Multi-guided vehicle scheduling method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of guided vehicle operation scheduling, in particular to a multi-guided vehicle scheduling method and device, electronic equipment and a storage medium. Then constructing a plurality of route timetable equations starting from a plurality of standby positions, advancing along grid points, passing through a material warehouse and finally arriving at a material level; then, according to a total operation time table, the multiple material level unoccupied quantities and the multiple material level consumption rates, route time table constraint conditions and multiple material level deadline moment constraint conditions are constructed respectively; and finally, optimizing the plurality of route timetable equations by taking the shortest total consumed time as a target, and determining a scheduling strategy of the plurality of standby guide vehicles according to an optimization result. According to the embodiment of the invention, the route time equation is set based on the grid points where the guide vehicles travel, the route groups are generated and input into the equation, the route groups are optimized, and the purposes of multi-pull fast running and efficient transportation of the guide vehicles are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of guided vehicle operation scheduling, and in particular to a multi-guided vehicle scheduling method, device, electronic equipment and storage medium. Background Art

[0002] AGV is the abbreviation of Automated Guided Vehicle, which refers to an unmanned automated vehicle with automatic guidance equipment such as magnetic strips, tracks or lasers, which travels along a planned path, is powered by batteries, and is equipped with safety protection and various auxiliary mechanisms (such as transfer and assembly mechanisms).

[0003] Usually, multiple AGVs, a control computer (console), navigation equipment, charging equipment and peripheral accessories form an AGV system. Its main working principle is that under the monitoring and task scheduling of the control computer, the AGV can accurately walk along the specified path, and after reaching the specified location of the task, it can complete a series of work tasks. The control computer can decide whether to go to the charging area for automatic charging based on the AGV's own power.

[0004] One guided vehicle scheduling strategy is to move according to the grid points set on the road surface. The scheduling strategy is to avoid any two guided vehicles appearing at the same grid point in the same time period. This scheduling strategy avoids collisions between guided vehicles. However, in order to avoid collisions between guided vehicles, a waiting time is usually set in the scheduling strategy, and the maximum carrying capacity of the guided vehicle is usually not fully utilized.

[0005] Based on this, it is necessary to develop and design a multi-guided vehicle scheduling method. Summary of the invention

[0006] The embodiments of the present invention provide a multi-guided vehicle scheduling method, device, electronic device and storage medium, which are used to solve the problem in the prior art that the comprehensive carrying capacity of the scheduling strategy of the guided vehicle based on grid point operation needs to be improved.

[0007] In a first aspect, an embodiment of the present invention provides a multi-guided vehicle scheduling method, comprising:

[0008] Obtain multiple material level margins, wherein each material level margin corresponds to a material level;

[0009] Construct multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through material warehouses to finally reach material positions, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle;

[0010] According to the total operation schedule, the plurality of material level margins and the plurality of material level consumption rates, respectively constructing a route schedule constraint condition and a plurality of material level absolute time constraint conditions, wherein each material level consumption rate and each material level absolute time constraint condition respectively corresponds to a material level;

[0011] The multiple route schedule equations are optimized with the goal of minimizing the total time consumption, and the scheduling strategies for the multiple standby guided vehicles are determined according to the optimization results, wherein the total time consumption represents the total operating time of the multiple standby guided vehicles.

[0012] In a possible implementation, the construction of multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through material warehouses to finally reach material positions includes:

[0013] Acquire a plurality of target material levels and a plurality of material warehouses, wherein each target material level corresponds to a material warehouse, and the number of the plurality of target material levels is the same as the number of the plurality of standby positions;

[0014] Determining a plurality of minimum transit times according to the material level margins corresponding to the plurality of target material levels;

[0015] Determine a plurality of routes according to the positions of the plurality of target material levels, the positions of the plurality of material depots and the plurality of standby positions, wherein the routes start from the standby position, pass through the material depot and end at the target material level, and the routes are arranged along grid points;

[0016] The multiple route schedule equations are constructed based on the multiple routes, the travel speed of the guide vehicle, the turning speed of the guide vehicle and the multiple minimum transit times.

