A strategy shift engineered slagging scheduling method

Abstract

The present application belongs to the field of engineering transportation, and specifically provides an engineering slag discharge scheduling method for strategy conversion, comprising: real-time data acquisition and dynamic monitoring; initially selecting the nearest slag field of the section and initially equipping the number of slag soil trucks of each section; identifying the leading section and the lagging section, and adjusting the scheduling scheme of the lagging section; detecting the interruption event in real time, then identifying the full-link bottleneck, and distributing the loading weight, transportation weight and unloading weight of the adjusted transportation line according to the full-link bottleneck identification result; establishing a path matching degree model, and selecting the adjusted path according to the path matching degree; scheduling the vehicles on each path, and preferentially making up the slag discharge gap of the lagging section; when the interruption event is solved, each section returns to the initial path for slag discharge, and the vehicles are recovered or re-distributed for the sections that have caught up with the progress. The method dynamically optimizes the scheduling scheme in response to the sudden events in the transportation process, and meets the slag discharge intensity guarantee for engineering construction.

Description

Technical Field

[0001] This invention belongs to the field of engineering transportation, and specifically relates to a method for scheduling engineering slag removal based on a strategy shift. Background Technology

[0002] Large-scale engineering projects are characterized by large volumes of earthwork excavation and high intensity of waste transportation. The excavation intensity is high, and the amount of waste is enormous, with numerous and scattered waste disposal sites. Even after the project itself handles the waste, a huge amount remains to be disposed of, posing significant challenges in land acquisition and resettlement, and potentially triggering a series of environmental protection and soil and water conservation issues. Therefore, to properly address the waste disposal problem, it is necessary to carefully select waste disposal sites, plan waste transportation routes, and optimize the allocation of waste, especially optimizing transportation routes and scheduling methods to ensure construction progress.

[0003] Existing technologies can be mainly categorized as follows: First, those focusing on vehicle scheduling. For example, CN114781874A provides a method for scheduling transport vehicles, establishing a relationship between departure time and vehicle parameters to obtain the target departure interval time, thus improving transportation efficiency. CN113988424A constructs a dual-optimization model for cyclical transportation tasks in trunk logistics networks. These technologies concentrate on improving the utilization rate of vehicles themselves, making full use of transportation resources to achieve optimization goals. Second, those focusing on complex transportation scheduling tasks. For example, CN119338216A provides an artificial intelligence-based vehicle scheduling management method and system for high-frequency, multi-task scenarios such as urban delivery and express logistics. CN113837495A uses a multi-stage optimization-based logistics trunk transportation scheduling optimization method to improve the rationality of logistics optimization scheduling schemes. These technologies aim to improve the optimization rationality of complex tasks, solving problems such as low collaboration efficiency and inaccurate path planning in complex tasks through task decomposition. Thirdly, emphasis is placed on transportation continuity. For example, CN112132478A provides a muck truck transportation management system that collects data on the quantity of earthwork or muck loading and unloading points, and formulates reasonable transportation routes based on the quantity of earthwork extracted and accumulated at loading points. CN118333367A provides a configuration method and system for electric muck trucks in tunnels that considers driving range, optimizing the use of electric muck trucks in tunnel construction by taking into account their mileage impact, thereby improving construction efficiency and reducing environmental impact. These technologies differ from logistics transportation and are primarily used in engineering construction to ensure construction continuity. Overall, existing technologies suffer from common problems such as insufficient adaptability to dynamic environments, reliance on static data or assumptions of stable environments, and difficulty in coping with sudden changes (such as traffic congestion or equipment failure). Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a strategy-shifting engineering slag discharge scheduling method, which dynamically optimizes the scheduling scheme in response to emergencies during transportation to ensure the slag discharge intensity meets the requirements of engineering construction.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a strategy-shifting engineering slag discharge scheduling method, comprising the following steps:

[0006] Step 1: Real-time data acquisition and dynamic monitoring;

[0007] Step 2: Set up the initial scheduling plan: Based on the distance between the contract section and the slag yard, initially select the slag yard closest to the contract section, and initially allocate the number of dump trucks for each contract section;

[0008] Step 3: Determine the construction progress of each section: Compared with the slag removal plan, identify the sections that are ahead of schedule and those that are behind schedule. No adjustments will be made to the sections that are ahead of schedule, and the scheduling plan will be adjusted for the sections that are behind schedule.

