the shuttle vehicle to pick up the driver and send him to the rest area. If not, the shuttle vehicle sends the driver back to the buffer area, and repeat Step 4.

4. A car carrier driver scheduling algorithm based on an integrated mode according to claim 1, characterized in that: During the first step, when updating the inbound task pool, the vehicle models in the buffer area need to be put into the task pool.

5. A car hauler driver scheduling algorithm based on an integrated mode according to any one of claims 1 to 4, characterized in that: Before updating the outbound task pool, according to the time, lane number, and sequence arrangement of the reservation queuing system, the outbound tasks are put into the outbound task pool, and the latest outbound time for each lane task is calculated based on the geographic information data.

6. A car hauler driver scheduling algorithm based on an integrated mode according to claim 1, characterized in that: During the third step, the best outbound vehicle is selected according to the AIC code, its location information and the surrounding vacant space information are determined, and the location information of the storage space for the best matching inbound vehicle is found.

7. A car hauler driver scheduling algorithm based on an integrated mode according to claim 1, characterized in that: During the fourth step, if the outbound vehicle is of other models and the buffer area already has the current model of car hauler, the current model of car hauler storage space is preferentially selected for inbound, otherwise it is randomly selected.

8. A car hauler driver scheduling algorithm based on an integrated mode according to claim 7, characterized in that: The storage space to be inbound, the scanning time, the parking lane number, and the outbound status to be are displayed on the driver's handheld PDA interface.

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