Mining area vehicle loading scheduling method based on minimum waiting time and earliest loading time

Abstract

The invention relates to a mining area vehicle loading scheduling method based on the minimum waiting time and the earliest loading time, the minimum waiting time and the earliest loading time of a transport vehicle are combined, a loading scheduling plan is generated when unloading of the transport vehicle is completed, and compared with a scheduling plan which is solved in advance, the mining area vehicle loading scheduling method has the advantages that timeliness is better; it is guaranteed that the transport vehicles are preferentially dispatched to the excavator corresponding to the marshalling where the transport vehicles are located, and meanwhile the excavator is supported to actively apply for the specific number of transport vehicles. As the predicted latest arrival time and the actual latest arrival time of the transport vehicle are recorded at each excavator point, the predicted latest arrival time and the actual latest arrival time of the transport vehicle can be updated during each loading and unloading, and when a driver of the transport vehicle does not load according to a scheduling plan, but after the next unloading is finished, the transport vehicle is not required to be loaded according to the scheduling plan. According to the method, the loading scheduling plan can be correctly generated, the influence of manual non-compliance operation can be quickly eliminated, the loading scheduling problem of the transportation vehicles in the mining area is simply and efficiently solved, and the waiting time of the transportation vehicles and the excavator is effectively shortened.

Description

Technical Field

[0001] The invention relates to a mining area vehicle loading scheduling method based on minimum waiting and earliest loading time, belonging to the technical field of vehicle loading scheduling. Background Art

[0002] In a common mining vehicle management system, there are multiple transport fleets, which belong to multiple transport companies. Because the transportation cost settlement is based on the transport company, different transport fleets will not work together in the mining area. Each transport fleet is divided into multiple transport groups. Each transport group will be bound to a unloading point, multiple excavators and multiple transport vehicles. Each unloading point can be bound to one or more transport groups, each excavator can only be bound to one transport group, and each transport vehicle can only be bound to one transport group. Since the output and billing are counted when unloading, the transport vehicle will return to the unloading point corresponding to its own transport group for unloading after loading the ore from the excavator. Therefore, this method solves the scheduling problem of which excavator point the transport vehicle should go to for loading after unloading.

[0003] There are three mainstream methods for the above-mentioned mining vehicle loading and scheduling problem. The first method is a simulation method, which uses discrete event simulation to evaluate the pros and cons of the predetermined scheduling plan based on a series of indicators such as the vehicle load, empty speed limit, heavy speed limit, unloading efficiency, excavator loading efficiency, and driving path. The second method is to establish a mathematical model for the vehicle loading and scheduling problem, and then use various general algorithms to solve the mathematical model. The third method is based on reinforcement learning. A reinforcement learning environment is written for the vehicle loading and scheduling problem, and appropriate states, actions, rewards, and reinforcement learning algorithms are selected to train a vehicle loading and scheduling model, and then the model is used for reasoning. Summary of the invention

[0004] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a mining vehicle loading scheduling method based on minimum waiting and earliest loading time, which generates a loading scheduling plan when the transport vehicle is unloaded. It is more timely than solving the scheduling plan in advance, and ensures that the transport vehicle is preferentially scheduled to the excavator corresponding to its own formation, and at the same time supports the excavator to actively apply for a specific number of transport vehicles.

[0005] The present invention is implemented by the following technical solution: a mining area vehicle loading scheduling method based on minimum waiting and earliest loading time comprises the following steps: Step 1: Monitor the unloading action of the transport vehicle in real time. When the transport vehicle is unloaded, traverse the latest arrival time of the transport vehicle stored in all excavator points, delete the latest arrival time matching the transport vehicle, and execute step 2; Step 2: Calculate the estimated queuing time of the transport vehicle to all excavator points in the same transport group, obtain the minimum queuing time, and determine whether the minimum value is greater than 0. If it is greater than 0, execute step 5, otherwise execute step 3; Step 3: According to the estimated queuing time of the transport vehicle to all excavator points in the same transport group calculated in step 2, find the excavator point and path with a queuing time of 0, and execute step 4; Step 4: Calculate the earliest loading time of the transport vehicle at the excavator point with a queue time of 0, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 5: Determine whether the number of transport vehicles actively applied for by the excavator point is greater than 0. If it is greater than 0, execute step 10; otherwise, execute step 6; Step 6: Calculate the estimated queuing time of the transport vehicle to all excavator points of different transport marshalings in the same fleet, obtain the minimum queuing time, and determine whether the minimum value is greater than 0. If it is greater than 0, execute step 9, otherwise execute step 7; Step 7: Based on the estimated queuing time of the transport vehicle to all excavator points of different transport marshalings in the same fleet calculated in step 6, find the excavator point and path with a queuing time of 0, and execute step 8; Step 8: Calculate the earliest loading time of the transport vehicle at the excavator point with a queue time of 0, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 9: Calculate the earliest loading time of all excavator points of the transport vehicle in different transport groups in the same fleet, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 10: The excavator point with the number of actively applied transport vehicles greater than 0 is used as the optional excavator point for loading scheduling, and the number of actively applied transport vehicles corresponding to the optional excavator point is used as the priority of loading scheduling, and step 11 is executed; Step 11: Calculate the estimated queuing time from the transport vehicle to the optional excavator point, find the excavator point with the shortest estimated queuing time and the highest priority, and execute step 12; Step 12: Determine whether the number of excavator points obtained in step 11 is greater than 1. If so, execute step 13; otherwise, execute step 14. Step 13: Calculate the earliest loading time of the transport vehicle corresponding to the excavator point in step 11, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 14: Use the excavator point and path obtained in step 11 as a loading scheduling plan and execute step 15; Step 15: Calculate the estimated latest arrival time of the transport vehicle at the target excavator point of the loading scheduling plan, and update the latest arrival time with the estimated latest arrival time, and execute step 16; Step 16: Update the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan. If the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan is greater than 0, the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan is reduced by 1, otherwise it is not processed and step 17 is executed; Step 17: Monitor the movement of the transport vehicle to the excavation point. When the transport vehicle arrives at the excavation point, update the latest arrival time of the transport vehicle at the excavation point with the actual arrival time of the transport vehicle at the excavation point, and execute step 1 to realize the real-time scheduling function of transport vehicle loading.