[0017] In one possible implementation, the route schedule equation is:

[0018]

[0019] Where, t(n) AI is the arrival time of the nth grid point, t(n-1) LO is the departure time of the n-1th grid point, w a is the first constant, w a is a positive value less than 1, D is the distance between two adjacent grid points, v is the speed of the guide vehicle, t(n) LO is the departure time of the nth grid point, w l is the second constant, w l is a positive value less than 1, t turn is the turning time. When the nth grid point is a non-turning point, t turn is zero, t Loadis the length of time spent in the material warehouse. When the nth grid point is not a grid point in the material warehouse, t turn is zero, t LDLimited The minimum transit time.

[0020] In a possible implementation, constructing a route schedule constraint condition according to the total operation schedule includes:

[0021] The route schedule constraint condition is constructed according to the first formula and the total operation schedule, wherein the first formula is:

[0022]

[0023] Where, t(n) A , is the arrival time of the nth grid point in the route schedule, t(n) LO is the arrival time of the nth grid point in the route schedule, position(n) is the position of the nth grid point in the route schedule, is the arrival time of the i-th grid point corresponding to the position in the total operation schedule, is the departure time of the i-th grid point corresponding to the position in the total running schedule, and | | is an OR operation.

[0024] In a possible implementation, multiple material level absolute time constraints are constructed according to the multiple material level margins and multiple material level consumption rates, including:

[0025] A plurality of material level absolute time constraints are constructed according to the second formula, the plurality of material level margins and the plurality of material level consumption rates, wherein the second formula is:

[0026]

[0027] In the formula, is the arrival time of the Nth grid point in the kth route schedule, is the arrival time of the first grid point in the kth route schedule, t Skd is the scheduling duration constant, is the material level vacancy corresponding to the kth route, is the material consumption rate of the material level corresponding to the k-th route, and N is the total number of grid points passed in the k-th route schedule.

[0028] In a possible implementation, the multiple route schedule equations are optimized with the shortest total time as the goal, and the scheduling strategies of the multiple standby guided vehicles are determined according to the optimization results, including:

[0029] Randomly generate a plurality of route groups, wherein each route group includes a plurality of first routes, and each first route corresponds to a standby position;

[0030] Substituting the multiple route groups into the target equation group respectively to obtain multiple total durations, wherein each total duration corresponds to a route group, and the target equation group is an equation group constructed according to the route schedule constraint condition, the multiple material level absolute time constraint conditions and the multiple route schedule equations;

[0031] Extracting the shortest duration from the multiple total durations as a reference duration;

[0032] Determine a drop rate according to the reference duration and the shortest duration obtained in the previous iteration, and add the drop rate to a drop rate queue;

[0033] If the multiple descent rates newly added to the descent rate queue are all lower than the threshold, the route group corresponding to the reference duration is used as the optimal route group, and the scheduling strategy of multiple standby guided vehicles is determined according to the optimal route group;

[0034] Otherwise, multiple route groups corresponding to the shortest durations are extracted from the multiple total durations as multiple target route groups, and the other multiple route groups are adjusted according to the multiple target route groups, and the process jumps to the step of substituting the multiple route groups into the target equation group respectively to obtain multiple total durations.

[0035] In a possible implementation, determining the drop rate according to the reference duration and the shortest duration obtained in the previous iteration includes:

[0036] The drop rate is determined according to the third formula, the reference duration and the shortest duration obtained in the previous iteration, wherein the third formula is:

[0037]

[0038] Where DR is the decline rate, For reference duration, Get the shortest duration for the previous iteration.

[0039] In a second aspect, an embodiment of the present invention provides a multi-guided vehicle scheduling device, which is used to implement the multi-guided vehicle scheduling method described in the first aspect or any possible implementation of the first aspect, and the multi-guided vehicle scheduling device includes:

[0040] The material level statistics module is used to obtain the free space of multiple material levels, where each material level free space corresponds to a material level;

[0041] A schedule generation equation construction module is used to construct multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through the material warehouse to finally reach the material position, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle;

[0042] A constraint condition construction module, used to construct a route schedule constraint condition and a plurality of material level absolute time constraint conditions according to the total operation schedule, the plurality of material level vacancies and the plurality of material level consumption rates, wherein each material level consumption rate and each material level absolute time constraint condition respectively corresponds to a material level;

[0043] as well as,

[0044] The scheduling strategy determination module is used to optimize the multiple route schedule equations with the goal of minimizing the total time consumption and determining the scheduling strategies of the multiple standby guided vehicles based on the optimization results, wherein the total time consumption represents the total operating time of the multiple standby guided vehicles.

