Beam manufacturing plan automatic scheduling method and system based on dynamic collision detection and storage rack matching

Abstract

The invention relates to the technical field of bridge construction and management, and discloses a beam manufacturing plan automatic scheduling method and system based on dynamic collision detection and storage rack matching, and the method comprises the steps: utilizing a multi-target balance optimization algorithm to enumerate a plurality of feasible beam erecting speeds, calculating scores corresponding to the plurality of feasible beam erecting speeds based on a multi-target weight, and calculating the scores corresponding to the plurality of feasible beam erecting speeds; arranging an optimal speed sequence according to the scores, and generating a daily girder erection arrangement table; according to the method, the progress collision problem is detected and early warned in real time by dynamically responding to the change of the project progress, and meanwhile, the optimal beam manufacturing plan is generated by optimizing the scheduling strategy and comprehensively considering a plurality of target factors; the automatic scheduling system can effectively improve the accuracy and the flexibility of a beam manufacturing plan, optimize resource configuration and reduce the risk of progress conflict, so that the construction efficiency and the project quality are improved, and the automatic scheduling system has relatively high adaptability and efficient scheduling capability.

Description

Technical Field

[0001] This invention relates to the field of bridge construction and management technology, and more specifically, to an automatic scheduling method and system for beam fabrication planning based on dynamic collision detection and matching of the fabrication frame. Background Technology

[0002] A bridge beam fabrication plan is a detailed work plan developed during bridge construction to ensure the timely and high-quality completion of beam fabrication and installation. This plan typically includes the beam fabrication process, production schedule, required equipment, personnel arrangements, and material preparation. The core objective of the beam fabrication plan is to rationally allocate production resources, optimize the construction process, ensure the efficient implementation of beam fabrication work, and consider various risks and contingency measures that may arise during construction. Through the beam fabrication plan, the construction team can clearly understand the specific requirements of each task, avoid resource waste during construction, and ensure the smooth progress of the project.

[0003] However, existing technologies generally employ scheduling methods dominated by human experience, which have significant limitations in terms of adaptability, systematicity, and scientific decision-making. On the one hand, it is difficult to dynamically adjust the established plan in real time according to the actual construction progress of the offline structure, resulting in frequent pre-work delays or excessive pressure on beam storage in the beam yard. On the other hand, beam fabrication, storage, and erection are often planned independently, lacking cross-process system verification and linkage mechanisms, which can easily lead to resource matching conflicts between the abutment and the box girder, restricting the overall continuity of the construction chain. In addition, when facing complex conditions such as schedule delays, resource bottlenecks, or process adjustments, existing methods lack a decision support system based on multi-objective optimization, making it difficult to quantitatively evaluate and optimize strategies such as waiting, speed adjustment, site transfer, or capacity reorganization, thus affecting the level of intelligent and refined management of engineering projects. Some existing management systems only have data recording functions and lack a mechanism to perform real-time dynamic collision detection of offline project progress and trigger multi-level early warnings, while also lacking closed-loop verification and linkage scheduling for beam fabrication, storage, and erection. Summary of the Invention

[0004] To overcome the above-mentioned deficiencies of the prior art, embodiments of the present invention provide an automatic scheduling method and system for beam fabrication planning based on dynamic collision detection and matching of the fabrication rack.

[0005] To achieve the above objectives, the present invention provides the following technical solution: Firstly, an automatic scheduling method for beam fabrication planning based on dynamic collision detection and rack matching is provided, the method comprising: Acquire basic data from the beam yard, initialize the basic data to obtain production data, obtain the status and output of box girders from the production data, and calculate the theoretical maximum daily production capacity of the beam yard. The production data includes: resource information, obstruction node data and equipment parameters. Obtain the planned completion date and remaining number of holes from the obstacle node data, calculate the expected arrival date based on the current date, determine the waiting days, make multi-level early warning decisions based on the waiting days, and trigger the rearrangement mechanism; Multiple feasible girder erection speeds are enumerated using a multi-objective equilibrium optimization algorithm. Based on the multi-objective weights, the scores corresponding to the multiple feasible girder erection speeds are calculated. The optimal speed sequence is arranged according to the scores, and a daily girder erection schedule is generated. Based on the daily beam erection schedule, the entire beam yard operation process is simulated day by day to verify daily capacity and inventory, determine the feasibility of the optimal scheduling plan, and output a complete final scheduling plan.

