Method for optimizing long-term and short-term rock dumping in mining process

Abstract

The invention discloses an optimization method for long-term and short-term rock dumping in a mining process. The method comprises the following steps: 1, determining a long-term rock dumping plan, and determining related conditions of the long-term rock dumping plan according to actual production requirements; 2, determining related conditions of the short-term plan of the shift; 3, constructing a short-term rock dumping optimization model of the shift; 4, solving the optimization model by adopting an evolutionary algorithm, and generating a shift short-term plan; 5, generating a reasonable vehicle-shovel ratio according to the short-term planned transportation volume of the shift; step 6, configuring a corresponding number of transport vehicles and shovel loading equipment according to the vehicle-shovel ratio, then executing the short-term plan of the shift, and counting related data after actual execution; and step 7, judging whether the long-term plan is completed or not according to the accumulated transportation volume and the accumulated working time counted by the related data, and if not, skipping to the step 2 to carry out the short-term plan stage of the next shift. The method has the characteristics of systematicness and flexible adaptability.

Description

Technical Field

[0001] The invention relates to the field of mining engineering and mining technology, and in particular to a long-term and short-term rock removal optimization method for a mining process. Background Art

[0002] In the process of open-pit mining, stripping the rock covering the ore body is a necessary preliminary operation. Since the amount of waste rock stripping in metal open-pit mines is usually much greater than the amount of ore mined, the workload of rock removal is huge, which puts high demands on the formulation of rock removal plans.

[0003] At present, the formulation of rock removal plans mainly relies on manual experience and is achieved through preset fixed task allocation. This traditional method has obvious shortcomings when dealing with complex operating environments: it is difficult to fully consider the various restrictions on loading and unloading points and the binding relationship between loading and unloading points, resulting in low resource utilization efficiency; in addition, traditional methods often ignore key factors such as excavator loading speed and shift cycle, and cannot accurately optimize the relationship between transportation volume and transportation distance, which in turn affects the overall operating efficiency of the mine; it does not combine long-term and short-term plans, lacks systematic and intelligent rock removal plan optimization methods, resulting in unreasonable resource allocation during the rock removal process, increasing non-productive operation time and costs. Summary of the invention

[0004] In order to overcome the above technical problems, the purpose of the present invention is to provide a long-term and short-term rock removal optimization method for the mining process, which has the characteristics of systematicity and flexible adaptability. The systematicity is reflected in dividing the long-term plan into multiple short-term plans, and the long-term and short-term plans are combined for execution; the flexible adaptability is reflected in establishing a feedback optimization mechanism, and dynamically adjusting the subsequent short-term plans according to the execution of the current short-term plan.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A method for optimizing long-term and short-term rock removal in a mining process comprises the following steps;

[0007] Step 1: Determine the long-term rock removal plan and determine the relevant conditions of the long-term rock removal plan according to actual production needs;

[0008] Step 2: Determine the relevant conditions for the short-term plan of this shift based on the actual production situation and the goals of the long-term plan;

[0009] Step 3: Based on the relevant conditions determined in step 2, a short-term rock removal optimization model for this shift is constructed, with variable X ij Represents loading point F i To each unloading point T j Planned rock transport volume;

[0010] Step 4, generating a rock removal plan for a shift, using an evolutionary algorithm to solve the optimization model and generate a short-term plan for this shift;

[0011] Step 5, generating a reasonable vehicle-to-shovel ratio according to the short-term planned transportation volume of the current shift;

[0012] Step 6, according to the vehicle-to-shovel ratio, configure a corresponding number of transport vehicles and shovel loading equipment to execute the short-term plan of this shift, and collect relevant data after actual execution;

[0013] Step 7: Determine whether the long-term plan is completed based on the cumulative transportation volume and cumulative working hours of relevant data statistics. If not, jump to step 2 to proceed to the short-term planning stage of the next shift.

