Traffic flow planning method, device, equipment and storage medium for open-pit mines

Abstract

The present application discloses a method, device, equipment and storage medium for traffic flow planning in an open-pit mine. The method includes: obtaining a shoveling plan for the open-pit mine; determining the transport equivalent distance between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, as well as at least one of the road quality grade, road slope, road speed limit and road turning radius; obtaining a traffic flow planning scheme based on the transport equivalent distance and a set planning optimization model; wherein the optimization objective of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: a shoveling plan constraint, a crushing station grade constraint and a transportation cycle constraint; the traffic flow planning scheme includes: a heavy vehicle trip from the loading point to the corresponding unloading point, and the transportation route of each heavy vehicle trip, and an empty vehicle trip from the unloading point to the corresponding loading point, and the transportation route of each empty vehicle trip.

Description

Technical Field

[0001] The present application relates to the field of mining, and in particular to a method, device, equipment and storage medium for traffic flow planning in an open-pit mine. Background Art

[0002] The production mode of open-pit mines is mainly based on the intermittent process of forklift loading and truck transportation. The control of open-pit mine transportation costs is crucial to improving the overall efficiency of open-pit mines, and the total energy consumption of mine transportation is a direct reflection of the transportation cost.

[0003] The results of traffic flow planning in open-pit mines determine the total energy consumption of mine transportation. Currently, for open-pit mines with a low level of digitalization and intelligent construction, fixed vehicle dispatching is mainly used for production. That is, based on the shoveling plan (including information such as loading points, loading equipment, loading volume and corresponding unloading point locations), a fixed number of trucks are designated to repeatedly travel back and forth between fixed loading and unloading points. This method does not involve traffic flow planning, resulting in a high total energy consumption of mine transportation. For mines with a certain foundation of digitalization and intelligent construction, traffic flow planning is one of the links in mine production organization. However, the existing traffic flow planning methods mainly aim to maximize shift production output. Although such methods have improved the production efficiency of mines to a certain extent within the local cycle, from a global perspective, they ignore the total energy consumption of mine transportation, mine sustainable development planning and mine production ore quality control.

[0004] Secondly, in the decision-making process of traffic flow planning in open-pit mines, it is crucial to accurately estimate the equivalent transportation distance between loading and unloading points. Current technical methods use the spatial distance between loading and unloading points as the basis for decision-making, ignoring the quality grade of mine roads, road slopes, road turns, etc., resulting in unreasonable traffic flow planning results. Summary of the Invention

[0005] In view of this, the embodiments of the present application provide a method, device, equipment and storage medium for traffic flow planning in an open-pit mine, aiming to effectively reduce the comprehensive energy consumption of mining and improve production efficiency.

[0006] The technical solution of the embodiment of the present application is implemented as follows:

[0007] In a first aspect, an embodiment of the present application provides a method for traffic flow planning in an open-pit mine, comprising:

[0008] Obtaining a shovel loading plan for an open-pit mine, wherein the shovel loading plan includes a loading plan and an unloading plan;

[0009] Determining transport equivalent distances between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius;

[0010] Based on the transport equivalent distance and the set planning optimization model, a traffic flow planning scheme is obtained;

[0011] Among them, the optimization goal of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: shoveling plan constraints, crushing station grade constraints and transportation cycle constraints; the traffic planning scheme includes: heavy vehicle trips from the loading point to the corresponding unloading point, and the transportation routes of each heavy vehicle trip, and empty vehicle trips from the unloading point to the corresponding loading point, and the transportation routes of each empty vehicle trip.

[0012] In some embodiments, the planning optimization model is as follows:

[0013]

[0014]

[0015] Among them, st represents the constraint rule, I is the set of loading points, i is the loading point index, J is the set of unloading points, j is the unloading point index, and f T is the truck capacity, w T is the truck's own weight, x i,j is the number of heavy vehicles from the i-th loading point to the j-th unloading point, y i,j is the number of empty vehicles from the jth unloading point to the ith loading point, is the transport equivalent distance, p i is the output at the loading point, p j is the output at the unloading point, f S is the shovel capacity, t S is the shovel loading time, o is the ore supply pile index, p o is the amount of ore for blasting, t a is the total duration of the transportation scheduling cycle, f L is the capacity of the hook machine, t L is the loading time of the hook machine, w is the stripping pile index, p w is the amount of rock removed from the blast pile, h is the index of the reverse blast pile, and p h is the amount of blasting ore transported, t D is the unloading time, v W is the speed of the heavy vehicle, v e is the empty vehicle speed, The upper limit of the grade requirement of the crushing station, g o,e To provide blasting grade for ore, is the lower limit of grade requirement of the crushing station, c is the crushing station index, e is the metal element index, is a path constraint.