[0006] The step 1 uses a map and a list to simulate the storage of excavation points and transport vehicle information. The map of the excavation points is traversed through an outer loop, and the list of transport vehicles corresponding to each excavation point is traversed through an inner loop. When a transport vehicle with a vehicle identification equal to the target vehicle ID is found, the latest arrival time matching the transport vehicle is deleted from the list.

[0007] The beneficial effects of the present invention are as follows: the method of the present invention combines the minimum waiting time and the earliest loading time of the transport vehicle, and generates a loading scheduling plan when the transport vehicle is unloaded. This is more timely than solving the scheduling plan in advance, ensuring that the transport vehicle is preferentially scheduled to the excavator corresponding to its own formation, and supporting the excavator to actively apply for a specific number of transport vehicles. Since the estimated latest arrival time and the actual latest arrival time of the transport vehicle are recorded at each excavator point, the estimated latest arrival time and the actual latest arrival time of the transport vehicle will be updated for each loading and unloading. When the transport vehicle driver does not load according to the scheduling plan, but after the next unloading is completed, the method of the present invention can still correctly generate a loading scheduling plan, can quickly eliminate the impact of non-compliant human operations, and simply and efficiently solve the problem of loading scheduling of transport vehicles in mining areas, effectively reduce the waiting time of transport vehicles and excavators, and improve the output of mining areas. It is suitable for complex and changeable mining environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The present invention is further described below with reference to the accompanying drawings and embodiments.

[0009] Figure 1 It is a flow chart of the loading scheduling algorithm of the present invention. DETAILED DESCRIPTION

[0010] like Figure 1 The mining area vehicle loading scheduling method based on minimum waiting time and earliest loading time shown in the figure comprises the following steps: Step 1: Monitor the unloading action of the transport vehicle in real time. When the transport vehicle is unloaded, traverse the latest arrival time of the transport vehicle stored in all excavator points, delete the latest arrival time matching the transport vehicle, and execute step 2; Step 2: Calculate the estimated queuing time of the transport vehicle to all excavator points in the same transport group, obtain the minimum queuing time, and determine whether the minimum value is greater than 0. If it is greater than 0, execute step 5, otherwise execute step 3; Step 3: According to the estimated queuing time of the transport vehicle to all excavator points in the same transport group calculated in step 2, find the excavator point and path with a queuing time of 0, and execute step 4; Step 4: Calculate the earliest loading time of the transport vehicle at the excavator point with a queue time of 0, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 5: Determine whether the number of transport vehicles actively applied for by the excavator point is greater than 0. If it is greater than 0, execute step 10; otherwise, execute step 6; Step 6: Calculate the estimated queuing time of the transport vehicle to all excavator points of different transport marshalings in the same fleet, obtain the minimum queuing time, and determine whether the minimum value is greater than 0. If it is greater than 0, execute step 9, otherwise execute step 7; Step 7: Based on the estimated queuing time of the transport vehicle to all excavator points of different transport marshalings in the same fleet calculated in step 6, find the excavator point and path with a queuing time of 0, and execute step 8; Step 8: Calculate the earliest loading time of the transport vehicle at the excavator point with a queue time of 0, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 9: Calculate the earliest loading time of all excavator points of the transport vehicle in different transport groups in the same fleet, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 10: The excavator point with the number of actively applied transport vehicles greater than 0 is used as the optional excavator point for loading scheduling, and the number of actively applied transport vehicles corresponding to the optional excavator point is used as the priority of loading scheduling, and step 11 is executed; Step 11: Calculate the estimated queuing time from the transport vehicle to the optional excavator point, find the excavator point with the shortest estimated queuing time and the highest priority, and execute step 12; Step 12: Determine whether the number of excavator points obtained in step 11 is greater than 1. If so, execute step 13; otherwise, execute step 14. Step 13: Calculate the earliest loading time of the transport vehicle corresponding to the excavator point in step 11, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 14: Use the excavator point and path obtained in step 11 as a loading scheduling plan and execute step 15; Step 15: Calculate the estimated latest arrival time of the transport vehicle at the target excavator point of the loading scheduling plan, and update the latest arrival time with the estimated latest arrival time, and execute step 16; Step 16: Update the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan. If the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan is greater than 0, the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan is reduced by 1, otherwise it is not processed and step 17 is executed; Step 17: Monitor the movement of the transport vehicle to the excavation point. When the transport vehicle arrives at the excavation point, update the latest arrival time of the transport vehicle at the excavation point with the actual arrival time of the transport vehicle at the excavation point, and execute step 1 to realize the real-time scheduling function of transport vehicle loading.

