Truck dynamic scheduling method, device and equipment and storage medium

Abstract

The application discloses a truck dynamic scheduling method and device, equipment and storage medium. The method comprises the following steps: determining the required truck number of the required path based on the target cargo flow rate and the current cargo flow rate of each path in the truck flow planning of the open-pit mine, wherein the cargo flow rate is the cargo flow volume borne by the unit length path per unit time, and the required path is the path with the current cargo flow rate less than the target cargo flow rate; determining the quick-action assignable truck number and the flow assignable truck number of the required path based on the current state of each truck, wherein the quick-action assignable truck number is the number of trucks waiting for unloading and trucks being unloaded, and the flow assignable truck number is the number of trucks waiting for unloading, trucks being unloaded and trucks being unloaded and then being transported by air; and determining the truck assigned to the required path based on the required truck number of the required path, the quick-action assignable truck number and the flow assignable truck number, and a set dynamic scheduling model. The truck dynamic adaptive scheduling can be considered in the truck and shovel balance and the truck and shovel imbalance and other scheduling scenarios.

Description

Technical Field

[0001] The present application relates to the field of mining, and in particular to a truck dynamic scheduling method, device, equipment and storage medium. Background Art

[0002] The production mode of open-pit mines is mainly based on the intermittent process of loading with shovels and transporting with trucks. The control of open-pit mine transportation costs is crucial to improving the overall efficiency of open-pit mines, and the effective scheduling of open-pit mine shovels is the main way to reduce mine transportation costs.

[0003] Traffic flow planning in open-pit mines specifies which shovels load materials, which routes, and which unloading points. This detailed shoveling plan optimizes the mine's production system and serves as a static plan for shift production. This results in dynamic optimization scheduling, which dynamically assigns trucks based on the shovel queues at loading points, predicted idleness, and queues at unloading points. This ensures that trucks don't wait for shovels, and shovels don't wait for trucks in open-pit mines, maximizing truck-shovel efficiency.

[0004] According to the goal of dynamic scheduling, it can be roughly divided into two categories: the first type of dynamic scheduling method aims to maximize the efficiency of forklifts or trucks, such as the earliest loading truck method, the minimum truck waiting method, the minimum shovel waiting method, the minimum forklift saturation method, the minimum truck transportation cycle method and the minimum forklift task deviation method; the second type of dynamic scheduling method aims to complete the task volume as much as possible, such as the minimum ratio variance algorithm, the ratio method and the two-stage method.

[0005] The first type of dynamic scheduling methods all focus on local scheduling preparation and are unable to optimize from a holistic and global perspective. They are only applicable to certain specific scheduling scenarios with fewer emergencies. The second type of methods primarily generates a vehicle-required route table and a truck table based on the current vehicle-shovel allocation. When the dynamic truck scheduling program is activated, the trucks in the truck table are assigned to the required routes based on the principle of assigning the best truck to the most required route. Analysis of the above dispatch logic shows that the so-called best truck only refers to the truck in the truck table for the most required shovel, rather than the global scheduling optimization principle. At the same time, when there are multiple vehicle models, this dispatch logic becomes inadequate. On the other hand, when there are a surplus of trucks, the first truck to be dispatched has the longest idle time, and the truck with the least production loss will be the last truck to be dispatched in the future. This will cause the current truck to be dispatched to a non-optimal route with an oversaturated truck population. Therefore, this dynamic scheduling logic also has certain limitations. Summary of the Invention

[0006] In view of this, the embodiments of the present application provide a truck dynamic scheduling method, device, equipment and storage medium, aiming to realize dynamic adaptive scheduling decisions of trucks in different scheduling scenarios such as vehicle-shovel balance and vehicle-shovel imbalance, so as to give full play to the vehicle-shovel efficiency of open-pit mines.