[0014] The step 1 specifically includes the following contents:

[0015] Step 1.1: Determine the long-term rock output target P i , representing the loading point F i The total amount of rock discharge expected in the long term;

[0016] Step 1.2, determine the total working time T total , indicating the total working time of the equipment in the long term;

[0017] Step 1.3, determine the binding relationship matrix B ij , representing the loading point F i With unloading point T j The value is 1 or 0, indicating whether there is a binding relationship. i With unloading point T j If there is no binding relationship, it means the mounting point F i The rock cannot be transported to the unloading point T j ;

[0018] Step 1.4, determine the distance matrix D ij , representing the loading point F i With unloading point T j The transportation distance between

[0019] Step 1.5, the rock output of each loading point is set to A i , the long-term completed work duration is T completed , are initially set to 0.

[0020] The step 2 is specifically as follows:

[0021] Step 2.1: Manually input the working time T of the current shift and automatically calculate the number of remaining shifts B in the long term remaining , the calculation formula is as follows:

[0022]

[0023] Step 2.2, assign shovels to each loading point in this shift manually, including C k With N ik , respectively represent the working capacity of the kth shovel loading equipment and the capacity assigned to the loading point F i The number of k-th type of shovel-loading equipment;

[0024] Step 2.3: Determine the target rock collection volume L for each unloading point in this shift j and the maximum rock recovery U j ;

[0025] Step 2.4: Automatically calculate the minimum rock output of each loading point in this shift The calculation formula is as follows:

[0026]

[0027] The rock output of this shift at the loading point should not be less than the ratio of the remaining rock volume to the remaining shifts, ensuring that the remaining rock volume can be completed within the remaining time;

[0028] Step 2.5: Automatically calculate the upper limit of rock output at each loading point in this shift The calculation formula is as follows:

[0029]

[0030] The amount of rock unloaded during the current shift at the loading point should not exceed the upper limit of the working capacity of the assigned shovel-loading equipment during the current shift, nor exceed the unfinished amount of the long-term plan for the loading point.

[0031] The step 3 is specifically as follows:

[0032] Step 3.1, the rock output constraint of the loading point ensures that the rock output of the loading point in this shift is between the minimum and maximum rock output:

[0033]

[0034] Step 3.2, the rock collection quantity constraint of the unloading point ensures that the rock collection quantity of the unloading point in this shift is between the target rock collection quantity and the maximum rock collection quantity:

[0035]

[0036] Step 3.3, objective function, minimizing the transport work is used as the objective function:

[0037]

[0038] The step 4 is specifically as follows:

[0039] Step 4.1, determine the individual gene encoding method and plan the transport volume X ij Stored as individual genes in a matrix format;

[0040] Step 4.2, determine the individual fitness function, based on the transport work The inverse of is used as the individual fitness function;

[0041] Step 4.3, determine the selection operator, use the tournament selection method to select individuals with higher fitness;

[0042] Step 4.4, determine the crossover operator, use the single-point crossover operation, generate new individuals in the population crossover stage while retaining the good characteristics of the parent generation;

[0043] Step 4.5, determine the mutation operator, randomly change some elements in the individual genes, increase the diversity of the population, and avoid falling into the local optimum;

[0044] Step 4.6, algorithm execution, creates a population of a certain size while ensuring that the genes of all individuals meet all constraints, performs selection, crossover, and mutation operations, and outputs the optimal solution as the rock removal plan for this shift after continuous iterative optimization.

[0045] The step 5 is specifically as follows:

[0046] Step 5.1, calculate the loading time of a truck at each loading point:

[0047]

[0048] Step 5.2, calculate the loading point F i The minimum distance between two vehicles loaded at without queuing:

[0049]

[0050] Step 5.3, calculate the loading point F i The upper limit of vehicles on the path between each unloading point with planned transportation volume:

[0051]

[0052] δ(x) is a piecewise function, which takes the value 1 when x is greater than 0 and takes the value 0 when x is less than or equal to 0.