[0006] Furthermore, the calculation of the theoretical maximum daily production capacity of the beam yard includes: The resource allocation of each type of box girder is obtained from the resource information, and the daily production capacity of each type of box girder in the two key stages of steel reinforcement binding and concrete pouring is calculated respectively. The smaller value is taken as the bottleneck capacity of this model, and the bottleneck capacity of each model is summed up according to the demand ratio to obtain the overall theoretical maximum daily capacity of the beam yard.

[0007] Further, the calculation of the expected arrival date based on the current date includes: The estimated arrival date = current date + number of remaining holes / maximum speed; The maximum speed is adjusted based on a discount function, the expression of which is: ; In the formula: To determine the risk factor for schedule delays, Weather influencing factors This is a historical efficiency adjustment factor.

[0008] Furthermore, the multi-level early warning decision based on the number of waiting days includes: Set the safety threshold as n, the maximum allowable threshold as m, and 0 < n < m; If n ≤ n, it is considered a normal state and no warning is triggered; If n < number of waiting days < m, it is determined to be a yellow alert; If m < number of waiting days, it is considered a red alert, and the rearrangement mechanism is triggered directly.

[0009] Furthermore, the calculation of scores corresponding to multiple feasible beam erection speeds based on multi-objective weights includes: The multi-objectives include waiting time, beam storage utilization rate, and rhythm stability. Values ​​are assigned to these three types of objectives as follows: , , , ; The scores of multiple candidate scheduling schemes are calculated based on the three types of objectives. The specific steps are as follows: A1: Waiting Time Score: In the formula: For the number of days to wait; A2: Beam Filling Rate Score: =Actual beam storage quantity / Maximum beam storage capacity; A3: Rhythm consistency score: In the formula: This represents the standard deviation of the number of beams erected daily. The score is: .

[0010] Furthermore, the generation of the daily beam erection schedule includes: Based on the optimal speed sequence, the number of basic girder erection is calculated and a daily girder erection sequence is generated using uniform interpolation. Based on the daily beam erection quantity sequence, the daily beam erection quantity is converted into a specific sequence of span positions and box girder models to obtain the daily beam erection schedule.

[0011] Furthermore, the verification of daily production capacity and inventory includes: The capacity verification includes three types of constraints: whether the qualified product inventory is ≥0; whether the total inventory is ≤ the maximum total number of beams stored; and whether the maximum daily capacity of the beam yard is ≥ the planned average daily demand. The system is considered to have passed the constraint test if all three types of constraints are met simultaneously. If the test fails, an early warning is issued, the simulation process is terminated, and the daily beam erection schedule is regenerated.

[0012] Secondly, an automatic beam fabrication scheduling system based on dynamic collision detection and rack matching is provided. This system is implemented based on the aforementioned automatic beam fabrication scheduling method based on dynamic collision detection and rack matching. The system includes: The data acquisition module acquires basic data from the beam yard, initializes the basic data to obtain production data, obtains the status and output of box girders from the production data, and calculates the theoretical maximum daily production capacity of the beam yard. The production data includes: resource information, obstacle node data, and equipment parameters. The multi-level early warning module receives production data from the data acquisition module, obtains the planned completion date and the number of remaining holes from the obstacle node data, calculates the expected arrival date based on the current date, obtains the waiting days, and makes multi-level early warning decisions based on the waiting days; The production scheduling module uses a multi-objective equilibrium optimization algorithm to enumerate multiple feasible beam erection speeds, calculates the scores corresponding to multiple feasible beam erection speeds based on multi-objective weights, arranges the optimal speed sequence according to the scores, generates a daily beam erection schedule, and uploads the daily beam erection schedule. The simulation feedback module receives the daily beam erection schedule uploaded from the production scheduling module, simulates the entire beam yard operation process day by day based on the daily beam erection schedule, verifies daily production capacity and inventory, determines the feasibility of the optimal scheduling plan, outputs a complete final scheduling plan, and feeds it back to the production scheduling module in real time.

[0013] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the above-mentioned automatic scheduling method for beam fabrication planning based on dynamic collision detection and matching of the fabrication rack.