[0007] The technical solution of the embodiment of the present application is implemented as follows:

[0008] In a first aspect, an embodiment of the present application provides a method for dynamic truck scheduling, comprising:

[0009] Determine the number of trucks required for a route requiring trucks based on the target and current freight flow rates of each route in the dynamic truck scheduling process. The freight flow rate is the amount of freight carried per unit time on a route of unit length. A route requiring trucks is one where the current freight flow rate is less than the target freight flow rate.

[0010] Determine the number of quickly assignable trucks and the number of fluidly assignable trucks for the required route based on the current status of each truck, wherein the current status is one of the following: waiting to be loaded, loading, re-shipping after loading, waiting to be unloaded, unloading, and empty shipment after unloading; the number of quickly assignable trucks is the number of trucks waiting to be unloaded and unloading; and the number of fluidly assignable trucks is the number of trucks waiting to be unloaded, unloading, and empty shipment after unloading;

[0011] The trucks assigned to the vehicle-demanding path are determined based on the required number of trucks, the number of fast-assignable trucks, the number of fluid-assignable trucks, and a set dynamic scheduling model.

[0012] In some embodiments, the number of trucks required for a required path is determined based on the target cargo flow rate and the current cargo flow rate of each path in the dynamic truck scheduling, specifically as follows:

[0013]

[0014] in, It represents the number of trucks required from dispatch point i to shovel j. The function floor represents rounding towards negative infinity. represents the target cargo flow rate from dispatch point i to shovel j, represents the current cargo flow rate from dispatch point i to shovel j, represents the equivalent transport distance from dispatch point i to shovel j, and c represents the average load of the truck.

[0015] In some embodiments, the forklift trucks assigned to the required path are determined based on the required number of trucks, the number of quickly assignable trucks, the number of fluidly assignable trucks, and a set dynamic scheduling model, as follows:

[0016]

[0017] Among them, s represents the assigned truck number, It represents the preparation time of forklift i when the truck is dispatched to the forklift i. It represents the preparation time of the truck when it is dispatched to forklift i, represents the number of trucks required for the required route, Indicates the number of trucks that can be quickly assigned, represents the number of trucks that can be assigned to the flow, t now Indicates the current scheduling time. Indicates the estimated air transport time from the dispatch point to the forklift. represents the target output of forklift i, t a Indicates the total duration of the scheduling cycle, represents the current output of forklift i, represents the number of trucks in the route being dispatched to forklift i.

[0018] In a second aspect, an embodiment of the present application provides a truck dynamic dispatching device, comprising:

[0019] A first determination module is configured to determine the number of trucks required for a vehicle-requiring route based on a target cargo flow rate and a current cargo flow rate for each route in the dynamic truck scheduling, wherein the cargo flow rate is the cargo flow per unit time on a route of unit length, and the vehicle-requiring route is a route whose current cargo flow rate is less than the target cargo flow rate;

[0020] a second determining module, configured to determine the number of quickly assignable trucks and the number of fluidly assignable trucks for the required route based on a current state of each truck, wherein the current state is one of the following: waiting to be loaded, loading, re-shipping after loading, waiting to be unloaded, unloading, and empty shipment after unloading; the number of quickly assignable trucks is the number of trucks waiting to be unloaded and unloading, and the number of fluidly assignable trucks is the number of trucks waiting to be unloaded, unloading, and empty shipment after unloading;

[0021] The truck allocation module is used to determine the trucks allocated to the vehicle-demanding path based on the required number of trucks for the vehicle-demanding path, the number of quickly allocable trucks, the number of fluidly allocable trucks, and a set dynamic scheduling model.

[0022] In some embodiments, the second determination module determines the required number of trucks for the required path based on the target cargo flow rate and the current cargo flow rate of each path in the dynamic truck scheduling, specifically as follows:

[0023]

[0024] in, It represents the number of trucks required from dispatch point i to shovel j. The function floor represents rounding towards negative infinity. represents the target cargo flow rate from dispatch point i to shovel j, represents the current cargo flow rate from dispatch point i to shovel j, represents the equivalent transport distance from dispatch point i to shovel j, and c represents the average load of the truck.