[0053] The number of sections that can be divided for a two-lane road is calculated by dividing the transport distance by two times the interval. The number of sections is the upper limit of vehicle capacity. If a loading point needs to serve vehicles from multiple routes, the number of sections for each route must be divided by the total number of routes served by the loading point to prevent vehicles from multiple routes from requesting shovel loading equipment services at the same time.

[0054] Step 5.4, calculate the lower limit of vehicles on the path between the loading point and each unloading point with planned transportation volume:

[0055]

[0056] Based on the planned transport volume, truck capacity and truck transport cycle, calculate the lower limit of vehicles that can complete the planned transport volume within the shift duration and round it up;

[0057] Step 5.5, refer to the calculated upper and lower limits of vehicles and manually allocate the number of vehicles according to the actual situation of the fleet.

[0058] The step 6 is specifically as follows:

[0059] Step 6.1: Count the actual rock output from each loading point during the shift

[0060] Step 6.2, update the completed rock production and completed work time in the long-term plan:

[0061]

[0062] T completed =T completed +T.

[0063] The step 7 is specifically as follows:

[0064] Step 7.1: If the rock output of all loading points is greater than or equal to the long-term rock output target or the completed working time is greater than or equal to the long-term total working time, then the process ends; otherwise, jump to step 7.2;

[0065] Step 7.2, if there is a loading point whose rock output is greater than or equal to the long-term rock output target, set the rock output value of the eligible loading point to the long-term rock output target value to prevent negative planned transportation volume in the calculation of the next shift, and jump to step 2 for the next shift; otherwise, jump directly to step 2 for the next shift.

[0066] Beneficial effects of the present invention:

[0067] The traditional method does not consider the equipment problem in the planning stage, while the present invention significantly improves the resource utilization rate and avoids the resource waste problem existing in the traditional method by considering the binding relationship between the loading point and the unloading point, as well as the excavator loading speed, vehicle load and speed and other key factors affecting the rock removal efficiency and cost; at the same time, through the allocation of equipment and the reasonable vehicle-to-shovel ratio generated according to the planned quantity, combined with the short-term shift rock removal optimization plan, it effectively reduces the non-productive operation time and reduces the transportation cost. In addition, real-time data statistics ensure the accurate monitoring of the plan progress. At the same time, it also provides a reference for the plan of the next shift, realizes dynamic adjustment, greatly improves the overall operation efficiency of the mine, and realizes the scientific management of the rock removal plan.

[0068] The present invention is aimed at the complex environment and transportation tasks with multiple loading points and unloading points. The method of the present invention realizes the reasonable allocation of resources through the binding relationship between loading points and unloading points and the analysis of the working capacity of excavators and transportation vehicles. The rock discharge volume of each loading point is dynamically adjusted strictly according to the equipment capacity and long-term plan progress to ensure that the task is completed within the specified shift and avoid equipment overload or idleness. The core advantage of the present invention lies in the application of evolutionary algorithms, which automatically generates the optimal rock discharge plan with the goal of minimizing transportation work, reducing non-productive operation time. Through reasonable vehicle-to-shovel ratio calculation, the matching efficiency of shovel loading equipment and transportation vehicles is improved, and vehicle queuing and resource waste are avoided. The real-time data feedback mechanism ensures the accurate execution of each shift task and provides a reliable basis for the adjustment of subsequent shift plans. In practical applications, this method effectively optimizes the operation process, greatly improves the efficiency of mine operations, and provides mining companies with a scientific and efficient rock discharge management solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 is a flow chart of the method of the present invention.

[0070] Figure 2 It is the rock removal plan result diagram of the present invention.

[0071] Figure 3 It is a result diagram of the fixed shovel and vehicle matching of the present invention.