[0014] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed, implements the above-mentioned automatic scheduling method for beam fabrication planning based on dynamic collision detection and matching of the fabrication rack.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This application discloses an automatic beam fabrication scheduling method and system based on dynamic collision detection and rack matching. The method includes: obtaining the planned completion date and remaining span count from obstacle node data; calculating the expected arrival date based on the current date; determining the waiting days; and making multi-level early warning decisions based on the waiting days. It also involves enumerating multiple feasible beam erection speeds using a multi-objective equilibrium optimization algorithm, calculating scores corresponding to these speeds based on multi-objective weights, arranging the optimal speed sequence according to the scores, and generating a daily beam erection schedule. This invention dynamically responds to changes in project progress, detects and warns of progress collisions in real time, and generates an optimal beam fabrication plan by optimizing scheduling strategies and comprehensively considering multiple objective factors. This automatic scheduling system effectively improves the accuracy and flexibility of beam fabrication planning, optimizes resource allocation, reduces the risk of schedule conflicts, thereby improving construction efficiency and project quality, and has strong adaptability and efficient scheduling capabilities. Attached Figure Description

[0016] Figure 1 A flowchart of the automatic scheduling method for beam fabrication planning based on dynamic collision detection and storage rack matching provided by the present invention; Figure 2 A schematic diagram of the module structure of the automatic scheduling system for beam fabrication planning based on dynamic collision detection and storage rack matching provided by the present invention; Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention; Figure 4 The multi-level early warning decision-making flowchart provided by this invention; Figure 5 The flowchart for the automatic scheduling of bridge erection provided by this invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1 Please see Figure 1 and Figures 4-5 As shown, this embodiment discloses an automatic scheduling method for beam fabrication planning based on dynamic collision detection and rack matching. The method includes: S101: Obtain basic data from the beam yard, initialize the basic data to obtain production data, obtain the status and output of box girders from the production data, and calculate the theoretical maximum daily production capacity of the beam yard. The production data includes: resource information, obstacle node data and equipment parameters. It should be understood that resource information includes: Information on beam fabrication platform and rebar jig: ID, model, daily production capacity, type, available quantity; Information on the girder storage area: the maximum storage capacity of each type of box girder, and the current inventory quantity for each status (awaiting maintenance, under maintenance, qualified).

[0019] Production process parameters: standard beam fabrication time and curing time (including final tensioning) for each type of box girder.

[0020] The obstacle node data includes: the planned completion date, the latest predicted completion date, and the starting borehole number for all obstacle nodes (such as bridge piers and roadbed sections).

[0021] Equipment parameters include: safety threshold, maximum waiting days, girder erection speed range, planned completion date, and safety redundancy dates.

[0022] At the same time, the basic data is initialized, that is, the current date is set as the project start date. The real-time status and cumulative output of the box girder are initialized as detailed in Table 1: Table 1: Real-time Production Status of Box Girder

[0023] As a specific implementation method, the theoretical maximum daily production capacity of the beam yard needs to be based on the resource allocation of various types of box girders. The calculation of the theoretical maximum daily production capacity of the beam yard includes: Resource allocation information for each type of box girder was obtained from resource information, and the daily production capacity of each type of box girder in the two key stages of rebar tying and concrete pouring was calculated, namely: ; The smaller value is taken as the bottleneck capacity of this model, and the bottleneck capacity of each model is summed up according to the demand ratio to obtain the overall theoretical maximum daily capacity of the beam yard.

[0024] S102: Obtain the planned completion date and remaining number of holes from the obstacle node data, calculate the expected arrival date based on the current date, obtain the waiting days, and make multi-level early warning decisions based on the waiting days; It should be understood that: the calculation of the estimated arrival date based on the current date includes: The estimated arrival date = current date + number of remaining holes / maximum speed; The maximum speed is adjusted based on a discount function, which is a speed correction function dynamically adjusted based on multiple factors. This function reduces the maximum beam erection speed according to the actual progress of the offline project and external conditions, and its output is the adjusted speed value. Its function expression is: ; In the formula: To determine the risk factor for schedule delays, Weather influencing factors Historical efficiency adjustment factor; It should be added that α is the schedule delay risk coefficient, with a value range of [0,1], which is dynamically calculated based on the deviation between the current progress of the offline project and the plan. α = max(0, 1 - current delay days / remaining time); Where, current delay days = latest predicted completion date - planned completion date (0 if negative), and remaining time is the total number of days from the current date to the planned completion date; β is a weather influence factor, with a value range of [0,1], which is dynamically adjusted based on historical weather data and forecasts. β = 1 - (estimated number of days of severe weather / remaining available construction period); Severe weather includes, but is not limited to, weather conditions that affect bridge erection operations, such as heavy rain, strong winds, and low temperatures. The criteria for judging such weather conditions can be based on the "Technical Specifications for Highway Bridge Construction" or the specific climate thresholds for the project. γ is a historical efficiency adjustment factor, with a value range of [0,1], based on recent bridge erection efficiency statistics: γ = Recent average actual beam erection rate / Maximum beam erection speed; For example, the average actual beam erection rate over the past 7 days. If there is no recent actual data, then γ=1.0.