[0016] In some embodiments, the loading plan includes: a shift production cycle, a loading point name, a loading point spatial range, a shovel loading orientation, a loading point ore type, a loading quantity, and the quality of each mineral element at the loading point;

[0017] The unloading plan includes: the name of the unloading point, the unloading volume and the upper and lower limits of the quality of each mineral element at the unloading point.

[0018] In some embodiments, determining the transport equivalent distance between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius, includes:

[0019] determining a set of loading points based on the loading plan, and determining a set of unloading points based on the unloading plan;

[0020] constructing an undirected graph corresponding to a road network based on the set of loading points, the set of unloading points, and the geographical location information of the open-pit mine;

[0021] Correcting the road length of each road in the undirected graph based on the road quality grade, road slope, road speed limit, and road turning radius to obtain a corrected distance value;

[0022] For any pair of loading points and unloading points, the path with the shortest corrected distance value is determined based on the optimal path algorithm, and the corrected distance value of the shortest path is used as the transportation equivalent distance between the corresponding loading point and unloading point.

[0023] In a second aspect, an embodiment of the present application provides a vehicle flow planning device for an open-pit mine, comprising:

[0024] An acquisition module is used to acquire a shoveling plan of an open-pit mine, wherein the shoveling plan includes a loading plan and an unloading plan;

[0025] a determination module configured to determine a transport equivalent distance between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius;

[0026] A planning module, configured to obtain a traffic flow planning solution based on the transport equivalent distance and a set planning optimization model;

[0027] Among them, the optimization goal of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: shoveling plan constraints, crushing station grade constraints and transportation cycle constraints; the traffic planning scheme includes: heavy vehicle trips from the loading point to the corresponding unloading point, and the transportation routes of each heavy vehicle trip, and empty vehicle trips from the unloading point to the corresponding loading point, and the transportation routes of each empty vehicle trip.

[0028] In some embodiments, the planning optimization model is as follows:

[0029]

[0030] Among them, st represents the constraint rule, I is the set of loading points, i is the loading point index, J is the set of unloading points, j is the unloading point index, and f T is the truck capacity, w T is the truck's own weight, x i,j is the number of heavy vehicles from the i-th loading point to the j-th unloading point, y i,j is the number of empty vehicles from the jth unloading point to the ith loading point, is the transport equivalent distance, p i is the output at the loading point, p j is the output at the unloading point, f S is the shovel capacity, t S is the shovel loading time, o is the ore supply pile index, p o is the amount of ore for blasting, t a is the total duration of the transportation scheduling cycle, f L is the capacity of the hook machine, t L is the loading time of the hook machine, w is the stripping pile index, p w is the amount of rock removed from the blast pile, h is the index of the reverse blast pile, and p h is the amount of blasting ore transported, t D is the unloading time, v W is the speed of the heavy vehicle, v e is the empty vehicle speed, The upper limit of the grade requirement of the crushing station, g o,e To provide blasting grade for ore, is the lower limit of grade requirement of the crushing station, c is the crushing station index, e is the metal element index, is a path constraint.

[0031] 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.

[0032] 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.

[0033] The technical solution provided by the embodiment of the present application obtains the shoveling plan of the open-pit mine; determines the transport equivalent distance between the paired loading points and the unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, as well as at least one of the road quality grade, road slope, road speed limit and road turning radius; obtains a traffic flow planning scheme based on the transport equivalent distance and a set planning optimization model; wherein the optimization objective of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: shoveling plan constraints, crushing station grade constraints and transportation cycle constraints; the traffic flow planning scheme includes: the number of heavy vehicles from the loading point to the corresponding unloading point, and the transportation route of each heavy vehicle, and the number of empty vehicles from the unloading point to the corresponding loading point, and the transportation route of each empty vehicle. In this way, the traffic flow planning scheme can be optimized on the basis of taking into account the shoveling plan constraints, crushing station grade constraints and transportation cycle constraints, so as to minimize the total energy consumption of mine transportation, meet the comprehensive requirements of total transportation energy consumption, mine sustainable development planning and mine production ore quality control, and thus improve mine production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of a method for traffic flow planning in an open-pit mine according to an embodiment of the present application;

[0035] Figure 2 This is a schematic structural diagram of a traffic flow planning device for an open-pit mine according to an embodiment of the present application;

[0036] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0037] The present application will be described in further detail below with reference to the accompanying drawings and embodiments.