[0045] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the steps of the method described in the first aspect or any possible implementation method of the first aspect.

[0046] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect or any possible implementation of the first aspect are implemented.

[0047] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0048] The embodiment of the present invention discloses a multi-guide vehicle scheduling method, which first obtains multiple material level vacancies, wherein each material level vacancies corresponds to a material level; then constructs multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through material storage to finally arrive at the material level, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle; then, according to the total operation schedule, the multiple material level vacancies and the multiple material level consumption rates, respectively constructs route schedule constraints and multiple material level absolute time constraints, wherein each material level consumption rate and each material level absolute time constraint respectively corresponds to a material level; finally, with the goal of minimizing the total time consumption, the multiple route schedule equations are optimized, and the scheduling strategy of the multiple standby guide vehicles is determined according to the optimization results, wherein the total time consumption represents the total operation time of the multiple standby guide vehicles. The implementation manner of the present invention sets a route time equation based on the grid points where the guide vehicles are traveling, and sets constraints on the time of arrival at the grid points and the absolute time constraints for the routes. Based on the above equations and constraints, the implementation manner of the present invention generates multiple route groups and inputs them into the equations, finds the optimal route group and adjusts other route groups according to the optimal route group, thereby optimizing the route groups and achieving the purpose of multiple guide vehicles carrying more and running faster and efficient transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 is a flow chart of a multi-guided vehicle scheduling method provided by an embodiment of the present invention;

[0051] Figure 2 This is an application scenario diagram of the guided vehicle route planning method provided by an embodiment of the present invention;

[0052] Figure 3 It is a schematic diagram of a route schedule planning method provided by an embodiment of the present invention;

[0053] Figure 4 It is a functional block diagram of a multi-guided vehicle dispatching device provided by an embodiment of the present invention;

[0054] Figure 5 It is a functional block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present invention with unnecessary details.

[0056] In order to make the purpose, technical solutions and advantages of the present invention more clear, a specific implementation method will be described below in conjunction with the accompanying drawings.

[0057] The following is a detailed description of an embodiment of the present invention. This example is implemented based on the technical solution of the present invention, and provides a detailed implementation method and a specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0058] Figure 1 A flowchart of a multi-guided vehicle scheduling method provided in an embodiment of the present invention.

[0059] like Figure 1 As shown, it shows a flowchart of the implementation of the multi-guided vehicle scheduling method provided by an embodiment of the present invention, which is described in detail as follows:

[0060] In step 101, a plurality of material level margins are obtained, wherein each material level margin corresponds to a material level.

[0061] In step 102, multiple route schedule equations are constructed starting from multiple standby positions, traveling along grid points and passing through the material warehouse to finally reach the material position, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle.

[0062] In some implementations, step 102 includes:

[0063] Acquire a plurality of target material levels and a plurality of material warehouses, wherein each target material level corresponds to a material warehouse, and the number of the plurality of target material levels is the same as the number of the plurality of standby positions;

[0064] Determining a plurality of minimum transit times according to the material level margins corresponding to the plurality of target material levels;

[0065] Determine a plurality of routes according to the positions of the plurality of target material levels, the positions of the plurality of material depots and the plurality of standby positions, wherein the routes start from the standby position, pass through the material depot and end at the target material level, and the routes are arranged along grid points;

[0066] The multiple route schedule equations are constructed based on the multiple routes, the travel speed of the guide vehicle, the turning speed of the guide vehicle and the multiple minimum transit times.