[0025] In some embodiments, the truck allocation module determines the forklift to be allocated to the required path based on the required number of trucks, the number of quickly allocable trucks, the number of fluidly allocable trucks, and a set dynamic scheduling model, as follows:

[0026]

[0027] Among them, s represents the assigned truck number, It represents the preparation time of forklift i when the truck is dispatched to the forklift i. It represents the preparation time of the truck when it is dispatched to forklift i, represents the number of trucks required for the required route, Indicates the number of trucks that can be quickly assigned, represents the number of trucks that can be assigned to the flow, t now Indicates the current scheduling time. Indicates the estimated air transport time from the dispatch point to the forklift. represents the target output of forklift i, t a Indicates the total duration of the scheduling cycle, represents the current output of forklift i, represents the number of trucks in the route being dispatched to forklift i.

[0028] In a third aspect, an embodiment of the present application provides an electronic device comprising: a processor and a memory for storing a computer program that can be run on the processor, wherein when the processor is used to run the computer program, it executes the steps of the method described in the first aspect of the embodiment of the present application.

[0029] In a fourth aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method described in the first aspect of the embodiment of the present application are implemented.

[0030] The technical solution provided by the embodiment of the present application determines the required number of trucks for the required path based on the target cargo flow rate and current cargo flow rate of each path in the dynamic dispatch of trucks, wherein the cargo flow rate is the cargo flow per unit time on a path of unit length, and the required path is a path whose current cargo flow rate is less than the target cargo flow rate; based on the current status of each truck, determines the number of quickly assignable trucks and the number of mobile assignable trucks for the required path, wherein the number of quickly assignable trucks is the number of trucks waiting to be unloaded and in the process of being unloaded, and the number of mobile assignable trucks is the number of trucks waiting to be unloaded, in the process of being unloaded, and empty after being unloaded; based on the required number of trucks, the number of quickly assignable trucks and the number of mobile assignable trucks for the required path, and the set dynamic dispatch model, determines the trucks to be assigned to the required path. The embodiment of the present application can reduce the waiting time of electric shovels and trucks within the dispatch cycle, maximize the production efficiency of electric shovels and trucks, take into account the dynamic adaptive dispatching decisions of trucks in different dispatching scenarios such as vehicle-shovel balance and vehicle-shovel imbalance, and give full play to the vehicle-shovel efficiency of open-pit mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a flow chart of the dynamic truck dispatching method according to an embodiment of the present application;

[0032] Figure 2 This is a schematic diagram of the structure of the truck dynamic dispatching device according to an embodiment of the present application;

[0033] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] The present application will be described in further detail below with reference to the accompanying drawings and embodiments.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application pertains. The terms used herein in the specification of this application are for the purpose of describing specific embodiments only and are not intended to limit this application.

[0036] The embodiment of the present application provides a truck dynamic scheduling method, which can be applied to electronic devices with data processing capabilities, such as notebooks, desktop computers or servers, to achieve dynamic scheduling and allocation of trucks based on traffic flow planning in open-pit mines, such as Figure 1 As shown, the method includes:

[0037] Step 101: Determine the number of trucks required for a path requiring trucks based on the target freight flow rate and current freight flow rate of each path in the dynamic truck scheduling process. The freight flow rate is the freight flow per unit time on a path of unit length. The path requiring trucks is a path whose current freight flow rate is less than the target freight flow rate.

[0038] It should be noted that the electronic device can obtain dynamic truck scheduling. The traffic flow planning can include: the number of heavy trucks from the loading point to the corresponding unloading point, and the transportation routes of each heavy truck, and the number of empty trucks from the unloading point to the corresponding loading point, and the transportation routes of each empty truck. The electronic device can also determine the target cargo flow rate and current cargo flow rate of each path based on the traffic flow planning. If the current cargo flow rate of the path is lower than the target cargo flow rate, the path is a vehicle-required path. If the current cargo flow rate of the path is higher than or equal to the target cargo flow rate, the path is a vehicle-free path.