[0038] 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.

[0039] In the related art, since mining production is only based on the shoveling plan, traffic flow planning also only focuses on the production output of the shift. The embodiment of the present application provides a traffic flow planning method for open-pit mines based on the shoveling plan. Combined with the road quality grade, road slope, road turns and other conditions of the mine road, the transportation equivalent distance between loading and unloading points is accurately estimated as the basis for traffic flow planning decisions, so as to achieve the goal of minimizing the total energy consumption of mine transportation, taking into account the shoveling plan constraints, crushing station grade constraints, transportation cycle constraints and other conditions of the open-pit mine traffic flow planning, thereby reducing mine production energy consumption and improving mine production efficiency.

[0040] The embodiment of the present application provides a method for traffic flow planning in an open-pit mine, which can be applied to electronic devices with data processing capabilities, such as notebooks, desktop computers or servers, to achieve traffic flow planning in open-pit mines, such as Figure 1 As shown, the method includes:

[0041] Step 101: Obtain a shoveling plan for an open-pit mine, wherein the shoveling plan includes a loading plan and an unloading plan.

[0042] For example, the open-pit shoveling plan can be a shift production instruction issued to each production shovel according to the time and space development sequence of mine stripping, the shift plan and the conditions of ore quality control.

[0043] In one example, the loading plan includes: shift production cycle, loading point name, loading point spatial range, shoveling direction, loading point ore type, loading volume and quality of each mineral element at the loading point; the unloading plan includes: unloading point name, unloading volume and upper and lower limits of quality of each mineral element at the unloading point.

[0044] Step 102: Determine the transport equivalent distance between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius.

[0045] It should be noted that the haul road network of open-pit mines is complex and constantly updated as production progresses. For example, the haul road network of open-pit mines can be roughly divided into three categories based on their service life: The first category is fixed roads, primarily used to connect mining sites, dumping sites, and other industrial sites. Fixed roads have high quality requirements, a relatively smooth surface, and relatively fast truck speeds. The second category is semi-fixed roads, primarily used to access the various steps of the mining site and the dumping site. As mining progresses, these roads are regularly updated. Semi-fixed roads have average quality requirements, average surface smoothness, and average truck speeds. The third category is temporary roads, primarily used to connect blast piles, stripping blast piles, and transporting blast piles to semi-fixed roads. As mining progresses, these roads are dynamically updated. Temporary roads have low quality, uneven surfaces, and slow truck speeds. The aforementioned road quality levels can include: a first quality level for fixed roads, a second quality level for semi-fixed roads, and a third quality level for temporary roads.

[0046] For example, when trucks operate on haul roads in open-pit mines, their travel is affected not only by the road quality grade but also by factors such as road slope, speed limit, and turning radius. The haul equivalent distance for truck dispatch in open-pit mines comprehensively considers factors such as road length, road quality grade, road slope, speed limit, and turning radius, then modifies the actual road length with corresponding influence coefficients to objectively reflect the truck's travel time on the road. This haul equivalent distance is the foundation for optimal route decisions and traffic flow planning optimization in open-pit mines.

[0047] In an application example, the transport equivalent distance l E The calculation formula is as follows:

[0048] l E =k r k g k v k t l

[0049] Among them, k r Indicates the mine road quality correction coefficient;

[0050] k g Indicates the slope correction coefficient of the mine road;

[0051] k v Indicates the speed limit correction factor of the mine road;

[0052] k t Indicates the turning radius correction coefficient of the mine road;

[0053] l represents the spatial transportation distance of the mine road.

[0054] In some embodiments, determining the transport equivalent distance between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius, includes:

[0055] determining a set of loading points based on the loading plan, and determining a set of unloading points based on the unloading plan;

[0056] constructing an undirected graph corresponding to a road network based on the set of loading points, the set of unloading points, and the geographical location information of the open-pit mine;

[0057] Correcting the road length of each road in the undirected graph based on the road quality grade, road slope, road speed limit, and road turning radius to obtain a corrected distance value;

[0058] For any pair of loading points and unloading points, the path with the shortest corrected distance value is determined based on the optimal path algorithm, and the corrected distance value of the shortest path is used as the transportation equivalent distance between the corresponding loading point and unloading point.