[0072] Figure 4 It is a diagram showing the equipment monitoring effect of the present invention. DETAILED DESCRIPTION

[0073] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0074] like Figure 1 As shown, a method for optimizing long-term and short-term rock removal in a mining process;

[0075] Variable definition: Assume that there are m rock loading points and n rock unloading points, respectively represented by F i(i=1,2,3,……,m) and T j (j=1,2,3,……,n) means, D ij For loading point F i To unloading point T j The average truck load is C truck , average driving speed V truck , average unloading time T unload .

[0076] The specific steps include:

[0077] Step 1: Determine the long-term rock removal plan and determine the relevant conditions of the long-term rock removal plan according to actual production needs;

[0078] Specifically include the following:

[0079] Step 1.1: Determine the long-term rock output target P i , representing the loading point F i The total amount of rock discharge is expected in the long term.

[0080] Step 1.2, determine the total working time T total , indicating the total working time of the equipment in the long term.

[0081] Step 1.3, determine the binding relationship matrix B ij , representing the loading point F i With unloading point T j The value is 1 or 0, indicating whether there is a binding relationship. i With unloading point T j If there is no binding relationship, it means the mounting point F i The rock cannot be transported to the unloading point T j .

[0082] Step 1.4, determine the distance matrix D ij , representing the loading point F i With unloading point T j The transportation distance between them.

[0083] Step 1.5, the rock output of each loading point is set to A i , the long-term completed work duration is T completed , are initially set to 0.

[0084] Step 2: Determine the relevant conditions for the short-term plan of this shift based on actual production needs;

[0085] Specifically include the following:

[0086] Step 2.1: Manually input the working time T of the current shift and automatically calculate the number of remaining shifts B in the long termremaining , the calculation formula is as follows:

[0087]

[0088] Step 2.2, assign shovels to each loading point in this shift manually, including C k With N ik , respectively represent the working capacity of the kth shovel loading equipment and the capacity assigned to the loading point F i The number of k-th type of shovel-loading equipment;

[0089] Step 2.3: Determine the target rock collection volume L for each unloading point in this shift j and the maximum rock recovery U j ;

[0090] Step 2.4: Automatically calculate the minimum rock output of each loading point in this shift The calculation formula is as follows:

[0091]

[0092] The rock output of this shift at the loading point should not be less than the ratio of the remaining rock volume to the remaining shifts, ensuring that the remaining rock volume can be completed within the remaining time;

[0093] Step 2.5: Automatically calculate the upper limit of rock output at each loading point in this shift The calculation formula is as follows:

[0094]

[0095] The amount of rock unloaded during the current shift at the loading point should not exceed the upper limit of the working capacity of the assigned shovel-loading equipment during the current shift, nor exceed the unfinished amount of the long-term plan for the loading point.

[0096] Step 3: Construct a rock removal optimization model with variable X ij Represents loading point F i To each unloading point T j Planned rock transportation volume; quantify the planned transportation volume from the loading point to the unloading point, and also serve as the genetic code of individuals in the evolutionary algorithm to facilitate the optimization operation of the evolutionary algorithm;

[0097] Specifically include the following:

[0098] Step 3.1, the rock output constraint of the loading point ensures that the rock output of the loading point in this shift is between the minimum and maximum rock output:

[0099]

[0100] Step 3.2, the rock collection quantity constraint of the unloading point ensures that the rock collection quantity of the unloading point in this shift is between the target rock collection quantity and the maximum rock collection quantity:

[0101]

[0102] Step 3.3, objective function, minimizing the transport work is used as the objective function:

[0103]

[0104] Step 4: Generate the shift plan, using the evolutionary algorithm to generate the shift plan; the evolutionary algorithm quickly generates a plan that meets all constraints and minimizes the transportation work target, thereby improving efficiency and reducing transportation costs;

[0105] The specific steps include:

[0106] Step 4.1, determine the individual gene encoding method and plan the transport volume X ij Stored as individual genes in a matrix format;