[0025] Furthermore, the schedule delay risk coefficient α can be calculated by comparing the difference between the current actual progress of the project and the original planned completion date. The greater the schedule delay, the lower the α value will be, reflecting a higher risk.

[0026] Secondly, the number of severe weather days can usually be obtained by weather impact factor β through three methods: First, by using meteorological forecasts or APIs to obtain real-time weather information and marking weather that affects construction, such as rainstorms, typhoons, and strong winds; second, by referring to historical meteorological data and making predictions based on severe weather records of the same season in the past; and third, by paying attention to meteorological disaster warnings or using on-site meteorological monitoring equipment to record the number of weather days that meet the warning standards in real time, thereby providing a basis for adjusting construction plans and schedules.

[0027] The historical efficiency adjustment factor γ is automatically calculated based on the bridge erection data of the past 7 days and updated every day at midnight. It comprehensively considers the operation parameters and influencing factors, assesses the current construction efficiency, and provides a predictive reference for future operations. Through dynamic adjustment, it ensures the accuracy of construction plans and resource allocation.

[0028] For example, waiting days = planned completion time of all obstacle units - estimated arrival time; Among them, such as Figure 4 As shown, the multi-level early warning decision based on the number of waiting days includes: Set the safety threshold as n, the maximum allowable threshold as m, and 0 < n < m; If n ≤ n, it is considered a normal state and no warning is triggered; If n < waiting days < m, it is judged as a yellow warning, prompting the relevant management unit to pay close attention to the progress risk of this key bottleneck, and suggesting that tracking or fine-tuning measures be taken; If m < number of waiting days, it is considered a red alert and the rescheduling mechanism is triggered directly to ensure the sustainability of the overall construction pace and production capacity balance; where the values ​​of m and n depend on different operational situations.

[0029] S103: Use a multi-objective equilibrium optimization algorithm to enumerate multiple feasible bridge erection speeds, calculate the scores corresponding to multiple feasible bridge erection speeds based on multi-objective weights, arrange the optimal speed sequence according to the scores, and generate a daily bridge erection schedule. As a specific implementation method, candidate erection speeds can be enumerated in steps between the minimum and maximum erection speeds (spans / day). : ; Among them, step size The setting principles are as follows: If the remaining construction period is long, a fixed step size should be used first (the threshold is specified in the "Railway Bridge Erection Machine Beam Erection Specification" (GB / T10213)): Speed ​​difference = maximum beam erection speed - minimum beam erection speed.

[0030] If the speed difference is ≤ 2 holes / day, then Δv = 0.5 holes / day; If 2 < speed difference ≤ 5 holes / day, then Δv = 1 hole / day; If the speed difference is greater than 5 holes / day, then Δv = 2 holes / day.

[0031] If the remaining construction period is tight, a dynamic step size is adopted: (maximum speed - minimum speed) / 10 (enumerate 10 candidate values).

[0032] Calculate the total time required for girder erection: For each candidate velocity vi, calculate the beam erection time Ti required to complete the remaining number of holes: Number of remaining holes / ; The waiting time was calculated based on the total time required for girder erection. : Remaining available construction period ; like <0: This indicates that the project is not yet ready after the beam erection is completed.

[0033] If 0 < ≤Maximum allowable waiting time: This means that the beam erection will be completed first, but the project will need to wait, and the waiting time is within the allowable range.

[0034] like If the maximum allowed waiting time is exceeded, it is considered an infeasible waiting time. Therefore, only those conditions that are met are selected. The set of feasible speeds with a maximum allowable waiting time.