[0067] In some implementations, the route schedule equation is:

[0068]

[0069] Where, t(n) AI is the arrival time of the nth grid point, t(n-1) LO is the departure time of the n-1th grid point, w a is the first constant, w a is a positive value less than 1, D is the distance between two adjacent grid points, v is the speed of the guide vehicle, t(n) LO is the departure time of the nth grid point, w l is the second constant, w l is a positive value less than 1, t turn is the turning time. When the nth grid point is a non-turning point, t turn is zero, t Load is the length of time spent in the material warehouse. When the nth grid point is not a grid point in the material warehouse, t turn is zero, t LDLimited The minimum transit time.

[0070] Exemplarily, the embodiment of the present invention is based on a route schedule equation constructed based on route planning.

[0071] like Figure 2 As shown, after the available quantity of material level 201 is obtained and arranged, each time the route is planned, the issuing position 202 of the required material of the material level 201 with the highest priority is always extracted from the available quantity arrangement, and the position of the guide vehicle closest to the issuing position 202 and in a waiting state, that is, the waiting position 203, is found.

[0072] In one application scenario, the speed of each guide vehicle during normal travel is configured as a speed, that is, a moving speed. The guide vehicle moves according to the point 204 set on the ground. For example, a guide vehicle guided by a QR code has a QR code label at the point 204. When the guide vehicle moves above the QR code, the position of the current point 204 can be known by scanning the QR code. These points 204 are arranged in a rectangular array. The time when the guide vehicle approaches and leaves the point 204 at a certain distance is the time period when the guide vehicle occupies the point 204. Other guide vehicles must not approach, otherwise a collision will occur. Generally, the time taken to occupy a circle with a preset radius with the point 204 as the center is taken as the passing time. Since the speeds are different when passing in a straight line and passing in a turn, the straight line passing time and the turning passing time can be determined by the moving speed, respectively. In addition, in order to obtain a route schedule, it is also necessary to obtain the material acceptance time, which includes the time from the guide vehicle arriving at the material issuing position 202 to the guide vehicle completing the material acceptance and leaving the material issuing position 202.

[0073] In planning the travel route of the guide vehicle, the embodiment of the present invention first plans a rectangle based on the starting point and the target point of the guide vehicle, wherein, when the guide vehicle moves from the waiting position 203 to the material issuing position 202, the waiting position 203 is used as the starting point and the material issuing position 202 is used as the target point; when moving from the material issuing position 202 to the material level 201, the material issuing position 202 is used as the starting point and the material level 201 is used as the target point. Figure 2 What is shown in FIG. 2 is a second rectangle 205 planned with the material sending position 202 and the material level 201 as vertices when moving from the material sending position 202 to the material level 201 . The route of the guide vehicle should be within this rectangle.

[0074] The main factor affecting the travel speed of the guided vehicle is the number of turns of the guided vehicle. Therefore, the embodiments of the present invention always try to complete the planning of the travel route of the guided vehicle under the premise of reducing the number of turns as much as possible and avoiding schedule conflicts.

[0075] Based on the number of turns, the embodiment of the present invention sets some waypoints. Generally speaking, the number of waypoints is obtained by subtracting one from the number of turns. In terms of setting the waypoints, the embodiment of the present invention sets the waypoints based on the relative orientation of the starting point and the target point, with the starting point as the reference. Each waypoint is on one side of the moving direction toward the target point relative to the previous waypoint. Figure 2For example, if the target point is on the right and upper side relative to the starting point, then when setting each waypoint 206, it is necessary to set it on the right and upper side of the previous waypoint 206. The advantage of such setting is that it can reduce the detour of the path, improve the efficiency of the passage, and save time. Those skilled in the art can know from the above discussion that following the above principles, there can be multiple combinations of waypoint settings. The embodiments of the present invention organize these combinations into waypoint combinations, and then plan the route based on these waypoint combinations.

[0076] In terms of route planning, the embodiment of the present invention sets rectangles between two waypoints with the two waypoints as vertices, and the sides of these rectangles are the path lines of the selectable paths. Figure 3 As shown, one feasible way is to select the common edge of two adjacent third rectangles 207 as the pass route. Through analysis, it can be seen that based on these adjacent third rectangles 207, there are two feasible routes that meet the number of turns. In other words, each combination of waypoints can obtain two feasible path solutions. Figure 3 A feasible path scheme is shown along the arrow direction.