[0107] Step 4.2, determine the individual fitness function, based on the transport work The inverse of is used as the individual fitness function;

[0108] Step 4.3, determine the selection operator, use the tournament selection method to select individuals with higher fitness;

[0109] Step 4.4, determine the crossover operator, use the single-point crossover operation, generate new individuals in the population crossover stage while retaining the good characteristics of the parent generation;

[0110] Step 4.5, determine the mutation operator, randomly change some elements in the individual gene (matrix), increase the diversity of the population, and avoid falling into the local optimum;

[0111] Step 4.6, algorithm execution, creates a population of a certain size while ensuring that the genes of all individuals meet all constraints, performs selection, crossover, and mutation operations, and outputs the optimal solution as the rock removal plan for this shift after continuous iterative optimization.

[0112] Step 5: Generate a reasonable vehicle-to-shovel ratio based on the planned transportation volume; optimize the utilization rate of equipment and minimize the number of equipment to reduce costs while meeting the transportation task;

[0113] The specific steps include:

[0114] Step 5.1, calculate the loading time of a truck at each loading point:

[0115]

[0116] Step 5.2, calculate the loading point F i The minimum distance between two vehicles loaded at without queuing:

[0117]

[0118] Step 5.3, calculate the loading point F i The upper limit of vehicles on the path between each unloading point with planned transportation volume:

[0119]

[0120] δ(x) is a piecewise function, which takes the value 1 when x is greater than 0 and takes the value 0 when x is less than or equal to 0.

[0121] The number of sections that can be divided for a two-lane road is calculated by dividing the transport distance by two times the interval. The number of sections is the upper limit of vehicle capacity. If a loading point needs to serve vehicles from multiple routes, the number of sections for each route must be divided by the total number of routes served by the loading point to prevent vehicles from multiple routes from requesting shovel loading equipment services at the same time.

[0122] Step 5.4, calculate the lower limit of vehicles on the path between the loading point and each unloading point with planned transportation volume:

[0123]

[0124] Based on the planned transport volume, truck capacity and truck transport cycle, calculate the lower limit of vehicles that can complete the planned transport volume within the shift duration and round it up;

[0125] Step 5.5, refer to the calculated upper and lower limits of vehicles and manually allocate the number of vehicles according to the actual situation of the fleet.

[0126] Step 6: Execute the shift plan and collect relevant data. Collect relevant data on the actual execution of the short-term plan of this shift to provide support for subsequent plan adjustment and optimization, establish an optimization feedback mechanism, and enhance flexibility and adaptability.

[0127] The specific steps include:

[0128] Step 6.1: Count the actual rock output from each loading point during the shift

[0129] Step 6.2, update the completed rock production and completed work time in the long-term plan:

[0130]

[0131] T completed =T completed +T

[0132] Step 7, make an end judgment:

[0133] Step 7.1, if the rock output of all loading points is greater than or equal to the long-term rock output target or the completed working time is greater than or equal to the long-term total working time, then end; otherwise jump to step 7.2.

[0134] Step 7.2, if there is a loading point whose rock output is greater than or equal to the long-term rock output target, set the rock output value of the eligible loading point to the long-term rock output target value to prevent negative planned transportation volume in the calculation of the next shift, and jump to step 2 for the next shift; otherwise, jump directly to step 2 for the next shift.

[0135] like Figure 2 As shown in the figure, after the short-term rock unloading plan is generated, the planned transportation volume from each loading point to each unloading point is obtained. In actual implementation, the rocks are weighed after being transported to the unloading point, and the system monitors and counts the actual completion volume of each planned transportation volume in the short-term plan of the shift;

[0136] like Figure 3 As shown in the figure, after generating a reasonable vehicle-shovel ratio, the staff will allocate the corresponding number of shovel equipment and transport vehicles to the corresponding loading points and unloading points to complete the short-term rock removal plan for this shift;

[0137] like Figure 4 As shown, during the execution of the rock removal plan, the status of the transport vehicles is monitored in real time to facilitate vehicle scheduling, improve transport efficiency and reduce transport costs.