[0009] Step 4: Interruption Response and End-to-End Bottleneck Identification: Real-time detection of interruption events. If no interruption event occurs, proceed directly to Step 6. After an interruption event occurs, detect the interruption link in the transportation link and adjust the transportation route according to the interruption situation. Then, perform end-to-end bottleneck identification and allocate loading weight, transportation weight, and unloading weight of the adjusted transportation route according to the end-to-end bottleneck identification results.

[0010] Step 5: Establish a path matching degree model, select the adjusted path based on the path matching degree, and select the path with the high path matching degree as the adjusted path;

[0011] Step Six: Flexible Vehicle Scheduling and Dynamic Adjustment: Scheduling vehicles for each route, prioritizing the filling of slag removal gaps in lagging sections;

[0012] Step 7, Rolling Optimization and Resource Recovery: After the interruption event is resolved, each section returns to the initial path to transport waste, and steps 3 and 6 are executed to recover or redistribute vehicles for sections that have caught up with the schedule.

[0013] In the preferred embodiment, step one includes real-time collection of actual and planned slag discharge volume for each section, data on the status of slag trucks, and data on road traffic capacity.

[0014] In the preferred embodiment, in step three, if the actual slag discharge intensity of a certain section is greater than the planned slag discharge intensity, then the section is considered an advanced section; if the actual slag discharge intensity of a certain section is less than the planned slag discharge intensity, then the section is considered a lagging section.

[0015] In the preferred embodiment, in step three, the segment lag rate is used to determine the segment type. If the segment lag rate is greater than 0, it indicates that the segment is an advanced segment; if the segment lag rate is less than 0, it indicates that the segment is a lagging segment.

[0016] The formula for calculating the section lag rate is:

[0017] (1);

[0018] in, To plan the amount of slag removed, , where i represents the actual slag output and i represents the standard section.

[0019] In the preferred embodiment, in step four, the interruption event includes sudden events that cause the transportation link to fail completely or partially, including road collapses, vehicle breakdowns, natural disasters, and temporary control measures. If the target slag yard cannot be reached, a slag yard or temporary storage area of ​​the same type is selected according to priority, and the vehicles that have not yet departed on the interrupted route are reassigned to other routes or sections.

[0020] In the preferred embodiment, the full bottleneck identification coefficient is calculated in step four as follows:

[0021] (2);

[0022] Where B represents the bottleneck identification coefficient; j is the road number; and k is the slag yard or material yard. The road congestion coefficient represents the ratio of the number of vehicles passing through to the maximum capacity of the road. Let i be the loading rate of section i. This represents the maximum theoretical loading rate for section i. Let k be the unloading rate of the slag yard. Let k be the maximum theoretical unloading rate of the slag yard.

[0023] In the preferred embodiment, the formula for calculating the total bottleneck identification coefficient includes: , , Of the three values, if Minimum indicates that the bottleneck of the entire supply chain is the loading efficiency. Minimum indicates that the bottleneck of the entire link is transportation efficiency. The minimum value indicates that the bottleneck in the entire chain is unloading efficiency, and the weight of the bottleneck link needs to be set higher than the weights of the other two links.

[0024] In the preferred embodiment, in step five, the path matching degree model expression is:

[0025] (3);

[0026] ;

[0027] in, This represents the path matching degree corresponding to the route from section i to slag yard k; j is the road number, and k is the slag yard or material yard. α is the road congestion coefficient, representing the ratio of passing vehicles to the maximum road capacity; α is the loading weight, β is the transportation weight, and γ is the unloading weight.

[0028] In the preferred embodiment, in step six, if additional vehicles are needed for the lagging section, and there are no sections with changed routes, the formula for calculating the additional vehicles needed for the transportation route is as follows:

[0029] (4);

[0030] When the calculated number of additional vehicles is not an integer, it is rounded up.

[0031] In the preferred embodiment, in step six, if the route has been changed due to an interruption event, the calculation formula for adding vehicles to the changed transportation route is as follows:

[0032] (5);

[0033] or, (6);

[0034] When the calculated number of additional vehicles is not an integer, it is rounded up.