[0039] In some embodiments, the number of trucks required for a required path is determined based on the target cargo flow rate and the current cargo flow rate of each path in the dynamic truck scheduling, specifically as follows:

[0040]

[0041] in, It represents the number of trucks required from dispatch point i to shovel j. The function floor represents rounding towards negative infinity. represents the target cargo flow rate from dispatch point i to shovel j, represents the current cargo flow rate from dispatch point i to shovel j, represents the equivalent transport distance from dispatch point i to shovel j, and c represents the average load of the truck.

[0042] Here, the path equivalent distance lE may be a distance value obtained by correcting the spatial distance based on at least one of the road quality grade, road slope, road speed limit, and road turning radius. For example, the calculation formula for the path equivalent distance lE is as follows:

[0043] l E =k r k g k v k t l

[0044] Among them, k r Indicates the mine road quality correction coefficient;

[0045] k g Indicates the slope correction coefficient of the mine road;

[0046] k v Indicates the speed limit correction factor of the mine road;

[0047] k t Indicates the turning radius correction coefficient of the mine road;

[0048] l represents the spatial transportation distance of the mine road.

[0049] For example, the transportation road network of an open-pit mine can be roughly divided into three categories based on the road's service life: the first category is fixed roads, which are mainly used to connect mining sites, spoil dumps, and other industrial sites. Fixed roads have high quality requirements, relatively smooth road surfaces, and relatively fast truck operation speeds. The second category is semi-fixed roads, which are mainly used to access the various steps of the mining site and the spoil dump. As mining progresses, the roads are regularly updated. Semi-fixed roads have average quality requirements, average road smoothness, and average truck operation speeds. The third category is temporary roads, which are mainly used to connect blast piles, strip blast piles, and transport blast piles to semi-fixed roads. As mining progresses, the roads are dynamically updated. Temporary roads have low quality, uneven road surfaces, and low truck operation speeds. That is, the aforementioned road quality levels can include: a first quality level corresponding to fixed roads, a second quality level corresponding to semi-fixed roads, and a third quality level corresponding to temporary roads.

[0050] Step 102: Determine the number of quickly assignable trucks and the number of mobile assignable trucks for the required path based on the current status of each truck, wherein the current status is one of the following: waiting for loading, loading, re-shipping after loading, waiting for unloading, unloading, and empty transport after unloading. The number of quickly assignable trucks is the number of trucks waiting for unloading and unloading, and the number of mobile assignable trucks is the number of trucks waiting for unloading, unloading, and empty transport after unloading.

[0051] Step 103 : Determine the trucks to be assigned to the vehicle-demanding route based on the required number of trucks, the number of fast-assignable trucks, the number of fluid-assignable trucks, and the set dynamic scheduling model.

[0052] It can be understood that the method of the embodiment of the present application can reduce the waiting time of electric shovels and trucks during the scheduling cycle, maximize the production efficiency of electric shovels and trucks, take into account the dynamic adaptive scheduling decisions of trucks under different scheduling scenarios such as vehicle-shovel balance and vehicle-shovel imbalance, and give full play to the vehicle-shovel efficiency of open-pit mines.

[0053] In some embodiments, the forklift trucks assigned to the required path are determined based on the required number of trucks, the number of quickly assignable trucks, the number of fluidly assignable trucks, and a set dynamic scheduling model, as follows:

[0054]

[0055] Among them, s represents the assigned truck number, It represents the preparation time of forklift i when the truck is dispatched to the forklift i. It represents the preparation time of the truck when it is dispatched to forklift i, represents the number of trucks required for the required route, Indicates the number of trucks that can be quickly assigned, represents the number of trucks that can be assigned to the flow, t now Indicates the current scheduling time. Indicates the estimated air transport time from the dispatch point to the forklift. represents the target output of forklift i, t a Indicates the total duration of the scheduling cycle, represents the current output of forklift i, represents the number of trucks in the route being dispatched to forklift i.

[0056] The following is an illustrative example of the truck dynamic scheduling method in the embodiment of the present application.