[0138] The present invention significantly improves resource utilization and avoids the problem of resource waste in traditional methods by considering the binding relationship between loading points and unloading points, as well as key factors affecting rock removal efficiency and cost, such as excavator loading speed, vehicle load and speed; at the same time, through the allocation of equipment and a reasonable vehicle-to-shovel ratio generated according to the planned quantity, combined with the short-term shift rock removal optimization plan, it effectively reduces non-productive operation time and reduces transportation costs. The present invention can effectively reduce non-productive operation time and reduce costs in transportation operations. In addition, real-time data statistics ensure accurate monitoring of the planned progress. At the same time, it also provides a reference for the plan of the next shift, realizes dynamic adjustment, greatly improves the overall operation efficiency of the mine, and realizes the scientific management of the rock removal plan.

Claims

1. A method for optimizing long-term and short-term rock removal in a mining process, characterized in that: The steps include: Step 1: Determine the long-term rock removal plan and determine the relevant conditions of the long-term rock removal plan according to actual production needs; Step 2: Determine the relevant conditions for the short-term plan of this shift based on the actual production situation and the goals of the long-term plan; Step 3: Based on the relevant conditions determined in step 2, a short-term rock removal optimization model for this shift is constructed, with variable X ij Represents loading point F i To each unloading point T j Planned rock transport volume; Step 4, generating a rock removal plan for a shift, using an evolutionary algorithm to solve the optimization model and generate a short-term plan for this shift; Step 5, generating a reasonable vehicle-to-shovel ratio according to the short-term planned transportation volume of the current shift; Step 6, according to the vehicle-to-shovel ratio, configure a corresponding number of transport vehicles and shovel loading equipment to execute the short-term plan of this shift, and collect relevant data after actual execution; Step 7: Determine whether the long-term plan is completed based on the cumulative transportation volume and cumulative working hours of relevant data statistics. If not, jump to step 2 to proceed to the short-term planning stage of the next shift.

2. The method for optimizing long-term and short-term rock removal in mining according to claim 1, characterized in that: The step 1 is specifically as follows: Step 1.1: Determine the long-term rock output target P i , representing the loading point F i The total amount of rock discharge expected in the long term; Step 1.2, determine the total working time T total , indicating the total working time of the equipment in the long term; Step 1.3, determine the binding relationship matrix B ij , representing the loading point F i With unloading point T j The binding relationship is 1 or 0, indicating whether there is a binding relationship. If the mounting point F i With unloading point T j If there is no binding relationship, it means the mounting point F i The rock cannot be transported to the unloading point T j ; Step 1.4, determine the distance matrix D ij , representing the loading point F i With unloading point T j Transportation distance between Step 1.5, the rock output of each loading point is set to A i , the long-term completed work duration is T completed , are initially set to 0.

3. The method for optimizing long-term and short-term rock removal in mining according to claim 2, characterized in that: The step 2 is specifically as follows: Step 2.1: Manually input the working time T of the current shift and automatically calculate the number of remaining shifts B in the long term remaining , the calculation formula is as follows: Step 2.2, assign shovels to each loading point in this shift manually, including C k With N ik , respectively represent the working capacity of the kth shovel loading equipment and the capacity assigned to the loading point F i The number of k-th type of shovel-loading equipment; Step 2.3: Determine the target rock collection volume L for each unloading point in this shift j and the maximum rock recovery U j ; Step 2.4: Automatically calculate the minimum rock output of each loading point in this shift The calculation formula is as follows: The rock output of this shift at the loading point should not be less than the ratio of the remaining rock volume to the remaining shifts, ensuring that the remaining rock volume can be completed within the remaining time; Step 2.5: Automatically calculate the upper limit of rock output at each loading point in this shift The calculation formula is as follows: The amount of rock unloaded during the current shift at the loading point should not exceed the upper limit of the working capacity of the assigned shovel-loading equipment during the current shift, nor exceed the unfinished amount of the long-term plan for the loading point.