[0035] The efficiency improvement is calculated as the ratio of the transportation efficiency of the changed route to the transportation efficiency of the original route, minus 1.

[0036] The reduction in efficiency is calculated as: 1 minus the ratio of the transportation efficiency of the changed route to the transportation efficiency of the original route.

[0037] The engineering slag discharge scheduling method based on strategy shift provided by this invention has the following beneficial effects:

[0038] 1. By fully integrating the "loading-transporting-unloading" process in the slag removal process, the slag is transformed from a "static transportation task" into a "dynamic resource flow," ensuring the continuity of construction.

[0039] 2. Effectively respond to emergencies during the transportation of slag from the project, avoid global delays caused by local problems, minimize transportation and time costs, and meet the actual needs of the project. Attached Figure Description

[0040] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0043] A method for scheduling engineering slag removal based on strategy shift includes the following steps:

[0044] Step 1: Real-time data collection and dynamic monitoring: This includes real-time collection of actual and planned slag discharge volumes for each section, data on the status of slag trucks, and data on road traffic capacity.

[0045] Real-time data collection includes actual and planned slag discharge volumes for each section, vehicle location, load, and empty / loaded status of dump trucks (via GPS and onboard sensors), as well as road capacity data.

[0046] Step 2: Set up the initial scheduling plan: Based on the distance between the contract section and the slag yard, initially select the slag yard closest to the contract section, and initially allocate the number of slag trucks for each contract section.

[0047] In this example, we focus on the third year of a project. The project has four spoil heaps (A, B, C, and D) and a backup storage yard (F). The earthwork excavation is divided into four sections. Each section corresponds to the nearest target spoil heap. Under normal circumstances, each section will dump spoil at the target spoil heap. The standard load capacity of each dump truck is a fixed value (50 m³ / truck), and the planned threshold is 95%. Specific information is shown in Tables 1 and 2.

[0048]

[0049]

[0050] Step 3: Judging the construction progress of each section: Compared with the slag removal plan, identify the sections that are ahead of schedule and those that are behind schedule. No adjustments will be made to the sections that are ahead of schedule, and the scheduling plan will be adjusted for the sections that are behind schedule.

[0051] If the actual slag discharge intensity of a certain section is greater than the planned slag discharge intensity, then the section is considered an advanced section. If the actual slag discharge intensity of a certain section is less than the planned slag discharge intensity, then the section is considered a lagging section.

[0052] The type of a bid section is determined by the bid section lag rate. A bid section lag rate greater than 0 indicates that the bid section is an advanced bid section, while a bid section lag rate less than 0 indicates that the bid section is a lagging bid section.

[0053] The formula for calculating the section lag rate is:

[0054] (1);

[0055] in, To plan the amount of slag removed, , where i represents the actual slag output and i represents the standard section.

[0056] The results of the delayed or advanced calculations for each section are shown in Table 3.

[0057]

[0058] Table 3 shows that the construction progress of Section 1 is ahead of schedule; the slag strength of Section 2 is 50% behind; the slag strength of Section 3 is 60% behind; and the slag strength of Section 4 is 50% behind.

[0059] Step 4: Interruption Response and End-to-End Bottleneck Identification: Real-time detection of interruption events. If no interruption event occurs, proceed directly to Step 6. After an interruption event occurs, detect the interruption link in the transportation link and adjust the transportation route according to the interruption situation. Then, perform end-to-end bottleneck identification and allocate loading weight, transportation weight, and unloading weight of the adjusted transportation route according to the end-to-end bottleneck identification results.

[0060] Disruption events include sudden events that cause complete or partial failure of the transportation link, including road collapses, vehicle breakdowns, natural disasters, and temporary control measures. If the target spoil disposal site cannot be reached, a spoil disposal site of the same type or a temporary storage area will be selected according to priority. Vehicles that have not yet departed on the interrupted route will be reassigned to other routes or sections.

