Flexible comprehensive scheduling method considering process conflicts under equipment collaborative allocation
By establishing a dynamic efficiency matrix and using the Hungarian method to optimize the allocation of processes and equipment, the problems of equipment collaborative allocation and process conflicts in flexible integrated scheduling were solved, realizing the rational utilization of equipment resources and improving production efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- JILIN NORMAL UNIV
- Filing Date
- 2025-11-27
- Publication Date
- 2026-04-17
AI Technical Summary
Existing flexible integrated scheduling methods neglect the issues of equipment collaborative allocation and conflicts between processes within the same level, resulting in low production efficiency.
A flexible integrated scheduling method that considers equipment collaborative allocation is adopted. By establishing a dynamic efficiency matrix and the Hungarian method, the allocation of processes and equipment is optimized. Combined with a mixed integer programming model, process conflicts are resolved, and the rational utilization of equipment resources is achieved.
This approach fully utilizes equipment resources, reduces total processing time, improves production efficiency and equipment utilization, and optimizes the scheduling process.
Smart Images
Figure CN121882504A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of computer integrated manufacturing technology, and in particular relates to a flexible integrated scheduling method that considers process conflicts under equipment collaborative allocation. Background Technology
[0002] Against the backdrop of rapid digital development, the manufacturing industry is undergoing a profound transformation from traditional models to intelligent and information-based approaches. The deep integration of digitalization and manufacturing technologies provides new impetus and support for intelligent manufacturing systems. Integrated scheduling, as a crucial component, fully integrates various technological elements such as intelligence and information, playing a vital role in improving the overall efficiency and intelligence level of manufacturing systems. Among these, scheduling system optimization is a core aspect of production and manufacturing, significantly driving progress in actual production processes. An efficient scheduling system can reduce production costs, effectively minimize waiting time in production processes, shorten the overall production cycle, enhance operational efficiency, and further guide the manufacturing industry into a new stage of high-efficiency development.
[0003] In traditional large-scale production scheduling, processing and assembly are typically handled separately, forming independent production stages, such as flow-shop scheduling and job-shop scheduling. However, with continuous social progress and the optimization of consumption structures, market demands are becoming increasingly diverse and personalized. This requires enterprises to consider not only production efficiency but also the differentiation and flexibility of customer needs. Therefore, production models are becoming increasingly complex, shifting towards multi-variety, small-batch complex production methods, which places higher demands on scheduling systems. In this context, continuing to separate product processing and assembly will hinder the efficient operation of the production system, thus impeding the improvement of overall enterprise capacity. Therefore, traditional scheduling models are clearly no longer suitable for the complex and dynamic development trend of the contemporary market. To better address the demand for multi-variety, small-batch products, a comprehensive scheduling model has emerged that represents the manufacturing constraints between complex product components using a tree structure and integrates "processing and assembly." This model breaks the limitations of separating product processing and assembly in traditional scheduling theory. Its main research directions include general comprehensive scheduling problems, multi-shop comprehensive scheduling problems, and flexible comprehensive scheduling problems.
[0004] With technological advancements, the importance of flexible manufacturing systems in the production field is becoming increasingly prominent. The scheduling problem for such systems is an NP-hard problem, possessing high flexibility, with multiple devices available for scheduling operations, effectively enhancing the scheduling elasticity of the manufacturing process. Therefore, how to select equipment and rationally schedule operations has become a key challenge in flexible integrated scheduling problems. In the research of flexible scheduling problems, mathematical programming is a typical optimization method based on mathematical theory. Its core idea is to formalize the objective function and constraints of the problem, express them as a mathematical model, and find the optimal solution in the feasible solution space, thus providing theoretical support for scheduling optimization. Currently, research on flexible scheduling often adopts heuristic methods, such as dynamic parallel integrated flexible scheduling methods based on equipment-driven and actual path approaches, flexible integrated scheduling methods based on reverse-order layer priority, and flexible integrated scheduling methods driven by bidirectional coordination mechanisms.