[0057] In this application example, the basic situation during a scheduling cycle at an open-pit mine is as follows: there are 6 blasting piles for ore supply, 3 blasting piles for stripping, and 2 blasting piles for transporting, each loaded by 4 electric shovels and 7 cranes. The demand for both the first and second crushing stations is 40,000 tons. The total amount of blasting piles for stripping is 100,000 tons, and the total amount of blasting piles for transporting is 50,000 tons. The production capacity of the electric shovel is 25,000 tons / day, and the production capacity of the crane is 18,000 tons / day. The average loading time for the electric shovel is 5 minutes, the average loading time for the crane is 7 minutes, and the average unloading time for the truck is 2 minutes. The number of trucks transporting ore is 92, with an average deadweight and bulk density of 44.13 tons and 35 tons, respectively. The empty and loaded truck speeds are 36 km / h and 25 km / h, respectively. Table 1 shows the scheduling information for a specific mine scheduling cycle under the fixed truck-shovel allocation method.

[0058] Table 1 Statistical analysis of fixed shovel allocation scheduling information

[0059]

[0060] The truck scheduling efficiency after using the dynamic adaptive scheduling algorithm in the same scenario is shown in Table 2.

[0061] Table 2 Statistical analysis of dynamic adaptive scheduling information under the same scenario

[0062]

[0063]

[0064] The comparative results show that under the same scheduling scenario, the idle time of electric shovels and cranes and the waiting time of trucks are reduced after using the dynamic adaptive scheduling method, so that the total scheduling cycle time is shorter while completing the same output.

[0065] To further verify whether reducing the number of trucks in the same scenario can also complete the production task in the scheduling period, the number of trucks in the scenario is reduced by 3, and other parameters remain unchanged. The truck scheduling efficiency after using the dynamic adaptive scheduling algorithm in this scenario is shown in Table 3.

[0066] Table 3 Dynamic adaptive scheduling information statistical analysis under the scenario of reducing 3 trucks

[0067]

[0068] Statistical analysis shows that reducing 3 trucks in the same scenario can also complete the production task in the scheduling period, so the dynamic adaptive scheduling method provided by the patent can significantly improve the truck-shovel efficiency in the open-pit mine.

[0069] To implement the method of the embodiments of the present application, the embodiments of the present application further provide a truck dynamic scheduling device, which is arranged in an electronic device, such as a computer. Figure 2 As shown in the figure, the truck dynamic scheduling device comprises a first determination module 201, a second determination module 202, and a truck allocation module 203. The first determination module 201 is configured to determine the required number of trucks for a required path based on the target traffic rate and the current traffic rate of each path in the truck dynamic scheduling, wherein the traffic rate is the traffic volume per unit time on a unit length path, and the required path is a path with a current traffic rate less than the target traffic rate. The second determination module 202 is configured to determine the number of fast-acting allocable trucks and the number of flowing allocable trucks for the required path based on the current state of each truck, wherein the current state is one of the following: waiting for loading, loading, loading and retransporting, waiting for unloading, unloading, and unloading and emptying, the number of fast-acting allocable trucks is the number of trucks waiting for unloading and unloading, and the number of flowing allocable trucks is the number of trucks waiting for unloading, unloading, and unloading and emptying. The truck allocation module 203 is configured to determine the trucks allocated to the required path based on the required number of trucks for the required path, the number of fast-acting allocable trucks, the number of flowing allocable trucks, and a set dynamic scheduling model.

[0070] In some embodiments, the second determination module determines the required number of trucks for the required path based on the target traffic rate and the current traffic rate of each path in the truck dynamic scheduling, specifically as follows:

[0071]

[0072] wherein, represents the required number of trucks from the scheduling point i to the shovel j, the function floor represents rounding to negative infinity, represents the target traffic rate from the scheduling point i to the shovel j, represents the current traffic rate from the scheduling point i to the shovel j, represents the equivalent transport distance from dispatch point i to shovel j, and c represents the average load of the truck.