[0077] Based on these feasible route plans, the occupied time periods can be allocated to the points passed by the route plan according to the previously determined transit time, turning time, straight line time and departure time node. In one application scenario, the route schedule is determined based on the route schedule equation:

[0078]

[0079] Where, t(n) AI is the arrival time of the nth grid point, t(n-1) LO is the departure time of the n-1th grid point, w a is the first constant, w a is a positive value less than 1, D is the distance between two adjacent grid points, v is the speed of the guide vehicle, t(n) LO is the departure time of the nth grid point, w l is the second constant, w l is a positive value less than 1, t turn is the turning time. When the nth grid point is a non-turning point, t turn is zero, t Load is the length of time spent in the material warehouse. When the nth grid point is not a grid point in the material warehouse, t turn is zero, t LDLimited The minimum transit time.

[0080] like Figure 3As shown, the duration of each route is T1, the duration of the turn is T2, and the duration of the straight line is T3. In this way, combined with the time node at departure, a temporary route timetable is obtained.

[0081] In step 103, route schedule constraints and multiple material level absolute time constraints are constructed according to the total operation schedule, the multiple material level vacancies, and the multiple material level consumption rates, wherein each material level consumption rate and each material level absolute time constraint corresponds to a material level.

[0082] In some implementations, constructing a route schedule constraint condition based on the total operation schedule includes:

[0083] The route schedule constraint condition is constructed according to the first formula and the total operation schedule, wherein the first formula is:

[0084]

[0085] Where, t(n) A , is the arrival time of the nth grid point in the route schedule, t(n) LO is the arrival time of the nth grid point in the route schedule, position(n) is the position of the nth grid point in the route schedule, is the arrival time of the i-th grid point corresponding to the position in the total operation schedule, is the departure time of the i-th grid point corresponding to the position in the total running schedule, and | | is an OR operation.

[0086] In some embodiments, the multiple material level absolute time constraints are constructed according to the multiple material level margins and the multiple material level consumption rates, including:

[0087] A plurality of material level absolute time constraints are constructed according to the second formula, the plurality of material level margins and the plurality of material level consumption rates, wherein the second formula is:

[0088]

[0089] In the formula, is the arrival time of the Nth grid point in the kth route schedule, is the arrival time of the first grid point in the kth route schedule, t Skd is the scheduling duration constant, is the material level vacancy corresponding to the kth route, is the material consumption rate of the material level corresponding to the k-th route, and N is the total number of grid points passed in the k-th route schedule.

[0090] Exemplarily, in order to prevent collision and material shortage, the embodiment of the present invention sets a route schedule constraint and a material level absolute time constraint, wherein the route schedule constraint is determined according to the first formula:

[0091]

[0092] Where, t(n) A , is the arrival time of the nth grid point in the route schedule, t(n) LO is the arrival time of the nth grid point in the route schedule, position(n) is the position of the nth grid point in the route schedule, is the arrival time of the i-th grid point corresponding to the position in the total operation schedule, is the departure time of the i-th grid point corresponding to the position in the total running schedule, and | | is an OR operation.

[0093] The material level absolute time constraint condition is determined according to the second formula:

[0094]

[0095] In the formula, is the arrival time of the Nth grid point in the kth route schedule, is the arrival time of the first grid point in the kth route schedule, t Skd is the scheduling duration constant, is the material level vacancy corresponding to the kth route, is the material consumption rate of the material level corresponding to the k-th route, and N is the total number of grid points passed in the k-th route schedule.

[0096] In step 104, the multiple route schedule equations are optimized with the goal of minimizing the total time consumption, and the scheduling strategies for the multiple standby guided vehicles are determined based on the optimization results, wherein the total time consumption represents the total operating time of the multiple standby guided vehicles.