[0005] To address the issue of existing research neglecting the conflict between equipment collaborative allocation and processes within the same level, this invention proposes a flexible integrated scheduling method that considers process conflicts under equipment collaborative allocation. Summary of the Invention
[0006] In view of this, the present invention aims to propose a flexible integrated scheduling method that considers process conflicts under equipment collaborative allocation, in order to solve the problem that existing flexible integrated scheduling methods mostly use factors such as the scheduling path of processes in the product process tree, leaf node processes, and reverse scheduling as optimization factors, and rarely consider the allocation problem of processes at the same level and the conflicts that occur during the allocation process.
[0007] To achieve the above objectives, the present invention adopts the following technical solution: According to a first aspect of the present invention, a flexible integrated scheduling method considering process conflicts under equipment collaborative allocation is provided, the method comprising the following steps: Step 1: Based on the product's process tree topology, determine the sequence of each process step, and then determine the priority of each process step. Step 2: Starting with the process with the highest priority at the current level, calculate the completion time of the process on each device. Step 3: Determine if the level contains only one process. If yes, select the equipment that finishes processing earliest and proceed to Step 6. Otherwise, proceed to Step 4. Step 4: Establish an efficiency matrix R based on the processing completion time of each process at the current level on each device; Step 5: Apply the Hungarian method to the efficiency matrix R to enable the current level of processes to select appropriate equipment; Step 6: Check if all processes have been completed. If yes, proceed to Step 8; otherwise, proceed to Step 7 to continue scheduling. Step 7: The layer priority decreases, and the process continues to Step 2 to complete the subsequent scheduling process; Step 8: Determine whether there is a situation where the same process selects the same equipment during the equipment allocation process. If yes, select the process with the longest average processing time under the current equipment allocation and process it first. Otherwise, go to Step 9. Step 9: Determine if there is an optimal processing time node for all processes on the current equipment. If yes, move the process forward to that time node; otherwise, proceed to Step 10. Step 10: The scheduling process ends and exits.
[0008] Furthermore, in the aforementioned flexible integrated scheduling, the constraints between processes and equipment must satisfy: The overall process of the product is represented by a tree structure. The constraints between processes are described by directed edges between nodes, and there is a partial order relationship between processes. Each process has a unique process number, corresponding to multiple optional equipment; The processing time of a process is determined by the selected equipment; Each process must be assigned to a unique processing equipment, and the processing of each process by the equipment has a definite time dimension and a continuous processing. The same equipment can perform different processes, but not simultaneously. Except for the leaf node process, the necessary and sufficient condition for each process to be completed is that all its preceding processes have been completed. When all processes have been completed, that time point is considered the total time taken for the entire product scheduling process.
[0009] Furthermore, the method is based on a mixed-integer programming model, with the objective function being to minimize the maximum completion time. It is assumed that n is the number of operations, m is the number of machines, and there are constraints between operations and machines. The available machines for each operation are known, and the processing time for the same operation on each machine is also known. The specific modeling is as follows: (1) (2) (3) (4) (5) (6) in, This represents the time required for process i to be completed on equipment j; It determines whether process i should be processed on equipment i; Indicates the start time of process i; This represents the set of all preceding operations of operation i; It is to determine the processing sequence of processes i and l on equipment j; Equation (1) represents the optimization objective of this invention: minimizing the maximum completion time; Equation (2) represents that process i can only be assigned to one machine for processing during the production process; Equation (3) represents that process i can only begin processing after all its preceding processes have been completed; Equation (4) represents that when When, process i takes precedence over process i. Processing; Equation (5) indicates when At that time, the process Priority operation i is processed; Equation (6) indicates that when operation i and operation i are processed... When assigned to the same device j, the processing of the two devices is mutually exclusive and they cannot be processed simultaneously.
[0010] Furthermore, the layer priority is defined as follows: the priority order of process scheduling is defined as layer priority. Assuming that the product processing technology tree has n layers, the priority of the root node process is defined as 1; the priority of all descendant node processes of the root node process is defined as 2, and process nodes at the same layer are regarded as sibling nodes; and so on, until the priority of all nodes in the nth layer is defined as n; the priority of the root node process is defined as the lowest, and the priority of the process in the nth layer is the highest.