[0073] In some embodiments, the truck allocation module determines the forklift to be allocated to the required path based on the required number of trucks, the number of quickly allocable trucks, the number of fluidly allocable trucks, and a set dynamic scheduling model, as follows:

[0074]

[0075] Among them, s represents the assigned truck number, It represents the preparation time of forklift i when the truck is dispatched to the forklift i. It represents the preparation time of the truck when it is dispatched to forklift i, represents the number of trucks required for the required route, Indicates the number of trucks that can be quickly assigned, represents the number of trucks that can be assigned to the flow, t now Indicates the current scheduling time. Indicates the estimated air transport time from the dispatch point to the forklift. represents the target output of forklift i, t a Indicates the total duration of the scheduling cycle, represents the current output of forklift i, represents the number of trucks in the route being dispatched to forklift i.

[0076] In actual application, the first determination module 201, the second determination module 202 and the truck allocation module 203 can be implemented by a processor in an electronic device. Of course, the processor needs to run the computer program in the memory to implement its functions.

[0077] It should be noted that the dynamic truck dispatching device provided in the above embodiment is merely illustrated by the division of the aforementioned program modules when performing dynamic truck dispatching. In actual applications, the aforementioned processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the aforementioned processing. Furthermore, the dynamic truck dispatching device provided in the above embodiment and the dynamic truck dispatching method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0078] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present application, the embodiment of the present application also provides an electronic device. Figure 3 Only an exemplary structure of the electronic device is shown, not all structures, and it can be implemented as needed. Figure 3 Partial or complete structure shown.

[0079] like Figure 3As shown, the electronic device 300 provided in the embodiment of the present application includes: at least one processor 301, a memory 302, a user interface 303 and at least one network interface 304. The various components in the electronic device 300 are coupled together through a bus system 305. It can be understood that the bus system 305 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 305 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 3 Various buses are labeled as bus system 305 .

[0080] The user interface 303 may include a display, a keyboard, a mouse, a trackball, a click wheel, keys, buttons, a touch pad or a touch screen.

[0081] The memory 302 in the embodiment of the present application is used to store various types of data to support the operation of the electronic device. Examples of such data include: any computer program used to operate on the electronic device.

[0082] The truck dynamic scheduling method disclosed in the embodiments of the present application can be applied to or implemented by processor 301. Processor 301 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the truck dynamic scheduling method can be completed by hardware integrated logic circuits in processor 301 or software instructions. The above-mentioned processor 301 can be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 301 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be directly implemented as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium located in memory 302. Processor 301 reads the information in memory 302 and, in combination with its hardware, completes the steps of the truck dynamic scheduling method provided in the embodiments of the present application.

[0083] In an exemplary embodiment, the electronic device may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0084] It can be understood that the memory 302 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a ferromagnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM) used as an external cache. By way of example but not limitation, many forms of RAM can be used, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0085] In an exemplary embodiment, the present application also provides a storage medium, namely, a computer storage medium, which may be a computer-readable storage medium, for example, including a memory 302 storing a computer program. The computer program may be executed by a processor 301 of an electronic device to complete the steps of the method described in the embodiment of the present application. The computer-readable storage medium may be a memory such as a ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, or CD-ROM.

[0086] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0087] In addition, the technical solutions described in the embodiments of the present application can be arbitrarily combined without conflict.