[0035] In implementation, the calculation of scores corresponding to multiple feasible beam erection speeds based on multi-objective weights includes: The multi-objectives include waiting time, beam storage utilization rate, and rhythm stability. Values ​​are assigned to these three types of objectives as follows: , , , It should be noted that the weights of the three types of objectives can be changed according to different operational situations, i.e., adjusted according to project priority: priority of construction period, priority of beam storage, and priority of construction stability. This application does not restrict this. The scores of multiple candidate scheduling schemes are calculated based on the three types of objectives. The specific steps are as follows: A1: Waiting Time Score: In the formula: The number of waiting days is used to calculate the score; the longer the waiting time, the lower the score, which directly reflects the risk of delays in the project. A2: Beam Filling Rate Score: =Actual beam storage quantity / Maximum beam storage capacity; For example, if the maximum beam storage capacity is 100 beams and the current qualified beam inventory is 75 beams, then Sstorage = 0.75; if the inventory is 110 beams (exceeding the limit), this speed is directly determined to be infeasible. "Actual beam storage quantity" is the current (or the corresponding date of the planned projection) qualified beam inventory quantity.

[0036] A3: Rhythm consistency score: In the formula: The standard deviation of the daily number of bridge beams erected is represented by the number of beams erected each day. The more stable the number of beams erected each day, the higher the score; the greater the fluctuation in the number, the lower the score. The score is: ; It should be noted that the generation of the daily beam erection schedule includes: Based on the optimal speed sequence, the number of foundation beams to be erected is calculated, and a daily beam erection sequence is generated using uniform interpolation. For each optimal speed, the generated daily beam erection sequence satisfies the following:

[0037] As a specific example, the integerized beam erection sequence construction method includes: Set base values:

[0038] Calculate the number of holes r to be filled: ; Finally, uniform interpolation is used to... indivual The sequences are inserted uniformly with spacing of:

[0039] The specific implementation steps of the uniform interpolation method are as follows: a1: Initialize sequence: Create a sequence with a length equal to the total duration. The list is used, and each initial value in the list is set as the baseline number of beams. .

[0040] a2: Calculate the insertion step size: Calculate the step size That is, approximately how many positions require the insertion of an additional beam-supporting hole.

[0041] a3: Determine the starting insertion point: To ensure a more even distribution of the increment over time, insertion is typically started in the first half of the sequence. The starting position is set to half the step size.

[0042] a4: Cyclic insertion operation: Starting from the initial insertion point, every […]. For each position, the number of daily beams corresponding to that position is increased by 1, completing one insertion. Repeat this process until... All the "filling holes" have been inserted.

[0043] a5: Loop processing: If there are still uninserted holes after traversing from the starting point to the end of the sequence, then continue the insertion operation from the beginning of the sequence (index 0) to ensure... The increments are evenly distributed throughout the entire project period. in the sequence.

[0044] The daily scheduling rules for beam erection positions and models are as follows: The remaining span sequence U of the pier numbers to be erected is obtained from the production data, sorted in ascending order by pier number, and the box girder model corresponding to each span is obtained. Mark special structural holes (such as the starting point of a continuous beam, abutment, road and river crossings, etc.). For example, the scheduling priority rules are as follows: Special structures take priority: If there are remaining beams planned for erection on a certain day, and there are special structure holes that have not yet been erected, then the special structure holes will be given priority. Pier sequence principle: For non-special structure spans, piers should be erected in the order of their numbers. Model matching principle: The model of the box girder erected each day must match the model of the existing girder on site, and the existing girder model should be used first. It should be added that the principle for generating daily beam erection positions is as follows: For the Heaven, allocation One hole position:

[0045] Among them, the function The logic is as follows: If the remaining special structure holes are not empty, the first special hole will be selected first. Otherwise, select the first one according to the bridge pier number sequence. One hole position; Check if the box girder model of the selected hole position matches the stored beam. If they do not match, proceed to the next available hole position.