[0059] For example, let the set of loading points of an open-pit mine be I, the set of unloading points be J, and the set of other intermediate nodes be K. The road network can be constructed as an undirected graph G = (V, I ∪ J ∪ K). The optimal path decision of an open-pit mine refers to finding the path with the shortest transportation equivalent distance (i.e., the corrected distance value) between any loading point i and any unloading point j. Therefore, the optimal path decision is a multi-source, undirected, non-negative-weighted shortest path problem, and the optimal path can be found using the Floyd-Warshall algorithm.

[0060] Step 103: Obtain a traffic flow planning solution based on the transport equivalent distance and the set planning optimization model.

[0061] Here, the optimization goal of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: shoveling plan constraints, crushing station grade constraints and transportation cycle constraints; the traffic planning scheme includes: heavy vehicle trips from the loading point to the corresponding unloading point, and the transportation routes of each heavy vehicle trip, and empty vehicle trips from the unloading point to the corresponding loading point, and the transportation routes of each empty vehicle trip.

[0062] It can be understood that the method of the embodiment of the present application can optimize the traffic planning scheme on the basis of taking into account the shoveling plan constraints, the crushing station grade constraints and the transportation cycle constraints, so as to minimize the total energy consumption of mine transportation, meet the comprehensive needs of total transportation energy consumption, mine sustainable development planning and mine production ore quality control, and thus improve the production efficiency of the mine.

[0063] In some embodiments, the planning optimization model is as follows:

[0064]

[0065]

[0066] Among them, st is the abbreviation of subject to (such that), which means the constraint rule, I is the set of loading points, i is the loading point index, J is the set of unloading points, j is the unloading point index, f T is the truck capacity, w T is the truck's own weight, x i,j is the number of heavy vehicles from the i-th loading point to the j-th unloading point, y i,j is the number of empty vehicles from the jth unloading point to the ith loading point, is the transport equivalent distance, p i is the output at the loading point, p j is the output at the unloading point, f S is the shovel capacity, t S is the shovel loading time, o is the ore supply pile index, p o is the amount of ore for blasting, t a is the total duration of the transportation scheduling cycle, f L is the capacity of the hook machine, t L is the loading time of the hook machine, w is the stripping pile index, p w is the amount of rock removed from the blast pile, h is the index of the reverse blast pile, and p h is the amount of blasting ore transported, t D is the unloading time, v W is the speed of the heavy vehicle, v e is the empty vehicle speed, The upper limit of the grade requirement of the crushing station, g o,e To provide blasting grade for ore, is the lower limit of grade requirement of the crushing station, c is the crushing station index, e is the metal element index, is a path constraint.

[0067] The following is an exemplary description of the planning optimization model of the embodiment of the present application: Assume that the set related to the planning optimization model is as follows:

[0068] I: Mounting point set;

[0069] J: unloading point set;

[0070] O: Ore blasting pile collection;

[0071] E: Metal element collection;

[0072] W: peel off the explosion pile collection;

[0073] H: bad luck explosion pile collection;

[0074] S: shovel assembly;

[0075] L: hook machine collection;

[0076] T: Truck collection;

[0077] C: Crushing station collection.

[0078] Assume that the indexes related to the planning optimization model are as follows:

[0079] i: mount point index;

[0080] j: uninstallation point index;

[0081] o: index of the ore explosion pile;

[0082] w: strip the burst index;

[0083] h: index of the reverse burst pile;

[0084] e: metal element index;

[0085] c: Crushing station index;

[0086] l: hook machine index;

[0087] t: Truck index.

[0088] Assume that the parameters related to the planning optimization model are as follows:

[0089] t a : The total duration of the scheduling transportation cycle;

[0090] n O : Number of blasting piles for ore supply;

[0091] n W : Number of stripped explosion piles;

[0092] n H : The number of bad luck explosion piles;

[0093] n S : Number of electric shovels;

[0094] n L : Number of hook machines;

[0095] n T : number of trucks;

[0096] f S : Shovel capacity;

[0097] f L : Hook machine capacity;

[0098] t S : Electric shovel loading time;

[0099] t L : The time it takes for the hook machine to load the ore;

[0100] t D : unloading time;

[0101] f T : Truck capacity;

[0102] w T : Truck weight;

[0103] v e : empty vehicle speed;

[0104] v W : heavy vehicle speed;

[0105] p i : Loading point output;

[0106] n I : Number of mounting points;

[0107] p o : Amount of ore for blasting; g o,e : blasting grade of ore; p w : the amount of rock stripped from the blast pile; p h : The amount of ore transported to the blast pile; Transport equivalent distance; Path constraints;

[0108] p j : Output at unloading point;

[0109] n J : Number of unloading points;

[0110] The upper limit of grade requirement for the crushing station;

[0111] g c,e : The lower limit of grade requirement for the crushing station.