[0097] In some implementations, step 104 includes:

[0098] Randomly generate a plurality of route groups, wherein each route group includes a plurality of first routes, and each first route corresponds to a standby position;

[0099] Substituting the multiple route groups into the target equation group respectively to obtain multiple total durations, wherein each total duration corresponds to a route group, and the target equation group is an equation group constructed according to the route schedule constraint condition, the multiple material level absolute time constraint conditions and the multiple route schedule equations;

[0100] Extracting the shortest duration from the multiple total durations as a reference duration;

[0101] Determine a drop rate according to the reference duration and the shortest duration obtained in the previous iteration, and add the drop rate to a drop rate queue;

[0102] If the multiple descent rates newly added to the descent rate queue are all lower than the threshold, the route group corresponding to the reference duration is used as the optimal route group, and the scheduling strategy of multiple standby guided vehicles is determined according to the optimal route group;

[0103] Otherwise, multiple route groups corresponding to the shortest durations are extracted from the multiple total durations as multiple target route groups, and the other multiple route groups are adjusted according to the multiple target route groups, and the process jumps to the step of substituting the multiple route groups into the target equation group respectively to obtain multiple total durations.

[0104] In some implementations, determining the drop rate according to the reference duration and the shortest duration obtained in the previous iteration includes:

[0105] The drop rate is determined according to the third formula, the reference duration and the shortest duration obtained in the previous iteration, wherein the third formula is:

[0106]

[0107] Where DR is the decline rate, For reference duration, Get the shortest duration for the previous iteration.

[0108] Exemplarily, in terms of scheduling strategy, an implementation of the present invention is to set up multiple route groups, each route group includes multiple routes, and each route corresponds to a standby position, that is, each route group is a combination of multiple routes set with multiple standby positions as starting points.

[0109] Input these route groups into the target equation group to obtain multiple total durations (some routes in the route group that do not meet the constraints will be eliminated and not included in the total duration), find the shortest duration from the multiple total durations, and determine the iterative decline rate according to the third formula, which is:

[0110]

[0111] Where DR is the decline rate, For reference duration, Get the shortest duration for the previous iteration.

[0112] The descent rate is added to the descent rate queue. If the descent rates of multiple newly added routes (for example, five) in the descent queue are always lower than the predetermined level, it means that the optimization limit is approaching. At this time, the timetable of the route group corresponding to the shortest duration is added to the existing timetable, and multiple guided vehicles are scheduled according to the timetable.

[0113] If the above conditions are not met, the optimal multiple route groups (the multiple route groups with the shortest total time) are selected from the multiple route groups, and the other route groups are adjusted according to the multiple route groups and substituted into the target equation group, and the iteration is repeated until the above conditions are met.

[0114] The implementation method of the multi-guide vehicle scheduling method of the present invention first obtains multiple material level vacancies, wherein each material level vacancies corresponds to a material level; then constructs multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through material storage to finally arrive at the material level, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle; then, according to the total operation schedule, the multiple material level vacancies and the multiple material level consumption rates, respectively constructs route schedule constraints and multiple material level absolute time constraints, wherein each material level consumption rate and each material level absolute time constraint respectively corresponds to a material level; finally, with the goal of minimizing the total time consumption, the multiple route schedule equations are optimized, and the scheduling strategy of the multiple standby guide vehicles is determined according to the optimization results, wherein the total time consumption represents the total operation time of the multiple standby guide vehicles. The implementation manner of the present invention sets a route time equation based on the grid points where the guide vehicles are traveling, and sets constraints on the time of arrival at the grid points and the absolute time constraints for the routes. Based on the above equations and constraints, the implementation manner of the present invention generates multiple route groups and inputs them into the equations, finds the optimal route group and adjusts other route groups according to the optimal route group, thereby optimizing the route groups and achieving the purpose of multiple guide vehicles carrying more and running faster and efficient transportation.

[0115] It should be understood that the size of the serial numbers of the steps in the above implementation does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation method of the present invention.

[0116] The following is an implementation of the device of the present invention. For details not described in detail, reference may be made to the corresponding method implementation described above.