[0061] If a sudden event such as a road collapse, vehicle breakdown, or natural disaster occurs during the transportation process, causing the transportation link to fail completely or partially, the system will detect the interruption event in real time through GPS, traffic monitoring, and equipment sensors (such as a sudden drop in road traffic rate to 0%). The system will prioritize switching to an emergency transportation route. If the target slag yard cannot be reached, the system will select a slag yard or temporary storage area of ​​the same type according to priority. Vehicles that have not yet departed on the interrupted route will be reassigned to other routes or sections.

[0062] Because of the mismatch in the "loading-transportation-unloading" process during construction, the efficiency of one link is significantly lower than that of others, resulting in a limited overall slag discharge rate. In this case, the bottleneck location is quantified by the full-link efficiency formula, and resources are dynamically adjusted for different bottlenecks. Any bottleneck in any link (such as slow loading, road congestion, or unloading backlog) will affect the overall efficiency. Therefore, the path matching degree model quantifies the status of each link to avoid mismatch with other links caused by overload of a single link (loading point, road, unloading point). For example, if more vehicles participate in transportation but the road is congested, it will reduce transportation efficiency.

[0063] Based on the actual needs of the project, different weights are assigned to loading efficiency (α), transportation smoothness (β), and unloading efficiency (γ). A route selection strategy guides vehicles to routes with higher efficiency for each stage. For example, if loading equipment in a certain section frequently malfunctions, the weight of α can be increased to prioritize routes with higher loading efficiency; if road congestion is frequent, the weight of β is increased to focus on routes with smoother traffic; if the unloading capacity of the slag yard is insufficient, the weight of γ is increased to avoid long queues of vehicles at the unloading point.

[0064] In this embodiment, the emergencies are shown in Table 4.

[0065]

[0066] Window 1, 7:00-11:00:

[0067] The closure of slag yard C directly affects section 3, causing a 60% lag in slag disposal intensity, requiring adjustments. Since slag yard C needs rectification and will temporarily suspend receiving slag, the candidate routes for P3 are P3-A, P3-B, P3-D, and P3-F, with a loading efficiency of 0.4 (200 / 500). The unloading efficiency is calculated based on the slag yard's maximum design rate.

[0068] The full bottleneck identification coefficient is calculated as follows:

[0069] (2);

[0070] Where B represents the bottleneck identification coefficient; j is the road number; and k is the slag yard or material yard. The road congestion coefficient represents the ratio of the number of vehicles passing through to the maximum capacity of the road. Let i be the loading rate of section i. This represents the maximum theoretical loading rate for section i. Let k be the unloading rate of the slag yard. Let k be the maximum theoretical unloading rate of the slag yard.

[0071] In the formula for calculating the total bottleneck identification coefficient, , , Of the three values, if Minimum indicates that the bottleneck of the entire supply chain is the loading efficiency. Minimum indicates that the bottleneck of the entire link is transportation efficiency. The minimum value indicates that the bottleneck in the entire chain is unloading efficiency, and the weight of the bottleneck link needs to be set higher than the weights of the other two links.

[0072] According to Formula 2, the bottleneck of the entire supply chain is loading efficiency, so it is given a greater weight. Higher loading efficiency results in a higher path matching degree. In this example, the loading weight, transportation weight, and unloading weight are set to 0.4, 0.3, and 0.3, respectively.

[0073] Step 5: Establish a path matching degree model, select the adjusted path based on the path matching degree, and choose the path with the high path matching degree as the adjusted path.

[0074] The path matching degree model expression is:

[0075] (3);

[0076] ;

[0077] in, This represents the path matching degree corresponding to the route from section i to slag yard k; j represents the road, and k represents the slag yard or material yard. α is the road congestion coefficient, representing the ratio of passing vehicles to the maximum road capacity; α is the loading weight, β is the transportation weight, and γ is the unloading weight.

[0078] The path matching degree is calculated according to Formula 3, as shown in Table 5:

[0079]

[0080] According to the path matching degree calculation results in Table 5, path P3-B has the highest path matching degree, so path P3-B can be selected for slag disposal.

[0081] Step Six: Flexible Vehicle Scheduling and Dynamic Adjustment: Scheduling vehicles for each route, prioritizing the filling of slag removal gaps in lagging sections.

[0082] This step achieves multi-objective collaboration, balancing progress, cost, and stability rather than a single optimal solution. By monitoring data in real time, scheduling strategies are automatically or semi-automatically adjusted to ensure balanced efficiency across the entire chain (loading-transportation-unloading).