[0046] Based on the daily beam erection quantity sequence, the daily beam erection quantity is converted into a specific sequence of span positions and box girder models to obtain the daily beam erection schedule; For a better understanding of the daily beam erection schedule, please refer to Table 2: Table 2: Explanation of the Bridge Erection Plan Data Structure

[0047] S104: Simulate the entire beam yard operation process day by day based on the daily beam erection schedule, verify daily capacity and inventory, determine the feasibility of the optimal scheduling plan, and output the complete final scheduling plan; It should be noted that the box girder state transition is automatically driven by the system, using a time-based automatic triggering mechanism. The system updates the elapsed time of each box girder daily in the simulation and compares it with the standard process time corresponding to each state. When a box girder's dwell time in a certain state reaches its preset standard time, the system automatically updates its state to the next stage without manual intervention. The transition from "curing completed" to "qualified" is typically associated with a virtual, extremely short quality inspection process. The system defaults to completing the inspection and marking it as qualified immediately after curing. If strict manual confirmation is required in actual management, the system supports suspending the process at this node, waiting for external confirmation signals for manual review before updating the state, thus achieving dynamic simulation. This includes: Erection consumption: Subtract the planned erection quantity for the day from the qualified product inventory; Maintenance status update: Decrease the remaining maintenance time of each box girder in the maintenance inventory by 1, and check and process the box girders that have completed maintenance; Production replenishment: Based on the actual daily production capacity of the beam yard, new box girders are generated and added to the inventory awaiting maintenance, and then moved into the maintenance area according to the rules; Inventory status update: Calculate the updated inventory quantities for each type of inventory.

[0048] In implementation, the verification of daily production capacity and inventory includes: The capacity verification includes three types of constraints: whether the qualified product inventory is ≥0; whether the total inventory is ≤ the maximum total number of beams stored; and whether the maximum daily capacity of the beam yard is ≥ the planned average daily demand. Among them, the constraint is considered to pass if all three types of constraint conditions are met at the same time. That is, if no three types of constraint warnings are triggered during the simulation up to the planned completion date, the plan is verified and continues to the next day's cycle.

[0049] If the test fails, an early warning will be issued, the simulation process will be terminated, and the daily beam erection schedule will be regenerated. Its verification feedback and loop mechanism is as follows: Verification Failure: If an alarm is triggered on any day during the simulation, the simulation will be immediately stopped, and a verification feedback report will be generated. This report mainly includes the following information: Alarm Date: The specific date on which the constraint alarm was first triggered.

[0050] Alarm type: Clearly indicate the type of conflict, such as "insufficient inventory of qualified products", "excessive capacity of beam storage area" or "beam yard capacity is less than the average daily demand".

[0051] Based on the type of alarm, optimization suggestions are generated, that is, specific adjustment directions are proposed, such as "suggest reducing the bridge erection speed" or "suggest adjusting the bridge erection sequence to prioritize the consumption of high-inventory models".

[0052] Secondly, based on the "alarm type" and "optimization suggestions," corresponding adjustment strategies are implemented to regenerate new candidate bridge erection plans. The main adjustment strategies are as follows: If the alarm type is "Insufficient stock of qualified products": If the suggestion is to "reduce the girder erection speed", then the candidate girder erection speed will be reduced in subsequent optimizations to decrease daily consumption. (Adjustment logic: Since the inventory consumption rate is greater than the replenishment rate, the girder erection speed needs to be reduced to decrease the average daily consumption and match inventory replenishment with consumption. At the same time, the user preference weight can be kept unchanged (or the girder utilization rate weight w2 can be increased). When re-enumerating the speed, the original minimum girder erection speed will remain unchanged, and the original maximum girder erection speed will be reduced by 10%-15% to form a new speed range adjustment range. Then, new candidate speeds will be enumerated according to the original step size rule.) The suggestion is to "adjust the girder erection sequence." Therefore, when generating the daily girder position list, the sorting rules should be modified to prioritize girder positions corresponding to box girder models with sufficient current inventory. (Adjustment logic: Regenerate the daily girder erection schedule in step 3.6, and modify the priority of the "model matching principle": move "prioritize using girder positions corresponding to models with high current inventory" after "special structure priority" and before "pier sequence principle"; simultaneously maintain the candidate speed enumeration and scoring process after speed adjustment, ensuring that the girder erection sequence adjustment and speed adjustment work synergistically to improve inventory matching efficiency.) If the alarm type is "Beam storage area capacity exceeded": The usual recommendation is to "increase the girder erection speed," which means increasing the candidate girder erection speed in subsequent optimizations to accelerate inventory depletion. (Adjustment logic: When re-enumerating the speed, the original maximum girder erection speed remains unchanged, while the original minimum girder erection speed is increased by 10%-15% to form a new speed range adjustment range. New candidate speeds are enumerated according to the original step size rule. At the same time, the weight w2 of the girder utilization rate can be increased to ensure that the new speed can prioritize reducing the inventory level.) If the alarm type is "Beam yard capacity is less than average daily demand": It is generally recommended to "reduce the beam erection speed" to match the erection demand with the actual capacity of the beam yard, or to trigger an external warning. (Adjustment logic: When re-enumerating the speed, both the upper and lower limits of the original speed range are reduced by 10%-20% to form a new speed range adjustment range, and new candidate speeds are enumerated according to the original step size rule; at the same time, the waiting time weight w1 can be increased to avoid exceeding the waiting time limit due to speed reduction).