[0117] Figure 4 is a functional block diagram of a multi-guided vehicle dispatching device provided by an embodiment of the present invention, referring to Figure 4 The multi-guide vehicle dispatching device includes: a material level statistics module 401, a schedule generation equation construction module 402, a constraint condition construction module 403 and a dispatching strategy determination module 404, wherein:

[0118] The material level statistics module 401 is used to obtain a plurality of material level vacancies, wherein each material level vacancies corresponds to a material level;

[0119] The schedule generation equation construction module 402 is used to construct multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through the material warehouse to finally reach the material position, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle;

[0120] The constraint condition construction module 403 is used to construct a route schedule constraint condition and a plurality of material level absolute time constraint conditions according to the total operation schedule, the plurality of material level vacancies and the plurality of material level consumption rates, wherein each material level consumption rate and each material level absolute time constraint condition respectively corresponds to a material level;

[0121] The scheduling strategy determination module 404 is used to optimize the multiple route schedule equations with the goal of minimizing the total time consumption and determining the scheduling strategies of the multiple standby guide vehicles based on the optimization results, wherein the total time consumption represents the total operating time of the multiple standby guide vehicles.

[0122] Figure 4 is a functional block diagram of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 400 and a memory 401, wherein the memory 401 stores a computer program 402 that can be run on the processor 400. When the processor 400 executes the computer program 402, the steps in the above-mentioned multi-guided vehicle scheduling method and the embodiment are implemented, for example Figure 1 Steps 101 to 104 are shown.

[0123] Exemplarily, the computer program 402 may be divided into one or more modules / units, and the one or more modules / units are stored in the memory 401 and executed by the processor 400 to implement the present invention.

[0124] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 4 may include, but is not limited to, a processor 400 and a memory 401. Those skilled in the art will appreciate that Figure 4 It is only an example of the electronic device 4 and does not constitute a limitation of the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device 4 may also include input and output devices, network access devices, buses, etc.

[0125] The processor 400 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0126] The memory 401 may be an internal storage unit of the electronic device 4, such as a hard disk or memory of the electronic device 4. The memory 401 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. Further, the memory 401 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 401 is used to store the computer program 402 and other programs and data required by the electronic device 4. The memory 401 may also be used to temporarily store data that has been output or is to be output.

[0127] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the implementation method can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method implementation method, which will not be repeated here.

[0128] In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0129] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0130] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0131] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0132] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0133] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned implementation method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various methods and device implementation methods. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium.

[0134] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A multi-guided vehicle dispatching method, characterized in that: include: Obtain multiple material level margins, wherein each material level margin corresponds to a material level; Construct multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through material warehouses to finally reach material positions, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle; According to the total operation schedule, the plurality of material level margins and the plurality of material level consumption rates, respectively constructing a route schedule constraint condition and a plurality of material level absolute time constraint conditions, wherein each material level consumption rate and each material level absolute time constraint condition respectively corresponds to a material level; The multiple route schedule equations are optimized with the goal of minimizing the total time consumption, and the scheduling strategies for the multiple standby guided vehicles are determined according to the optimization results, wherein the total time consumption represents the total operating time of the multiple standby guided vehicles.

2. The multi-guided vehicle dispatching method according to claim 1, characterized in that: The construction of multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through material warehouses to finally reach material positions includes: Acquire multiple target material levels and multiple material warehouses, wherein each target material level corresponds to a material warehouse, and the number of the multiple target material levels is the same as the number of the multiple standby positions; Determining a plurality of minimum transit times according to the material level margins corresponding to the plurality of target material levels; Determine a plurality of routes according to the positions of the plurality of target material levels, the positions of the plurality of material depots and the plurality of standby positions, wherein the routes start at the standby position, pass through the material depot and end at the target material level, and the routes are arranged along the grid points; The multiple route schedule equations are constructed based on the multiple routes, the travel speed of the guide vehicle, the turning speed of the guide vehicle and the multiple minimum transit times.

3. The multi-guided vehicle dispatching method according to claim 2, characterized in that: The route schedule equation is: Where, t(n) AI is the arrival time of the nth grid point, t(n-1) LO is the departure time of the n-1th grid point, w a is the first constant, w a is a positive value less than 1, D is the distance between two adjacent grid points, v is the speed of the guide vehicle, t(n) LO is the departure time of the nth grid point, w l is the second constant, w l is a positive value less than 1, t turn is the turning time. When the nth grid point is a non-turning point, t turn is zero, t Load is the length of time spent in the material warehouse. When the nth grid point is not a grid point in the material warehouse, t turn is zero, t LDLimited The minimum transit time.