[0011] Furthermore, the efficiency matrix R is shown in the following equation: in, This indicates the completion time of process i on equipment j. If process i cannot be processed on equipment j, then let... If the number of processes is not equal to the number of equipment, that is If so, virtual rows or columns need to be added to make the efficiency matrix a square matrix. The element value in the virtual column is the minimum value of the original element in its row, and the element value in the virtual row is 0.
[0012] Furthermore, the average processing time of the subsequent process is defined as follows: for a certain process i, after determining the most suitable processing equipment for all processes with lower priority than process i using the Hungarian method, the average processing time of the corresponding subsequent process is further calculated. That is, under the current allocation scheme, the average total processing time of all subsequent processes of process i, as shown in the following formula: in Let i represent the set of all subsequent processes of process i. This indicates the number of processes contained in the set.
[0013] Furthermore, the optimal processing time node is defined as follows: for a certain process, the time point at which it can be processed as early as possible on the current equipment is called the optimal processing time node of that process.
[0014] According to a third aspect of the present invention, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation as described in the above embodiments.
[0015] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation.
[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention provides a flexible integrated scheduling method that considers process conflicts under equipment collaborative allocation. Unlike other flexible integrated scheduling methods, this invention fully considers the collaborative processing of process hierarchical scheduling and equipment resource allocation. Combining the layered structure of the product process tree and the multiple selection characteristics between process equipment in flexible integrated scheduling, this method starts from the highest priority process and establishes a dynamic efficiency matrix by calculating the completion time of each process on different equipment. It equates the process-equipment allocation problem to an assignment problem, dynamically reflects the processing capacity of different equipment under the current state, and realizes dynamic optimization of the scheduling process. 2. This invention constructs a flexible integrated scheduling model based on a mixed integer programming model. It treats the processing time and start time of each process as continuous decision variables, the variable representing whether a process is processed on the equipment as an integer decision variable, minimizes the total processing time as the objective function, and uses equipment resources and the partial order relationship between processes as constraints. Under a unified mathematical model framework, it realizes the organic coupling of multiple constraints and objective functions, thus providing a systematic description of the flexible scheduling problem and constructing a theoretical framework for the in-depth analysis of subsequent problems and the development of intelligent manufacturing. 2. This invention uses the Hungarian method to solve the efficiency matrix, ensuring that each process can be reasonably allocated to different equipment, thereby promoting the full utilization of equipment resources and minimizing the total processing time; 3. This invention proposes a conflict resolution strategy based on the average value of subsequent paths. This strategy can occupy equipment resources as early as possible and reduce the impact on the overall completion time. At the same time, it is combined with the horizontal optimization of layer priority to form a two-way collaborative optimization, further improving the global scheduling efficiency. Attached Figure Description
[0017] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart illustrating the framework of a flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation, as described in this invention. Figure 2 A schematic diagram of the manufacturing process tree for a complex product (D). Figure 3 This invention schedules complex products using a D-Gantt chart with 130 man-hours. Figure 4 A dynamic parallel integrated flexible scheduling method based on device-driven and actual path scheduling is used to schedule 140 man-hours of Gantt chart; Figure 5 To schedule 140 man-hours using a flexible integrated scheduling method based on reverse-order layer priority; Figure 6 A flexible integrated scheduling method based on a two-way coordination mechanism and signal-driven scheduling is used to schedule 140 man-hours in the Gantt chart. Detailed Implementation
[0018] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0019] Combination Figures 1-6 The present invention proposes a flexible integrated scheduling method for process conflicts under equipment collaborative allocation, the method comprising the following steps: Step 1: Based on the product's process tree topology, determine the sequence of each process step, and then determine the priority of each process step. Step 2: Starting with the process with the highest priority at the current level, calculate the completion time of the process on each device. Step 3: Determine if the level contains only one process. If yes, select the equipment that finishes processing earliest and proceed to Step 6. Otherwise, proceed to Step 4. Step 4: Establish an efficiency matrix R based on the processing completion time of each process at the current level on each device; Step 5: Apply the Hungarian method to the efficiency matrix R to enable the current level of processes to select appropriate equipment; Step 6: Check if all processes have been completed. If yes, proceed to Step 8; otherwise, proceed to Step 7 to continue scheduling. Step 7: The layer priority decreases, and the process continues to Step 2 to complete the subsequent scheduling process; Step 8: Determine whether there is a situation where the same process selects the same equipment during the equipment allocation process. If yes, select the process with the longest average processing time under the current equipment allocation and process it first. Otherwise, go to Step 9. Step 9: Determine if there is an optimal processing time node for all processes on the current equipment. If yes, move the process forward to that time node; otherwise, proceed to Step 10. Step 10: The scheduling process ends and exits.