[0053] Ultimately, by iteratively generating daily beam erection schedules and simulating the entire beam yard operation process day by day, a candidate plan that can be verified is generated, or all candidate plans fail verification and require manual intervention.

[0054] Example 2 Please see Figure 2 As shown, based on the same inventive concept, this embodiment discloses an automatic scheduling system for beam fabrication planning based on dynamic collision detection and rack matching. For details not covered in this embodiment, please refer to the relevant sections of Embodiment 1. The system includes: The data acquisition module acquires basic data from the beam yard, initializes the basic data to obtain production data, obtains the status and output of box girders from the production data, and calculates the theoretical maximum daily production capacity of the beam yard. The production data includes: resource information, obstacle node data, and equipment parameters. The multi-level early warning module receives production data from the data acquisition module, obtains the planned completion date and the number of remaining holes from the obstacle node data, calculates the expected arrival date based on the current date, obtains the waiting days, and makes multi-level early warning decisions based on the waiting days; The production scheduling module uses a multi-objective equilibrium optimization algorithm to enumerate multiple feasible beam erection speeds, calculates the scores corresponding to multiple feasible beam erection speeds based on multi-objective weights, arranges the optimal speed sequence according to the scores, generates a daily beam erection schedule, and uploads the daily beam erection schedule. The simulation feedback module receives the daily beam erection schedule uploaded from the production scheduling module, simulates the entire beam yard operation process day by day based on the daily beam erection schedule, verifies daily production capacity and inventory, determines the feasibility of the optimal scheduling plan, outputs a complete final scheduling plan, and feeds it back to the production scheduling module in real time.

[0055] Example 3 Please see Figure 3 As shown, this embodiment discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the automatic scheduling method for beam fabrication planning based on dynamic collision detection and rack matching provided by the above methods.

[0056] Since the electronic device described in this embodiment is the electronic device used to implement the automatic beam fabrication planning method based on dynamic collision detection and rack matching in the embodiments of this application, those skilled in the art can understand the specific implementation and various variations of the electronic device in this embodiment based on the automatic beam fabrication planning method based on dynamic collision detection and rack matching described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. Any electronic device used by those skilled in the art to implement the automatic beam fabrication planning method based on dynamic collision detection and rack matching in the embodiments of this application falls within the scope of protection of this application.

[0057] Example 4 This embodiment discloses a computer-readable storage medium, including a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, it implements the above-described automatic scheduling method for beam fabrication planning based on dynamic collision detection and rack matching.

[0058] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters, weights, and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0059] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired or wireless network. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0060] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0061] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0062] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only one method, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0063] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0064] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0065] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0066] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for automatic scheduling of a beam manufacturing plan based on dynamic collision detection and storage rack matching, characterized in that, The method comprises: Obtaining basic data from the beam field, initializing the basic data, obtaining production data, obtaining the state and yield of the box girder from the production data, and calculating the theoretical maximum daily production capacity of the beam field, wherein the production data comprises: resource information, obstacle node data and equipment parameters; Obtaining the planned completion date and the remaining hole number from the obstacle node data, calculating the expected arrival date based on the current date, obtaining the waiting days, and making multi-level early warning decisions according to the waiting days; Using a multi-objective balanced optimization algorithm to enumerate a plurality of feasible girder erection speeds, calculating the scores corresponding to the plurality of feasible girder erection speeds based on multi-objective weights, arranging the optimal speed sequence according to the scores, and generating a daily girder erection arrangement table; Simulating the whole process of beam field operation day by day according to the daily girder erection arrangement table, checking the daily production capacity and inventory, determining the feasibility of the optimal scheduling scheme, and outputting a complete final scheduling scheme.