4. The multi-guided vehicle dispatching method according to claim 1, characterized in that: Constructing route schedule constraints according to the total operation schedule includes: The route schedule constraint condition is constructed according to the first formula and the total operation schedule, wherein the first formula is: Where, t(n) AI is the arrival time of the nth grid point in the route schedule, t(n) LO is the arrival time of the nth grid point in the route schedule, position(n) is the position of the nth grid point in the route schedule, is the arrival time of the i-th grid point corresponding to the position in the total operation schedule, is the departure time of the i-th grid point corresponding to the position in the total running schedule, and || is an OR operation.

5. The multi-guided vehicle dispatching method according to claim 1, characterized in that: According to the plurality of material level margins and the plurality of material level consumption rates, a plurality of material level absolute time constraints are constructed, including A plurality of material level absolute time constraints are constructed according to the second formula, the plurality of material level margins and the plurality of material level consumption rates, wherein the second formula is: In the formula, is the arrival time of the Nth grid point in the kth route schedule, is the arrival time of the first grid point in the kth route schedule, t Skd is the scheduling duration constant, is the material level vacancy corresponding to the kth route, is the material consumption rate of the material level corresponding to the k-th route, and N is the total number of grid points passed in the k-th route schedule.

6. The multi-guided vehicle dispatching method according to any one of claims 1 to 5, characterized in that: The method of optimizing the multiple route schedule equations with the goal of minimizing the total time consumption and determining the scheduling strategies of the multiple standby guided vehicles according to the optimization results includes: Randomly generate a plurality of route groups, wherein each route group includes a plurality of first routes, and each first route corresponds to a standby position; Substituting the multiple route groups into the target equation group respectively to obtain multiple total durations, wherein each total duration corresponds to a route group, and the target equation group is an equation group constructed according to the route schedule constraint condition, the multiple material level absolute time constraint conditions and the multiple route schedule equations; Extracting the shortest duration from the multiple total durations as a reference duration; Determine a drop rate according to the reference duration and the shortest duration obtained in the previous iteration, and add the drop rate to a drop rate queue; If the multiple descent rates newly added to the descent rate queue are all lower than the threshold, the route group corresponding to the reference duration is used as the optimal route group, and the scheduling strategy of multiple standby guided vehicles is determined according to the optimal route group; Otherwise, multiple route groups corresponding to the shortest durations are extracted from the multiple total durations as multiple target route groups, and the other multiple route groups are adjusted according to the multiple target route groups, and the process jumps to the step of substituting the multiple route groups into the target equation group respectively to obtain multiple total durations.

7. The multi-guided vehicle dispatching method according to claim 6, characterized in that: The step of determining the drop rate according to the reference duration and the shortest duration obtained in the previous iteration includes: The drop rate is determined according to the third formula, the reference duration and the shortest duration obtained in the previous iteration, wherein the third formula is: Where DR is the decline rate, For reference duration, Get the shortest duration for the previous iteration.

8. A multi-guided vehicle dispatching device, characterized in that: Used to implement the multi-guided vehicle dispatching method according to any one of claims 1 to 7, the multi-guided vehicle dispatching device comprises: The material level statistics module is used to obtain the free space of multiple material levels, where each material level free space corresponds to a material level; A schedule generation equation construction module is used to construct multiple route schedule equations starting from multiple standby positions, traveling along grid points and passing through the material warehouse to finally reach the material position, wherein each route schedule equation corresponds to a standby position, and each standby position corresponds to a standby guide vehicle; A constraint condition construction module, used to construct a route schedule constraint condition and a plurality of material level absolute time constraint conditions according to the total operation schedule, the plurality of material level vacancies and the plurality of material level consumption rates, wherein each material level consumption rate and each material level absolute time constraint condition respectively corresponds to a material level; as well as, The scheduling strategy determination module is used to optimize the multiple route schedule equations with the goal of minimizing the total time consumption and determining the scheduling strategies of the multiple standby guided vehicles based on the optimization results, wherein the total time consumption represents the total operating time of the multiple standby guided vehicles.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method as claimed in any one of claims 1 to 7 are implemented.

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