[0112] The decision variables of the planning optimization model are as follows: i,j : The number of heavy vehicles from the i-th loading point to the j-th unloading point; y i,j : The number of empty trucks from the jth unloading point to the ith loading point. The constraints of the planning optimization model are as follows:

[0113] (1) Consistency constraints on round trip times in truck scheduling

[0114] (2) Output constraints at loading points based on shoveling plans

[0115] (3) Output constraints at unloading points based on shoveling plans

[0116] (4) Constraints on the production capacity of blasting piles for ore supply

[0117]

[0118] (5) Removing the constraints on explosive pile production capacity

[0119]

[0120] (6) Constraints on the production capacity of dumping and blasting piles

[0121]

[0122] (7) Unloading point production capacity constraints

[0123]

[0124] (8) Total time constraints for heavy vehicle transport

[0125]

[0126] (9) Total time constraint for empty truck transportation

[0127]

[0128] (10) Crushing station grade constraints

[0129]

[0130] (11) Path logical constraints

[0131]

[0132] (12) Logical constraints on decision variables

[0133] Integer

[0134] Among them, the transportation energy consumption of open-pit mines refers to the product of the equivalent transportation distance and the total weight of the truck. The main purpose of open-pit mine transportation traffic planning is to minimize the total energy consumption. The total energy consumption includes both the total energy consumption of heavy vehicle transportation and the total energy consumption of empty vehicle transportation. Taking this as the objective function, a mathematical model of open-pit mine transportation traffic planning based on integer programming is established.

[0135] Among them, constraint (1) ensures the consistency of the number of round trips during truck scheduling, that is, the total number of trips from a certain loading point to each unloading point is equal to the total number of trips from each unloading point back to the loading point, and at the same time, the total number of trips sent back from a certain unloading point to each loading point is equal to the total number of trips from each loading point to the unloading point; constraint (2) realizes that the loading capacity of each loading point is greater than the output of the loading point, thereby ensuring the completion of the shoveling planned output demand of each loading point; constraint (3) realizes that the unloading capacity of each unloading point is greater than the output of the unloading point, thereby ensuring the completion of the shoveling planned output demand of each unloading point; constraint (4) realizes that each ore supply pile completes the ore supply output demand within the scheduling cycle, that is, the total amount of electric shovel loading of the ore supply pile is greater than the output demand of the ore supply pile, and the total ore loading time is within the scheduling cycle time range; constraint (5) realizes that each stripping pile completes the stripping output demand within the scheduling cycle, that is, the total amount of loading of the stripping pile crane is greater than the output demand of the stripping pile, and the total loading time is within the scheduling cycle time range; constraint (6) realizes that each transported blast pile completes the ore supply output demand within the scheduling cycle The total amount of loading of the crane for transporting explosive piles is greater than the production demand of transporting explosive piles, and the total loading time is within the time range of the scheduling cycle; constraint (7) realizes that each unloading point completes the unloading production demand within the scheduling cycle, ensuring that the total unloading time is within the time range of the scheduling cycle; constraint (8) realizes the total time limit of the heavy vehicle constraint, ensuring that the total transportation time of the heavy vehicle trip is within the time range of the scheduling cycle; constraint (9) realizes the total time limit of the empty vehicle constraint, ensuring that the total transportation time of the empty vehicle trip is within the time range of the scheduling cycle Within; Constraint (10) realizes the grade fluctuation limit of the crushing station, ensuring that the average grade of each element in each crushing station is within its allowed fluctuation range; Constraint (11) is the path logic constraint, each truck loaded with ore blasting pile can only be transported to the crushing station accordingly, each truck loaded with stripping blasting pile can only be transported to the spoil dump accordingly, and each truck loaded with transporting blasting pile can only be transported to the storage yard accordingly, to avoid logistics loading and unloading confusion; Constraint (12) ensures the non-negativity of each decision variable, and the decision variable is required to be an integer greater than or equal to 0 in integer programming.