[0083] For delayed sections requiring additional vehicles, if there are no sections with changed routes, the formula for calculating the additional vehicles needed for the transportation route is as follows:

[0084] (4).

[0085] If the route has been changed due to an interruption event, the formula for calculating the additional vehicles to be dispatched on the changed transportation route is as follows:

[0086] (5);

[0087] or, (6);

[0088] The efficiency improvement is calculated as the ratio of the transportation efficiency of the changed route to the transportation efficiency of the original route, minus 1.

[0089] The reduction in efficiency is calculated as: 1 minus the ratio of the transportation efficiency of the changed route to the transportation efficiency of the original route.

[0090] The original route P3-C has an actual capacity of 300 * 0.9 = 270 vehicles / hour and a transport capacity of 270 * 50 = 13,500 m³ / hour. The alternative route P3-B has an actual capacity of 700 * 0.5 = 350 vehicles / hour and a transport capacity of 350 * 50 = 17,500 m³ / hour. The actual transport efficiency is improved by 29.6%. Route efficiency directly affects the actual transport capacity of each vehicle; therefore, the following additional vehicles are needed:

[0091] ;

[0092] Therefore, the adjusted route requires an additional 5 vehicles.

[0093] Compared to simply adding more vehicles without changing the route (P3-C), which requires 6 vehicles to fill the gap, this algorithm, by fully considering the relationship between loading, unloading, and transportation, only requires 5 vehicles after optimization.

[0094] Since there were no unforeseen events, P2 and P4 continued to transport waste according to the overall construction layout (P2-B, P4-D). The number of additional vehicles was calculated based on road congestion using formula (4), as follows:

[0095] ;

[0096] ;

[0097] Therefore, P2 will receive 5 additional vehicles, and P4 will receive 3 additional vehicles.

[0098] Window 2, 11:00-13:00:

[0099] Status update: P2 has caught up with 1000m³ of progress, with 1500m³ remaining; P3 has caught up with 1000m³ of progress, with 500m³ remaining; P4 has caught up with 600m³ of progress, with 1400m³ remaining.

[0100] The main path P2-B is interrupted, requiring a re-selection of a path. Due to the ongoing renovation of slag yard C, the only candidate paths for P2 are P2-A, the detour path P2-B, P2-D, and P2-F. The loading efficiency is 1.33 (400 / 300), with loading efficiency being the bottleneck for each path. The loading weight, transportation weight, and unloading weight are set to 0.4, 0.3, and 0.3, respectively. The path matching degree is calculated according to Formula 3, as shown in Table 6.

[0101]

[0102] Based on the results in Table 6, the P2-B detour route is selected. The actual capacity of the original route P2-B is 600 * 0.6 = 360 vehicles / hour, and the transport capacity is 360 * 50 = 18,000 m³ / hour. The actual capacity of the alternative route is 400 * 0.6 = 240 vehicles / hour, and the transport capacity is 240 * 50 = 12,000 m³ / hour. Window 1 P2 increases to 5 vehicles. However, based on the calculation of the P2-B route, due to the reduced transport capacity of the detour route, the required number of vehicles is:

[0103] ;

[0104] The detour route has a capacity of 12,000 m³ / h, while the original route has a capacity of 18,000 m³ / h. The transportation efficiency decreases by (18,000 - 12,000) / 18,000 = 0.333. P2 originally had 3 vehicles, and window 1 adds 5 more, for a total of 8 vehicles. What is the number of vehicles required after the route adjustment? The original plan was for 12 vehicles, but due to the detour, transportation efficiency was reduced, so P2 needed to add 4 more vehicles.

[0105] Window 3, 13:00-15:00:

[0106] Status update: P2 has caught up with 1500m³ of progress, with 1000m³ remaining; P3 has caught up with the normal progress and can gradually release vehicle resources; P4 has caught up with 900m³ of progress, with 1100m³ remaining.