[0020] The most significant characteristic of flexible integrated scheduling is the one-to-many relationship between processes and equipment, and the fact that the processing time of the same process is not unique on different equipment, resulting in a degree of variability in equipment selection. Therefore, flexible integrated scheduling is a typical application that achieves optimization by establishing a mixed-integer programming model. In this flexible integrated scheduling, the constraints between processes and equipment must satisfy: The overall process of the product is represented by a tree structure. The constraints between processes are described by directed edges between nodes, and there is a partial order relationship between processes. Each process has a unique process number, corresponding to multiple optional equipment; The processing time of a process is determined by the selected equipment; Each process must be assigned to a unique processing equipment, and the processing of each process by the equipment has a definite time dimension and a continuous processing. The same equipment can perform different processes, but not simultaneously. Except for the leaf node process, the necessary and sufficient condition for each process to be completed is that all its preceding processes have been completed. When all processes have been completed, that time point is considered the total time taken for the entire product scheduling process.
[0021] The method described in this invention is based on a mixed-integer programming model. The objective function is to minimize the maximum completion time. It is assumed that n is the number of processes, m is the number of machines, and there are constraints between processes and machines. The available machines for each process are known, and the processing time of the same process on each machine is also known. The specific modeling is as follows: (1) (2) (3) (4) (5) (6) in, This represents the time required for process i to be completed on equipment j; It determines whether process i should be processed on equipment i; Indicates the start time of process i; This represents the set of all preceding operations of operation i; It is to determine the processing sequence of processes i and l on equipment j; Equation (1) represents the optimization objective of this invention: minimizing the maximum completion time; Equation (2) represents that process i can only be assigned to one machine for processing during the production process; Equation (3) represents that process i can only begin processing after all its preceding processes have been completed; Equation (4) represents that when When, process i takes precedence over process i. Processing; Equation (5) indicates when At that time, the process Priority operation i is processed; Equation (6) indicates that when operation i and operation i are processed... When assigned to the same device j, the processing of the two devices is mutually exclusive and they cannot be processed simultaneously.
[0022] The layer priority is defined as follows: the priority order of process scheduling is defined as layer priority. Assuming that the product processing technology tree has n layers, the priority of the root node process is defined as 1; the priority of all descendant node processes of the root node process is defined as 2, and process nodes at the same layer are regarded as sibling nodes; and so on, until the priority of all nodes at the nth layer is defined as n; the priority of the root node process is defined as the lowest, and the priority of the process at the nth layer is the highest.
[0023] The efficiency matrix R is shown in the following equation: in, This indicates the completion time of process i on equipment j. If process i cannot be processed on equipment j, then let... If the number of processes is not equal to the number of equipment, that is If so, virtual rows or columns need to be added to make the efficiency matrix a square matrix. The element value in the virtual column is the minimum value of the original element in its row, and the element value in the virtual row is 0.