4. The method for optimizing long-term and short-term rock removal in mining according to claim 3 is characterized in that: The step 3 is specifically as follows: Step 3.1, the rock output constraint of the loading point ensures that the rock output of the loading point in this shift is between the minimum and maximum rock output: Step 3.2, the rock collection quantity constraint of the unloading point ensures that the rock collection quantity of the unloading point in this shift is between the target rock collection quantity and the maximum rock collection quantity: Step 3.3, objective function, minimizing the transport work is used as the objective function:

5. The method for optimizing long-term and short-term rock removal in mining according to claim 4, characterized in that: The step 4 is specifically as follows: Step 4.1, determine the individual gene encoding method and plan the transport volume X ij Stored as individual genes in a matrix format; Step 4.2, determine the individual fitness function, based on the transport work The inverse of is used as the individual fitness function; Step 4.3, determine the selection operator, use the tournament selection method to select individuals with higher fitness; Step 4.4, determine the crossover operator, use the single-point crossover operation, generate new individuals in the population crossover stage while retaining the good characteristics of the parent generation; Step 4.5, determine the mutation operator, randomly change some elements in the individual genes, increase the diversity of the population, and avoid falling into the local optimum; Step 4.6, algorithm execution, creates a population of a certain size while ensuring that the genes of all individuals meet all constraints, performs selection, crossover, and mutation operations, and outputs the optimal solution as the rock removal plan for this shift after continuous iterative optimization.

6. The method for optimizing long-term and short-term rock removal in mining according to claim 5, characterized in that: The step 5 is specifically as follows: Step 5.1, calculate the loading time of a truck at each loading point: Step 5.2, calculate the loading point F i The minimum distance between two vehicles loaded at without queuing: Step 5.3, calculate the loading point F i The upper limit of vehicles on the path between each unloading point with planned transportation volume: δ(x) is a piecewise function, which takes the value 1 when x is greater than 0 and takes the value 0 when x is less than or equal to 0; The number of sections that can be divided for a two-lane road is calculated by dividing the transport distance by two times the interval. The number of sections is the upper limit of vehicle capacity. If a loading point needs to serve vehicles from multiple routes, the number of intervals of each route should be divided by the total number of routes served by the loading point to prevent vehicles from multiple routes from requesting shovel loading equipment services at the same time. Step 5.4, calculate the lower limit of vehicles on the path between the loading point and each unloading point with planned transportation volume: Based on the planned transport volume, truck capacity and truck transport cycle, calculate the lower limit of vehicles that can complete the planned transport volume within the shift duration and round it up; Step 5.5, refer to the calculated upper and lower limits of vehicles and manually allocate the number of vehicles according to the actual situation of the fleet.

7. The method for optimizing long-term and short-term rock removal in mining according to claim 6, characterized in that: The step 6 is specifically as follows: Step 6.1: Count the actual rock output from each loading point during the shift Step 6.2, update the completed rock production and completed work time in the long-term plan: T completed =T completed +T。 8. The method for optimizing long-term and short-term rock removal in mining according to claim 7, characterized in that: The step 7 is specifically as follows: Step 7.1: If the rock output of all loading points is greater than or equal to the long-term rock output target or the completed working time is greater than or equal to the long-term total working time, then the process ends; otherwise, jump to step 7.2; Step 7.2: If there is a loading point whose rock output is greater than or equal to the long-term rock output target, set the rock output value of the loading point that meets the conditions to the long-term rock output target value to prevent negative planned transportation volume from occurring in the calculation of the next shift, and jump to step 2 for the next shift; Otherwise, jump directly to step 2 for the next shift.

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