[0136] The planning optimization model of the embodiment of the present application is solved to obtain a traffic flow planning scheme, that is, the heavy vehicle trips from the loading point to the corresponding unloading point, and the transportation routes of each of the heavy vehicle trips, and the empty vehicle trips from the unloading point to the corresponding loading point, and the transportation routes of each of the empty vehicle trips.

[0137] The following is an example of an application to illustrate the traffic flow planning method for an open-pit mine in an embodiment of the present application.

[0138] In this application example, the basic situation during the scheduling cycle of 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 each crushing station 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 of the electric shovel is 5 minutes, the average loading time of the crane is 7 minutes, and the average unloading time of 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. The output and metal element grade of each blasting pile are shown in Table 1, and the output and metal element grade demand of each crushing station are shown in Table 2.

[0139] Table 1 Ore blasting pile output and metal element grade

[0140]

[0141] Table 2 Crushing station output and metal element grade

[0142]

[0143] There are two stripping piles, with production requirements of 35,000 tons and 30,000 tons, respectively, and two transshipment piles, with production requirements of 25,000 tons and 20,000 tons, respectively. The equivalent distances (also referred to as haul distances) that trucks travel between loading and unloading points are shown in Table 3, with the path constraints shown in Table 4.

[0144] Table 3 Distance between loading point and unloading point

[0145]

[0146] Table 4 Path constraints between loading points and unloading points

[0147]

[0148] Before optimizing the transport flow planning, the mine used a fixed truck-shovel method to organize and dispatch transportation, that is, trucks were fixed to travel back and forth between designated loading and unloading points. At this time, the number of loaded trucks between each loading point and its corresponding unloading point must be equal to the number of empty trucks. The number of loaded trucks, empty trucks, and the energy consumption of loaded trucks and empty trucks during the transport cycle are shown in Table 5.

[0149] Table 5 Energy consumption before optimization of transport flow planning

[0150]

[0151] The above traffic flow is planned and optimized using the integer programming mathematical model of transport traffic flow planning. The mathematical model is solved and the optimized distribution of loaded and empty vehicle trips is obtained as shown in Tables 6 and 7.

[0152] Table 6 Distribution of heavy vehicle trips after optimization of transport traffic flow planning

[0153]

[0154] Table 7 Distribution of empty trains after optimized transport flow planning

[0155]

[0156] Statistical analysis shows that with the same loading and unloading requirements, the total energy consumption before the optimization of transport vehicle flow planning is 1.217×10 9 t·m, after the optimization of transport vehicle flow planning, the total energy consumption is 1.030×10 9 t·m, and the total energy consumption was reduced by 15.4%.

[0157] In order to implement the method of the embodiment of the present application, the embodiment of the present application also provides a traffic flow planning device for an open-pit mine, which is set on an electronic device, such as Figure 2 As shown, the traffic flow planning device for the open-pit mine includes: an acquisition module 201, a determination module 202, and a planning module 203. The acquisition module 201 is used to obtain the shoveling plan of the open-pit mine, and the shoveling plan includes: a loading plan and an unloading plan; the determination module 202 is used to determine the transportation equivalent distance between the paired loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, as well as at least one of the road quality grade, road slope, road speed limit, and road turning radius; the planning module 203 is used to obtain a traffic flow planning scheme based on the transportation equivalent distance and a set planning optimization model; wherein the optimization objective of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: a shoveling plan constraint, a crushing station grade constraint, and a transportation cycle constraint; the traffic flow planning scheme includes: a heavy vehicle trip from the loading point to the corresponding unloading point, and the transportation route of each heavy vehicle trip, and an empty vehicle trip from the unloading point to the corresponding loading point, and the transportation route of each empty vehicle trip.