[0024] The average processing time of the subsequent processes is defined as follows: For a given process i, after determining the most suitable processing equipment using the Hungarian method for all processes with lower priority than process i, the average processing time of the corresponding subsequent processes is further calculated. That is, under the current allocation scheme, the average total processing time of all subsequent processes of process i, as shown in the following formula: in Let i represent the set of all subsequent processes of process i. This indicates the number of processes contained in the set.
[0025] The optimal processing time node is defined as follows: for a certain process, the time point at which it can be processed as early as possible on the current equipment is called the optimal processing time node of that process.
[0026] The flexible integrated scheduling method for process conflicts under equipment collaborative allocation described in this invention differs from other flexible integrated scheduling methods. This invention fully considers the collaborative processing of process hierarchical scheduling and equipment resource allocation. Combining the layered structure of the product process tree and the multiple selection characteristics between process equipment in flexible integrated scheduling, this method starts from the highest priority process and establishes a dynamic efficiency matrix by calculating the completion time of each process on different equipment. It equates the process-equipment allocation problem to an assignment problem, dynamically reflects the processing capacity of different equipment under the current state, and realizes dynamic optimization of the scheduling process.
[0027] This invention uses the Hungarian method to solve the efficiency matrix, ensuring that each process can be reasonably allocated to different equipment, thereby promoting the full utilization of equipment resources and minimizing the total processing time.
[0028] This invention proposes a conflict resolution strategy based on the average value of subsequent paths. This strategy can occupy equipment resources as early as possible and reduce the impact on the overall completion time. At the same time, it is combined with the horizontal optimization of layer priority to form a two-way collaborative optimization, which further improves the global scheduling efficiency.
[0029] Below, with Figure 2 The following is a scheduling demonstration using the complex product D processing technology tree as an example.
[0030] Step 1: Starting with the process with the highest layer priority, calculate the completion times of processes D10 and D18 on each machine. D10: D18: An efficiency matrix is then constructed based on this. Since the matrix is not a square matrix, virtual rows are added, and the element values are set to 0 to convert it into a square matrix. The adjusted square matrix is then solved using the Hungarian method, resulting in the process-equipment allocation scheme: process D10 is allocated to equipment M4, and process D18 is allocated to equipment M1.
[0031] Step 2: Delete the completed processes D10 and D18, decreasing the layer priority. This layer includes processes D9, D17, and D20. Calculate their processing completion time on each machine. Since processes D9 and D17 have predecessor processes, calculations must be performed under the condition of satisfying the predecessor and successor constraints. Process D20 has no predecessor constraints, so its processing completion time on each machine is calculated directly. Following the matrix adjustment method in Step 1, the initial efficiency matrix is transformed into a square matrix by adding virtual rows, establishing efficiency matrix R2, as shown below: The Hungarian method is applied to the efficiency matrix R2 to obtain the process-equipment allocation scheme. Based on this, the equipment corresponding to process D9 is determined to be M1, the equipment corresponding to D17 is M4, and the equipment corresponding to D20 is M3.
[0032] Step 3: There are 5 processes with a layer priority of 5, namely D5, D8, D12, D16, and D19. Based on the process constraint characteristics, they are divided into two categories: (1) Operations D5 and D12 are leaf node operations in the process tree, with no immediate predecessor constraint relationship. The calculation of processing time does not need to consider the influence of the preceding operations. (2) Processes D8, D16, and D19 have clear preceding processes and must simultaneously satisfy the dual constraint relationship of immediate predecessor constraint and immediate successor constraint.
[0033] Therefore, under the constraints, the processing time of each of the five processes at this level on each piece of equipment is calculated, and the corresponding efficiency matrix R3 is established. Since the number of processes and the number of equipment in this matrix do not match, it is not a square matrix. Therefore, a virtual column needs to be added to transform it into a square matrix. The elements of the virtual column are the minimum values in their respective rows. The resulting efficiency matrix R3 is shown below: The Hungarian method was used to apply the adjusted efficiency matrix to obtain the process-equipment allocation scheme as follows: process D5 is allocated to equipment M1, D16 is allocated to equipment M2, D12 and D19 are both allocated to equipment M3, and D8 is allocated to equipment M4.