[0107] Rainfall across the region led to a decrease in road traffic efficiency, reducing Cj for all routes by 20%. Taking waste material transportation in Section 4 as an example, the slag yard C is undergoing renovation, and the candidate routes are P4-A, P4-B, P4-D, and P4-F. The bottleneck of the entire P4-B link is identified as transportation efficiency, therefore the weight coefficients are 0.3, 0.4, and 0.3, and the loading efficiency is 1.25 (250 / 200).

[0108]

[0109] Table 7 shows that route P4-B has the highest matching degree. The actual capacity of the original route P4-D is 700 * 0.64 = 448 vehicles / hour, and the transportation capacity is 448 * 50 = 22,400 m³ / hour. The actual capacity of the alternative route is 1000 * 0.48 = 480 vehicles / hour, and the transportation capacity is 480 * 50 = 24,000 m³ / hour. Currently, there are 5 vehicles on P4, but the calculation is based on P4-D, requiring:

[0110] ;

[0111] Therefore, in practice, 5 vehicles are still needed, but theoretically, the alternative route P4-B can save vehicle resources.

[0112] After 15:00:

[0113] The road landslide was repaired at 14:00, the slag yard C was rectified at 15:00, and the rainstorm stopped at 15:00. At this time, it is necessary to reassess the overall status: P2 has caught up with the normal progress at 14:40 and can gradually release vehicle resources; P4 has caught up with the progress of 1100m³ at 15:00, with 900m³ remaining.

[0114] Slag yard C resumed operation, with the unloading rate restored to 250 m³ / h (the maximum design rate is 300 m³ / h). The main path of the landslide route P2-B was restored, and the traffic efficiency correction factor was restored to 0.6. After the rainstorm ended, the traffic efficiency correction factors of all roads were restored to the data in Table 2.

[0115] Step 7, Rolling Optimization and Resource Recovery: After the interruption event is resolved, each section returns to the initial path to transport waste, and steps 3 and 6 are executed to recover or redistribute vehicles for sections that have caught up with the schedule.

[0116] After the emergency is resolved, the corresponding transportation strategy is no longer suitable for the current situation. Therefore, scheduling optimization is implemented, and the strategy is dynamically updated based on the latest data. When the progress of a section recovers to a certain threshold above the planned value, the optimization target is switched. Through the reverse optimization mechanism, the resource occupation of the recovered sections is gradually reduced, and vehicles are redistributed to sections that still need to catch up. By improving their transportation capacity, the catching up progress is accelerated, and the overall project efficiency is improved, rather than simply reducing resources.

[0117] With all unforeseen events resolved, each section resumed transporting waste along its original main route. Due to adjustments in vehicle resources caused by the unforeseen events, the number of vehicles for P2, P3, and P4 were 8, 11, and 5 respectively. After resuming the original main route, only 6, 10, and 4 vehicles were needed for transport. Therefore, 2 and 1 vehicles were released from P2 and P3 respectively, for a total of 3 vehicles, to supplement P4 (which needs to catch up with the progress of 900m³). Thus, P4 had 8 vehicles and needed 2.25 hours. Therefore, P4 was able to catch up with the normal progress at 17:15. Afterwards, 4 vehicle resources were released to await a new round of scheduling.

[0118] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for scheduling engineering slag removal based on strategy shift, characterized in that, Includes the following steps: Step 1: Real-time data acquisition and dynamic monitoring; Step 2: Set up the initial scheduling plan: Based on the distance between the contract section and the slag yard, initially select the slag yard closest to the contract section, and initially allocate the number of dump trucks for each contract section; Step 3: Determine the construction progress of each section: Compared with the slag removal plan, identify the sections that are ahead of schedule and those that are behind schedule. No adjustments will be made to the sections that are ahead of schedule, and the scheduling plan will be adjusted for the sections that are behind schedule. Step 4: Interruption Response and End-to-End Bottleneck Identification: Real-time detection of interruption events. If no interruption event occurs, proceed directly to Step 6. If an interruption event occurs, detect the interruption link in the transportation link and adjust the transportation route according to the interruption situation. Then, full-link bottleneck identification is performed, and the loading weight, transportation weight, and unloading weight of the adjusted transportation route are allocated based on the full-link bottleneck identification results. Step 5: Establish a path matching degree model, select the adjusted path based on the path matching degree, and select the path with the high path matching degree as the adjusted path; The path matching degree model expression is: （3）； ； in, This represents the path matching degree corresponding to the route from section i to slag yard k; j is the road number, and k is the slag yard or material yard. The road congestion coefficient represents the ratio of passing vehicles to the maximum road capacity; α is the loading weight, β is the transportation weight, and γ is the unloading weight. Let i be the loading rate of section i; This represents the maximum theoretical loading rate for section i. Let k be the unloading rate of the slag yard. Let k be the maximum theoretical unloading rate of the slag yard. Step Six: Flexible Vehicle Scheduling and Dynamic Adjustment: Scheduling vehicles for each route, prioritizing the filling of slag removal gaps in lagging sections; Step 7, Rolling Optimization and Resource Recovery: After the interruption event is resolved, each section returns to the initial path to transport waste, and steps 3 and 6 are executed to recover or redistribute vehicles for sections that have caught up with the schedule.