[0088] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A truck dynamic dispatching method, characterized in that: include: Determine the number of trucks required for a route requiring trucks based on the target and current freight flow rates of each route in the dynamic truck scheduling process. The freight flow rate is the amount of freight carried per unit time on a route of unit length. A route requiring trucks is one where the current freight flow rate is less than the target freight flow rate. Determine the number of quickly assignable trucks and the number of fluidly assignable trucks for the required vehicle route based on the current status of each truck, wherein the current status is one of the following: waiting for loading, loading, re-shipping after loading, waiting for unloading, unloading, and empty shipment after unloading; the number of quickly assignable trucks is the number of trucks waiting for unloading and unloading, and the number of fluidly assignable trucks is the number of trucks waiting for unloading, unloading, and empty shipment after unloading; Determining the trucks to be assigned to the vehicle-demanding route based on the required number of trucks, the number of quickly assignable trucks, the number of fluidly assignable trucks, and a set dynamic scheduling model; The forklift trucks assigned to the required path are determined based on the required number of trucks, the number of fast-allocable trucks, the number of mobile-allocable trucks, and the set dynamic scheduling model, as follows: Among them, s represents the assigned truck number, It represents the preparation time of forklift i when the truck is dispatched to the forklift i. It represents the preparation time of the truck when it is dispatched to forklift i, represents the number of trucks required for the required route, Indicates the number of trucks that can be quickly assigned, represents the number of trucks that can be assigned to the flow, t now Indicates the current scheduling time. Indicates the estimated air transport time from the dispatch point to the forklift. represents the target output of forklift i, t a Indicates the total duration of the scheduling cycle, represents the current output of forklift i, represents the number of trucks in the route being dispatched to forklift i.

2. The method according to claim 1, characterized in that The number of trucks required for the required path is determined based on the target cargo flow rate and current cargo flow rate of each path in the dynamic truck scheduling, as follows: in, It represents the number of trucks required from dispatch point i to shovel j. The function floor represents rounding towards negative infinity. represents the target cargo flow rate from dispatch point i to shovel j, represents the current cargo flow rate from dispatch point i to shovel j, represents the equivalent transport distance from dispatch point i to shovel j, and c represents the average load of the truck.

3. A truck dynamic dispatching device, characterized in that: include: A first determination module is configured to determine the number of trucks required for a vehicle-requiring route based on a target cargo flow rate and a current cargo flow rate for each route in the dynamic truck scheduling, wherein the cargo flow rate is the cargo flow per unit time on a route of unit length, and the vehicle-requiring route is a route whose current cargo flow rate is less than the target cargo flow rate; a second determining module, configured to determine the number of quickly assignable trucks and the number of fluidly assignable trucks for the required vehicle route based on the current status of each truck, wherein the current status is one of the following: waiting for loading, loading, re-shipping after loading, waiting for unloading, unloading, and empty transport after unloading; the number of quickly assignable trucks is the number of trucks waiting for unloading and unloading, and the number of fluidly assignable trucks is the number of trucks waiting for unloading, unloading, and empty transport after unloading; A truck allocation module, configured to determine the trucks allocated to the vehicle-demanding route based on the required number of trucks for the vehicle-demanding route, the number of quickly allocable trucks, the number of fluidly allocable trucks, and a set dynamic scheduling model; The truck allocation module determines the forklift to be allocated to the required path based on the required number of trucks, the number of fast-allocatable trucks, the number of fluid-allocatable trucks, and the set dynamic scheduling model, as follows: Among them, s represents the assigned truck number, It represents the preparation time of forklift i when the truck is dispatched to the forklift i. It represents the preparation time of the truck when it is dispatched to forklift i, represents the number of trucks required for the required route, Indicates the number of trucks that can be quickly assigned, represents the number of trucks that can be assigned to the flow, t now Indicates the current scheduling time. Indicates the estimated air transport time from the dispatch point to the forklift. represents the target output of forklift i, t a Indicates the total duration of the scheduling cycle, represents the current output of forklift i, represents the number of trucks in the route being dispatched to forklift i.

4. The device according to claim 3, characterized in that The second determination module determines the number of trucks required for the required path based on the target cargo flow rate and the current cargo flow rate of each path in the dynamic truck scheduling, as follows: in, It represents the number of trucks required from dispatch point i to shovel j. The function floor represents rounding towards negative infinity. represents the target cargo flow rate from dispatch point i to shovel j, represents the current cargo flow rate from dispatch point i to shovel j, represents the equivalent transport distance from dispatch point i to shovel j, and c represents the average load of the truck.

5. An electronic device, characterized in that: include: A processor and a memory for storing a computer program capable of being executed on the processor, wherein The processor is configured to execute the steps of the method according to any one of claims 1 to 2 when running a computer program.

6. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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