[0034] Step 4: Since processes D12 and D19 are both assigned to the same equipment, they are treated as a single process and processed on equipment M3. Based on the current equipment processing status, the processing completion time of processes from the fourth layer to the second layer on each equipment is calculated. An efficiency matrix is established and transformed into a square matrix. The Hungarian method is applied for allocation, resulting in the following process-equipment allocation scheme: processes D11, D6, and D2 are assigned to equipment M1; processes D4, D13, and D1 are assigned to equipment M2; processes D7 and D3 are assigned to equipment M3; and processes D15 and D14 are assigned to equipment M4.
[0035] Step 5: To resolve the conflict between processes D12 and D19, a conflict resolution strategy based on the average of subsequent paths is adopted. The subsequent processes for process D12 are D11, D6, D2, and D1. The subsequent processes for process D19 are D15, D14, D13, and D1. Therefore, D19 is processed first on equipment M3 due to time constraints.
[0036] Step 6: By checking whether there is an optimal processing time node for all processes on the current equipment, it was found that process D15 has an optimal processing time node on the current equipment. Therefore, the start time of process D15 is moved forward to t=50, and the start times of its subsequent processes D14 and D13 are moved forward to t=70 and t=90 respectively. Thus, process tree D has been scheduled, totaling 130 man-hours. Its scheduling Gantt chart is shown below. Figure 3 As shown.
[0037] To further illustrate the superiority of this invention, it is now compared with a dynamic parallel integrated flexible scheduling method based on device-driven and actual path, a flexible integrated scheduling method based on reverse-order layer priority, and a flexible integrated scheduling method driven by a two-way coordination mechanism signal. Their scheduling Gantt charts are as follows: Figure 4 , Figure 5 and Figure 6 As shown in the experimental results, the product of the present invention requires less processing time and has a higher overall equipment utilization rate.
[0038] For the flexible scheduling results of complex product D, the processing time of the dynamic parallel integrated flexible scheduling method based on equipment driving and actual path, the flexible integrated scheduling method based on reverse order layer priority, and the flexible integrated scheduling method based on two-way coordination mechanism signal driving is 140 man-hours, while the processing time of the present invention is 130 man-hours, which is less.
[0039] The overall equipment utilization rates of the four methods mentioned above are shown in Table 1. The overall equipment utilization rate of the present invention in the flexible scheduling system reached 82.8%, which is 2.6%, 8.6% and 4.7% higher than the dynamic parallel integrated flexible scheduling method based on equipment driving and actual path, the flexible integrated scheduling method based on reverse order layer priority and the flexible integrated scheduling method based on bidirectional coordination mechanism signal driving, respectively.
[0040] Table 3 Overall Utilization Analysis of Flexible Dispatch System Equipment The reason why this invention achieves better scheduling performance in flexible integrated scheduling systems is mainly because: (1) Starting from the layer priority of the process, this invention updates the processing completion time of each process at the same level on each device in real time, establishes a dynamic efficiency matrix, treats the process-device allocation as an assignment problem, and uses the Hungarian method to realize the allocation of processes and devices at the same level, ensuring that each device follows the "busiest as possible" principle at the same level. From the Gantt chart analysis results of this invention, all processes at the 5th level are distributed on each device for processing, which improves the load balance of resources and realizes the overall optimization of equipment utilization efficiency. However, the other three methods do not distribute all processes at the 5th level on all devices for processing, thus increasing the idle time of the devices. Taking device M4 as an example, this invention achieves seamless and efficient scheduling, with the device utilization rate reaching 100% and the total processing time being 90 man-hours. Although the dynamic parallel integrated flexible scheduling method based on device drive and actual path also achieves full load of device resources, the total man-hours are extended to 105 man-hours. In the flexible integrated scheduling method based on reverse layer priority and the flexible integrated scheduling method based on bidirectional coordination mechanism signal drive, device M4 is not fully utilized.