[0011] The step 1 uses a map and a list to simulate the storage of excavation points and transport vehicle information. The map of the excavation points is traversed through an outer loop, and the list of transport vehicles corresponding to each excavation point is traversed through an inner loop. When a transport vehicle with a vehicle identification equal to the target vehicle ID is found, the latest arrival time matching the transport vehicle is deleted from the list.

Claims

1. A mining vehicle loading scheduling method based on minimum waiting and earliest loading time, characterized in that: The steps include: Step 1: Monitor the unloading action of the transport vehicle in real time. When the transport vehicle is unloaded, traverse the latest arrival time of the transport vehicle stored in all excavator points, delete the latest arrival time matching the transport vehicle, and execute step 2; Step 2: Calculate the estimated queuing time of the transport vehicle to all excavator points in the same transport group, obtain the minimum queuing time, and determine whether the minimum value is greater than 0. If it is greater than 0, execute step 5, otherwise execute step 3; Step 3: According to the estimated queuing time of the transport vehicle to all excavator points in the same transport group calculated in step 2, find the excavator point and path with a queuing time of 0, and execute step 4; Step 4: Calculate the earliest loading time of the transport vehicle at the excavator point with a queue time of 0, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 5: Determine whether the number of transport vehicles actively applied for by the excavator point is greater than 0. If it is greater than 0, execute step 10; otherwise, execute step 6; Step 6: Calculate the estimated queuing time of the transport vehicle to all excavator points of different transport marshalings in the same fleet, obtain the minimum queuing time, and determine whether the minimum value is greater than 0. If it is greater than 0, execute step 9, otherwise execute step 7; Step 7: Based on the estimated queuing time of the transport vehicle to all excavator points of different transport marshalings in the same fleet calculated in step 6, find the excavator point and path with a queuing time of 0, and execute step 8; Step 8: Calculate the earliest loading time of the transport vehicle at the excavator point with a queue time of 0, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 9: Calculate the earliest loading time of all excavator points of the transport vehicle in different transport groups in the same fleet, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 10: The excavator point with the number of actively applied transport vehicles greater than 0 is used as the optional excavator point for loading scheduling, and the number of actively applied transport vehicles corresponding to the optional excavator point is used as the priority of loading scheduling, and step 11 is executed; Step 11: Calculate the estimated queuing time from the transport vehicle to the optional excavator point, find the excavator point with the shortest estimated queuing time and the highest priority, and execute step 12; Step 12: Determine whether the number of excavator points obtained in step 11 is greater than 1. If so, execute step 13; otherwise, execute step 14. Step 13: Calculate the earliest loading time of the transport vehicle corresponding to the excavator point in step 11, find the excavator point and path corresponding to the minimum value of the earliest loading time, and generate a loading scheduling plan based on the excavator point and path, and execute step 15; Step 14: Use the excavator point and path obtained in step 11 as a loading scheduling plan and execute step 15; Step 15: Calculate the estimated latest arrival time of the transport vehicle at the target excavator point of the loading scheduling plan, and update the latest arrival time with the estimated latest arrival time, and execute step 16; Step 16: Update the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan. If the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan is greater than 0, the number of transport vehicles actively applied for by the target excavator point in the loading scheduling plan is reduced by 1, otherwise it is not processed and step 17 is executed; Step 17: Monitor the movement of the transport vehicle to the excavation point. When the transport vehicle arrives at the excavation point, update the latest arrival time of the transport vehicle at the excavation point with the actual arrival time of the transport vehicle at the excavation point, and execute step 1 to realize the real-time scheduling function of transport vehicle loading.

2. The method for scheduling vehicle loading in a mining area based on minimum waiting time and earliest loading time according to claim 1, characterized in that: The step 1 uses a map and a list to simulate the storage of excavation points and transport vehicle information. The map of the excavation points is traversed through an outer loop, and the list of transport vehicles corresponding to each excavation point is traversed through an inner loop. When a transport vehicle with a vehicle identification equal to the target vehicle ID is found, the latest arrival time matching the transport vehicle is deleted from the list.

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