[0158] In some embodiments, the planning optimization model is as follows:

[0159]

[0160]

[0161] Among them, st represents the constraint rule, I is the set of loading points, i is the loading point index, J is the set of unloading points, j is the unloading point index, and f T is the truck capacity, w T is the truck's own weight, x i,j is the number of heavy vehicles from the i-th loading point to the j-th unloading point, y i,j is the number of empty vehicles from the jth unloading point to the ith loading point, is the transport equivalent distance, p i is the output at the loading point, p j is the output at the unloading point, f S is the shovel capacity, t S is the shovel loading time, o is the ore supply pile index, p o is the amount of ore for blasting, t a is the total duration of the transportation scheduling cycle, f L is the capacity of the hook machine, t L is the loading time of the hook machine, w is the stripping pile index, p w is the amount of rock removed from the blast pile, h is the index of the reverse blast pile, and p h is the amount of blasting ore transported, t D is the unloading time, v W is the speed of the heavy vehicle, v e is the empty vehicle speed, The upper limit of the grade requirement of the crushing station, g o,e To provide blasting grade for ore, is the lower limit of grade requirement of the crushing station, c is the crushing station index, e is the metal element index, is a path constraint.

[0162] In some embodiments, the loading plan includes: a shift production cycle, a loading point name, a loading point spatial range, a shovel loading orientation, a loading point ore type, a loading quantity, and the quality of each mineral element at the loading point;

[0163] The unloading plan includes: the name of the unloading point, the unloading volume and the upper and lower limits of the quality of each mineral element at the unloading point.

[0164] In some embodiments, the determination module 202 is specifically configured to:

[0165] determining a set of loading points based on the loading plan, and determining a set of unloading points based on the unloading plan;

[0166] constructing an undirected graph corresponding to a road network based on the set of loading points, the set of unloading points, and the geographical location information of the open-pit mine;

[0167] Correcting the road length of each road in the undirected graph based on the road quality grade, road slope, road speed limit, and road turning radius to obtain a corrected distance value;

[0168] For any pair of loading points and unloading points, the path with the shortest corrected distance value is determined based on the optimal path algorithm, and the corrected distance value of the shortest path is used as the transportation equivalent distance between the corresponding loading point and unloading point.

[0169] In actual application, the acquisition module 201, the determination module 202 and the planning module 203 can be implemented by a processor of the electronic device. Of course, the processor needs to run the computer program in the memory to implement its functions.

[0170] It should be noted that the above-mentioned embodiment of the open-pit mine traffic flow planning device is only used as an example to illustrate the division of the above-mentioned program modules when performing traffic flow planning for the open-pit mine. In actual application, the above-mentioned 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 above-mentioned processing. In addition, the open-pit mine traffic flow planning device provided in the above-mentioned embodiment and the open-pit mine traffic flow planning method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0171] 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 the exemplary structure of the electronic device is shown, not all structures, and can be implemented as needed. Figure 3 Partial or complete structure shown.

[0172] like Figure 3 As 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 .

[0173] 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.

[0174] 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.

[0175] The open-pit mine traffic flow planning method disclosed in the embodiments of this 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 open-pit mine traffic flow planning method can be completed by hardware integrated logic circuits or software instructions in processor 301. The processor 301 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. Processor 301 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium located in memory 302. Processor 301 reads information from memory 302 and, in conjunction with its hardware, completes the steps of the open-pit mine traffic flow planning method provided in the embodiments of this application.

[0176] 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.

[0177] It is understood that memory 302 can be volatile memory or non-volatile memory, or can include both volatile and non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disk, or compact disc read-only memory (CD-ROM); magnetic surface memory can be magnetic disk memory or tape memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, 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 (DDRSDRAM), 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.

[0178] 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.

[0179] 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.

[0180] In addition, the technical solutions described in the embodiments of the present application can be arbitrarily combined without conflict.