[0041] (2) To resolve conflicts arising when allocating processes and equipment at the same level, this invention uses the target process i... The processing order of conflicting processes is determined based on the established criteria, achieving vertical optimization of the scheduling process. For example, processes D12 and D19 are both assigned to the same equipment, thus causing a conflict during scheduling. Therefore, according to the conflict resolution strategy based on the average of subsequent paths, this invention prioritizes the processing of process D19, allowing subsequent process D15 to be processed as early as possible. After applying the dynamic parallel integrated flexible scheduling method based on equipment-driven and actual paths, and the flexible integrated scheduling method based on bidirectional coordination mechanism signal-driven methods, the starting processing time of process D15 is 65 man-hours in both cases, which is 15 man-hours later than in this invention. After applying the flexible integrated scheduling method based on reverse-order priority, the starting processing time of process D15 is the same as in this invention, but the total processing time of this invention is reduced by 10 man-hours compared to the total processing time of the flexible integrated scheduling method based on reverse-order priority, further demonstrating the superiority of this invention.
[0042] This invention constructs a flexible integrated scheduling model based on a mixed integer programming model. It treats the processing time and start time of each process as continuous decision variables, the variable representing whether a process is processed on the equipment as an integer decision variable, minimizes the total processing time as the objective function, and uses equipment resources and the partial order relationship between processes as constraints. Under a unified mathematical model framework, it achieves the organic coupling of multiple constraints and objective functions, thus providing a systematic description of the flexible scheduling problem and constructing a theoretical framework for the in-depth analysis of subsequent problems and the development of intelligent manufacturing.
[0043] Meanwhile, this invention, from the perspective of process hierarchy, treats the allocation problem of process-equipment at each level as an assignment problem and establishes a dynamic efficiency matrix. Subsequently, the Hungarian method is applied to find suitable matching schemes, enabling processes at each level to be distributed across various devices for processing, thus achieving rational resource utilization. Furthermore, addressing the issue of conflicts arising when processes select equipment, a conflict resolution strategy based on the average of subsequent paths is proposed. This implements bidirectional optimization at both horizontal and vertical levels, reducing equipment idle time and effectively improving overall scheduling efficiency. This invention not only possesses high theoretical rigor but also demonstrates good optimization results in practical applications, opening up new avenues of thought for flexible integrated scheduling problems.
[0044] This invention proposes an electronic device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the flexible integrated scheduling method that considers process conflicts under equipment collaborative allocation.
[0045] This invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the flexible integrated scheduling method that considers process conflicts under equipment collaborative allocation.
[0046] The memory in this application embodiment can be volatile memory or non-volatile memory, or it can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DRRAM). It should be noted that the memory used in the methods described in this invention is intended to include, but is not limited to, these and any other suitable types of memory.
[0047] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application 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 wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. 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 integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., high-density digital video discs (DVDs)), or semiconductor media (e.g., solid-state drives (SSDs)).
[0048] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, detailed descriptions are omitted here.
[0049] It should be noted that the processor in the embodiments of this application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by the integrated logic circuitry in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above methods.
[0050] The above provides a detailed description of the flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.
Claims
1. A flexible integrated scheduling method considering process conflicts under equipment collaborative allocation, characterized in that, The method includes the following steps: Step 1: Based on the product's process tree topology, determine the sequence of each process step, and then determine the priority of each process step. Step 2: Starting with the process with the highest priority at the current level, calculate the completion time of the process on each device. Step 3: Determine if the level contains only one process. If yes, select the equipment that finishes processing earliest and proceed to Step 6. Otherwise, proceed to Step 4. Step 4: Establish an efficiency matrix R based on the processing completion time of each process at the current level on each device; Step 5: Apply the Hungarian method to the efficiency matrix R to enable the current level of processes to select appropriate equipment; Step 6: Check if all processes have been completed. If yes, proceed to Step 8; otherwise, proceed to Step 7 to continue scheduling. Step 7: The layer priority decreases, and the process continues to Step 2 to complete the subsequent scheduling process; Step 8: Determine whether there is a situation where the same process selects the same equipment during the equipment allocation process. If yes, select the process with the longest average processing time under the current equipment allocation and process it first. Otherwise, go to Step 9. Step 9: Determine if there is an optimal processing time node for all processes on the current equipment. If yes, move the process forward to that time node; otherwise, proceed to Step 10. Step 10: The scheduling process ends and exits.