2. The method of claim 1, wherein the method further comprises: The calculation of the theoretical maximum daily production capacity of the beam field comprises: Obtaining the resource allocation of each type of box girder from the resource information, and calculating the daily production capacity of each type of box girder in the two key links of steel bar binding and concrete pouring respectively; Taking the smaller value as the bottleneck capacity of the type, and then collecting the bottleneck capacities of each type according to the demand proportion to obtain the overall theoretical maximum daily production capacity of the beam field.

3. The method of claim 1, wherein the method further comprises: The calculation of the expected arrival date based on the current date comprises: The expected arrival date = current date + remaining hole number / maximum speed; Wherein, the maximum speed is adjusted based on a discount function, and the function expression is: ； In the formula: is a progress delay risk coefficient, is a weather impact factor, is a historical efficiency adjustment factor.

4. The method of claim 1, wherein the method further comprises: The multi-level early warning decision based on the waiting days comprises: Setting the safety threshold as n and the maximum allowed threshold as m, 0 < n < m; If ≤ n, it is considered as a normal state, and no early warning is triggered; If n < waiting days < m, it is determined as a yellow early warning; If m < waiting days, it is considered as a red early warning, and the rearrangement mechanism is directly triggered.

5. The method of claim 4, wherein the method further comprises: The calculation of the scores corresponding to the plurality of feasible girder erection speeds based on multi-objective weights comprises: The multiple targets include waiting time, beam utilization and rhythm stability, and the three types of targets are valued as , , , ; Wherein, the scores of a plurality of candidate scheduling schemes are calculated according to three types of targets, and the specific steps are as follows: A1: Wait time score: where: is the number of days of waiting; A2: Beam inventory fill rate score: = Actual beam inventory / Maximum beam capacity; A3: Pace smoothness score: where: is the standard deviation of the number of girders erected per day; Score is: .

6. The method of claim 1, wherein the method further comprises: The generation of the daily girder erection arrangement table comprises: Based on the optimal speed sequence, the basic girder erection quantity is calculated and the uniform interpolation method is used to generate a daily girder erection quantity sequence; Based on the daily girder erection quantity sequence, the daily girder erection quantity is converted into a specific hole position and box girder type sequence to obtain the daily girder erection arrangement table.

7. The method of automatically scheduling a plan for fabricating beams based on matching the plan to a fabricator using dynamic collision detection of claim 6, wherein, The checking of the daily production capacity and inventory comprises: The capacity checking includes three types of constraint conditions: whether the qualified product inventory is ≥ 0; whether the total inventory is ≤ the maximum storage beam total amount; whether the maximum daily production capacity of the beam field is ≥ the planned daily demand; Wherein, the three types of constraint conditions are satisfied simultaneously, which is considered as a constraint passing, if the checking is not passed, an early warning is issued, the simulation process is terminated, and a daily girder erection arrangement table is regenerated.

8. An automated scheduling system for beam planning based on dynamic collision detection and storage rack matching, characterized in that, The system comprises: The data acquisition module acquires basic data from the beam field, initializes the basic data, obtains production data, acquires the state and yield of the box girder from the production data, and calculates the theoretical maximum daily production capacity of the beam field. The multi-level early warning module receives the production data from the data acquisition module, acquires the planned completion date and the remaining hole number from the blocking node data, calculates the expected arrival date based on the current date, obtains the waiting days, makes a multi-level early warning decision according to the waiting days, and triggers the rearrangement mechanism. The production arrangement module enumerates a plurality of feasible girder erection speeds by using a multi-objective balanced optimization algorithm, calculates the scores corresponding to the plurality of feasible girder erection speeds based on multi-objective weight, arranges the optimal speed sequence according to the scores, and generates a daily girder erection arrangement table. The simulation feedback module receives the daily girder erection arrangement table uploaded from the production arrangement module, simulates the whole process of the beam field operation day by day according to the daily girder erection arrangement table, verifies the daily production capacity and the inventory, determines the feasibility of the optimal scheduling scheme, outputs a complete final scheduling scheme, and feeds back to the production arrangement module in real time.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor executes the computer program to realize the automatic scheduling method of the beam manufacturing plan based on dynamic collision detection and storage rack matching as claimed in claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed to realize the automatic scheduling method of the beam manufacturing plan based on dynamic collision detection and storage rack matching as claimed in claims 1-7.

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