2. The engineering slag discharge scheduling method based on strategy shift according to claim 1, characterized in that, Step one includes real-time collection of actual and planned slag discharge volumes for each section, data on the status of slag trucks, and data on road traffic capacity.

3. The engineering slag discharge scheduling method for strategy shift according to claim 1, characterized in that, In step three, if the actual slag discharge intensity of a certain section is greater than the planned slag discharge intensity, then the section is considered an advanced section; if the actual slag discharge intensity of a certain section is less than the planned slag discharge intensity, then the section is considered a lagging section.

4. The engineering slag discharge scheduling method for strategy shift according to claim 3, characterized in that, In step three, the segment lag rate is used to determine the segment type. A segment lag rate greater than 0 indicates that the segment is an advanced segment, and a segment lag rate less than 0 indicates that the segment is a lagging segment. The formula for calculating the section lag rate is: （1）； in, To plan the amount of slag removed, The actual slag output is represented by 'i', where 'i' represents the standard section.

5. The engineering slag discharge scheduling method for strategy shift according to claim 1, characterized in that, In step four, the interruption events include sudden events that cause the transportation link to fail completely or partially, including road collapses, vehicle breakdowns, natural disasters, and temporary control measures. If the target slag yard cannot be reached, a slag yard or temporary storage area of ​​the same type will be selected according to priority, and the vehicles that have not yet departed on the interrupted route will be reassigned to other routes or sections.

6. The engineering slag discharge scheduling method for strategy shift according to claim 1, characterized in that, In step four, the full bottleneck identification coefficient is calculated as follows: （2）； Where B represents the bottleneck identification coefficient; j is the road number; and k is the slag yard or material yard. The road congestion coefficient represents the ratio of the number of vehicles passing through to the maximum capacity of the road. Let i be the loading rate of the section. This represents the maximum theoretical loading rate for section i. Let k be the unloading rate of the slag yard. Let k be the maximum theoretical unloading rate of the slag yard.

7. The engineering slag discharge scheduling method for strategy shift according to claim 6, characterized in that, In the formula for calculating the total bottleneck identification coefficient, , , Of the three values, if Minimum indicates that the bottleneck of the entire supply chain is the loading efficiency. Minimum indicates that the bottleneck of the entire link is transportation efficiency. The minimum value indicates that the bottleneck in the entire chain is unloading efficiency, and the weight of the bottleneck link needs to be set higher than the weights of the other two links.

8. The engineering slag discharge scheduling method for strategy shift according to claim 1, characterized in that, In step six, if additional vehicles are needed for lagging sections, and there are no sections with changed routes, the formula for calculating the additional vehicles needed for the transportation route is as follows: （4）； When the calculated number of additional vehicles is not an integer, it is rounded up.

9. The engineering slag discharge scheduling method for strategy shift according to claim 1, characterized in that, In step six, if the route has been changed due to an interruption event, the formula for calculating the additional vehicles to be dispatched on the changed transportation route is as follows: （5）； or, (6); When the calculated number of additional vehicles is not an integer, it is rounded up. The efficiency improvement is calculated as the ratio of the transportation efficiency of the changed route to the transportation efficiency of the original route, minus 1. The reduction in efficiency is calculated as: 1 minus the ratio of the transportation efficiency of the changed route to the transportation efficiency of the original route.

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