[0181] 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 traffic flow planning method for an open-pit mine, characterized in that: include: Obtaining a shovel loading plan for an open-pit mine, wherein the shovel loading plan includes a loading plan and an unloading plan; Determining transport equivalent distances between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius; Based on the transport equivalent distance and the set planning optimization model, a traffic flow planning scheme is obtained; The optimization objective of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: shoveling plan constraints, crushing station grade constraints, and transportation cycle constraints; the vehicle flow planning scheme includes: heavy vehicle trips from loading points to corresponding unloading points, and the transportation routes of each heavy vehicle trip, and empty vehicle trips from unloading points to corresponding loading points, and the transportation routes of each empty vehicle trip; The planning optimization model is as follows: Among them, st represents the constraint rule, I is the set of loading points, i is the loading point index, J is the set of unloading points, j is the unloading point index, and f T is the truck capacity, w T is the truck's own weight, x i,j is the number of heavy vehicles from the i-th loading point to the j-th unloading point, y i,j is the number of empty vehicles from the jth unloading point to the ith loading point, is the transport equivalent distance, p i is the output at the loading point, p j is the output at the unloading point, f S is the shovel capacity, t S is the shovel loading time, o is the ore supply pile index, p o is the amount of ore for blasting, t a is the total duration of the transportation scheduling cycle, f L is the capacity of the hook machine, t L is the loading time of the hook machine, w is the stripping pile index, p w is the amount of rock removed from the blast pile, h is the index of the reverse blast pile, and p h is the amount of blasting ore transported, t D is the unloading time, v W is the speed of the heavy vehicle, v e is the empty vehicle speed, The upper limit of the grade requirement of the crushing station, g o,e To provide blasting grade for ore, is the lower limit of grade requirement of the crushing station, c is the crushing station index, e is the metal element index, is the path constraint; The determining of the transport equivalent distances between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius, includes: determining a set of loading points based on the loading plan, and determining a set of unloading points based on the unloading plan; constructing an undirected graph corresponding to a road network based on the set of loading points, the set of unloading points, and the geographical location information of the open-pit mine; Correcting the road length of each road in the undirected graph based on the road quality grade, road slope, road speed limit, and road turning radius to obtain a corrected distance value; For any pair of loading points and unloading points, the path with the shortest corrected distance value is determined based on the optimal path algorithm, and the corrected distance value of the shortest path is used as the transportation equivalent distance between the corresponding loading point and unloading point.

2. The method according to claim 1, characterized in that The loading plan includes: shift production cycle, loading point name, loading point spatial range, shovel loading direction, loading point ore type, loading quantity and quality of each mineral element at the loading point; The unloading plan includes: the name of the unloading point, the unloading volume and the upper and lower limits of the quality of each mineral element at the unloading point.

3. A traffic flow planning device for an open-pit mine, characterized in that: include: An acquisition module is used to acquire a shoveling plan of an open-pit mine, wherein the shoveling plan includes a loading plan and an unloading plan; a determination module configured to determine a transport equivalent distance between pairs of loading points and unloading points based on each loading point in the loading plan and each unloading point in the unloading plan, and at least one of a road quality grade, a road slope, a road speed limit, and a road turning radius; A planning module, configured to obtain a traffic flow planning solution based on the transport equivalent distance and a set planning optimization model; The optimization objective of the planning optimization model is to minimize the total energy consumption of mine transportation, and the constraints of the planning optimization model include at least: shoveling plan constraints, crushing station grade constraints, and transportation cycle constraints; the vehicle flow planning scheme includes: heavy vehicle trips from loading points to corresponding unloading points, and the transportation routes of each heavy vehicle trip, and empty vehicle trips from unloading points to corresponding loading points, and the transportation routes of each empty vehicle trip; The planning optimization model is as follows: Among them, st represents the constraint rule, I is the set of loading points, i is the loading point index, J is the set of unloading points, j is the unloading point index, and f T is the truck capacity, w T is the truck's own weight, x i,j is the number of heavy vehicles from the i-th loading point to the j-th unloading point, y i,j is the number of empty vehicles from the jth unloading point to the ith loading point, is the transport equivalent distance, p i is the output at the loading point, p j is the output at the unloading point, f S is the shovel capacity, t S is the shovel loading time, o is the ore supply pile index, p o is the amount of ore for blasting, t a is the total duration of the transportation scheduling cycle, f L is the capacity of the hook machine, t L is the loading time of the hook machine, w is the stripping pile index, p w is the amount of rock removed from the blast pile, h is the index of the reverse blast pile, and p h is the amount of blasting ore transported, t D is the unloading time, v W is the speed of the heavy vehicle, v e is the empty vehicle speed, The upper limit of the grade requirement of the crushing station, g o,e To provide blasting grade for ore, is the lower limit of grade requirement of the crushing station, c is the crushing station index, e is the metal element index, is the path constraint; The determining module is specifically configured to: determining a set of loading points based on the loading plan, and determining a set of unloading points based on the unloading plan; constructing an undirected graph corresponding to a road network based on the set of loading points, the set of unloading points, and the geographical location information of the open-pit mine; Correcting the road length of each road in the undirected graph based on the road quality grade, road slope, road speed limit, and road turning radius to obtain a corrected distance value; For any pair of loading points and unloading points, the path with the shortest corrected distance value is determined based on the optimal path algorithm, and the corrected distance value of the shortest path is used as the transportation equivalent distance between the corresponding loading point and unloading point.

4. 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.

5. 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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