2. The flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation according to claim 1, characterized in that: In the aforementioned flexible integrated scheduling, the constraints between processes and equipment must satisfy the following: The overall process of the product is represented by a tree structure. The constraints between processes are described by directed edges between nodes, and there is a partial order relationship between processes. Each process has a unique process number, corresponding to multiple optional equipment; The processing time of a process is determined by the selected equipment; Each process must be assigned to a unique processing equipment, and the processing of each process by the equipment has a definite time dimension and a continuous processing. The same equipment can perform different processes, but not simultaneously. Except for the leaf node process, the necessary and sufficient condition for each process to be completed is that all its preceding processes have been completed. When all processes have been completed, that time point is considered the total time taken for the entire product scheduling process.
3. The flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation according to claim 2, characterized in that: The method is based on a mixed-integer programming model, with the objective function being to minimize the maximum completion time. It is assumed that n is the number of operations, m is the number of machines, and there are constraints between operations and machines. The available machines for each operation are known, and the processing time for the same operation on each machine is also known. The specific modeling is as follows: （1） （2） （3） （4） （5） （6） in, This represents the time required for process i to be completed on equipment j; It determines whether process i should be processed on equipment i; Indicates the start time of process i; This represents the set of all preceding operations of operation i; It is to determine the processing sequence of processes i and l on equipment j; Equation (1) represents the optimization objective of this invention: minimizing the maximum completion time; Equation (2) represents that process i can only be assigned to one machine for processing during the production process; Equation (3) represents that process i can only begin processing after all its preceding processes have been completed; Equation (4) represents that when When, process i takes precedence over process i. Processing; Equation (5) indicates when At that time, the process Priority operation i is processed; Equation (6) indicates that when operation i and operation i are processed... When assigned to the same device j, the processing of the two devices is mutually exclusive and they cannot be processed simultaneously.
4. The flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation according to claim 1, characterized in that: The layer priority is defined as follows: the priority order of process scheduling is defined as layer priority. Assuming that the product processing technology tree has n layers, the priority of the root node process is defined as 1; the priority of all descendant node processes of the root node process is defined as 2, and process nodes at the same layer are regarded as sibling nodes; and so on, until the priority of all nodes at the nth layer is defined as n; the priority of the root node process is defined as the lowest, and the priority of the process at the nth layer is the highest.
5. The flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation according to claim 1, characterized in that: The efficiency matrix R is shown in the following equation: in, This indicates the completion time of process i on equipment j. If process i cannot be processed on equipment j, then let... If the number of processes is not equal to the number of equipment, that is If so, virtual rows or columns need to be added to make the efficiency matrix a square matrix. The element value in the virtual column is the minimum value of the original element in its row, and the element value in the virtual row is 0.
6. The flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation according to claim 1, characterized in that: The average processing time of the subsequent processes is defined as follows: For a given process i, after determining the most suitable processing equipment using the Hungarian method for all processes with lower priority than process i, the average processing time of the corresponding subsequent processes is further calculated. That is, under the current allocation scheme, the average total processing time of all subsequent processes of process i, as shown in the following formula: in Let i represent the set of all subsequent processes of process i. This indicates the number of processes contained in the set.
7. A flexible integrated scheduling method for considering process conflicts under equipment collaborative allocation as described in claim 1, characterized in that: The optimal processing time node is defined as follows: for a certain process, the time point at which it can be processed as early as possible on the current equipment is called the optimal processing time node of that process.
8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the steps of the method as claimed in any one of claims 1-7.
9. A computer-readable storage medium, characterized in that, It stores a computer program thereon, the computer program being used to cause the computer to perform the steps of the method as described in any one of claims 1-7.