Rapid screening and dispatching rules, methods and devices

Abstract

A method and device for quickly screening dispatching rules. The method for quickly screening dispatching rules includes the following steps: obtaining a dispatching result and a corresponding situation. Establishing a dispatching rule exploration table according to the dispatching result, wherein the dispatching rule exploration table is composed of dispatching rules and processes. Calculating the participation ratio of each dispatching rule in the dispatching rule exploration table; calculating the contribution ratio according to the participation ratio, obtaining a screening value, and determining the selected dispatching rule based on the screening value.

Description

Technical Field

[0001] The invention relates to a method and a device for fast screening of work assignment rules. Background Art

[0002] The current method of selecting dispatching rules is to make subjective judgments based on the current production environment through human or experience. However, there are many types of dispatching rules and combinations that can be selected. The traditional method of simulating the scheduling results output by the program in a rule-based manner and then filtering out the appropriate dispatching rules is costly and time-consuming. In a work site that emphasizes production efficiency, it is not easy to filter out dispatching rules that are suitable for the current corresponding situation within an effective time. A mechanism is needed to quickly obtain dispatching rules. Therefore, how to quickly screen dispatching rules is one of the current research and development directions. Summary of the invention

[0003] The invention relates to a method and a device for quickly screening work assignment rules.

[0004] According to one embodiment of the present invention, a method for quickly screening dispatching rules is proposed, and the method for quickly screening dispatching rules includes the following steps: Obtaining a scheduling result and a corresponding scenario. Establishing a dispatching rule exploration table based on the scheduling result, wherein the dispatching rule exploration table is composed of dispatching rules and process steps. Calculating the participation ratio of each dispatching rule in the dispatching rule exploration table; calculating the contribution ratio based on the participation ratio, obtaining a screening value, and determining the selected dispatching rule based on the screening value.

[0005] According to another embodiment of the present invention, a device for quickly screening dispatching rules is provided, and the device for quickly screening dispatching rules includes a data unit and an exploration unit. The data unit obtains the scheduling result or the corresponding situation; the exploration unit is coupled to the data unit, and establishes a dispatching rule exploration table according to the scheduling result, wherein the dispatching rule exploration table is composed of dispatching rules and process steps, calculates the participation ratio of each dispatching rule in the dispatching rule exploration table, calculates the contribution ratio according to the participation ratio, obtains the screening value, and determines the selected dispatching rule according to the screening value.

[0006] In order to better understand the above and other aspects of the present invention, the following is a detailed description of preferred embodiments with reference to the accompanying drawings as follows: BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 A block diagram of a device for rapid screening and dispatching rules according to an embodiment of the present invention is shown;

[0008] Figure 2A and Figure 2B A schematic diagram showing an exemplary exploration unit according to an embodiment of the present invention is shown;

[0009] Figure 3A Gantt diagram is shown for generating exploration scheduling data in a rule-based manner according to another embodiment of the present invention;

[0010] Figure 4 A schematic diagram showing an example of achieving convergence using a genetic algorithm according to an embodiment of the present invention;

[0011] Figure 5A and Figure 5B A schematic diagram showing an example of extracting a dispatch rule by using a dispatch rule exploration table established by multiple solutions according to an embodiment of the present invention;

[0012] Figure 6 A flowchart of an example of a fast screening and dispatching rule according to an embodiment of the present invention is shown.

[0013] In the above drawings, the meanings of the reference numerals are as follows:

[0014] 10: Fast screening and dispatching rule device

[0015] 12: Processing Unit

[0016] 14: Data Unit

[0017] 16: Exploration Unit

[0018] 18: Detection unit

[0019] 19: User Interface

[0020] Up: Take the upper part

[0021] Down: take down part

[0022] Mid: Section Line

[0023] Steps: S62, S64, S66, S68 DETAILED DESCRIPTION

[0024] The technical terms used in this specification refer to the customary terms in the technical field. If some terms are explained or defined in this specification, the interpretation of these terms shall be based on the explanation or definition in this specification. Each embodiment of the present disclosure has one or more technical features. Under the premise of possible implementation, a person with ordinary knowledge in the technical field may selectively implement some or all of the technical features in any embodiment, or selectively combine some or all of the technical features in these embodiments.

[0025] Figure 1 FIG. 1 is a block diagram of a fast screening and dispatching algorithm device 10 according to an embodiment of the present invention. The fast screening and dispatching algorithm device 10 includes a data unit 14 and a mining unit 16. The mining unit 16 is coupled to the data unit 14.

[0026] In one embodiment, the data unit 14 and the mining unit 16 may be a hardware, such as a central processing unit (CPU), or other programmable general-purpose or special-purpose micro control unit (MCU), microprocessor, digital signal processor (DSP), programmable controller, application specific integrated circuit (ASIC), graphics processing unit (GPU), arithmetic logic unit (ALU), complex programmable logic device (CPLD), field programmable gate array (FPGA) or other similar components or combinations of the above components. In one embodiment, the data unit 14 and the mining unit 16 may include firmware, the above hardware and / or software or machine executable code stored in a memory and loaded, read, written and / or executed by the above hardware, but the present invention is not limited thereto.

[0027] In one embodiment, the memory of the data unit 14 can be a hardware with memory or storage function, and the memory or storage hardware can be, for example, a volatile memory or a non-volatile memory, or any type of fixed or removable random access memory (RAM), register, read-only memory (ROM), flash memory, hard disk drive (HDD), solid state drive (SSD) or similar elements or a combination of the above elements. The data unit 14 can store at least one scheduling result and at least one corresponding scenario, as well as a corresponding original dispatching rule.

[0028] In one embodiment, the user interface 19 may be a device with a display function, such as a screen, a mobile phone, a computer, a terminal or a notebook computer, but the present invention is not limited thereto.

[0029] In one embodiment, the mining unit 16 can infer the function of selecting the dispatching rule based on the scheduling result and the corresponding situation stored, retrieved or calculated by the data unit 14. For example, for a given scheduling result and the corresponding situation, the dispatching rule that is most suitable for the scheduling result can be mined by event mining; please refer to Figure 2A and Figure 2B A schematic diagram of an example of an exploration unit according to an embodiment of the present invention is shown. The scheduling result may be, for example, a Gantt chart; the corresponding scenario may be, for example, a printed circuit board (PCB) field, where available resources are, for example, machines and work orders, and 4 machines and 3 work orders are captured, which can be regarded as the current field scheduling result, but the present invention is not limited thereto. The scheduling goal of this application example is to minimize the completion time of the last process. The Gantt chart of this example is generated by rule-based scheduling technology.

[0030] Please refer to Figure 2A In one embodiment, the four machines are M1, M2, M3 and M4, the three work orders are J1, J2 and J3, M2(09), M3(10), M2(09), M1(12), M1(12), M4(15) and M4(15), there are 7 process steps (operations, OP) in total, and the process steps are numbered 1 to 7 in sequence, that is, M2(09) is the process step 1 number, M3(10) is the process step 2 number, and so on, M4(15) is the process step 7 number. M1(12)->M4(15) is the process of work order 1, M3(10)->M2(09)->M4(15) is the process of work order 2, and M2(09)->M1(12) is the process of work order 3. The 09 in M2(09) means that if machine 2 starts to execute from 0 unit time, it must execute 9 unit time to complete. 0 is the start time and 9 is the end time, which are collectively referred to as the start and end time. In one embodiment, the process and the start and end time are included in the corresponding context.

[0031] In 2A, J1:M1(12)->M4(15) means that the J1 work order must spend 12 time units to complete the M1(12) process step before the M1 machine. After the M1 machine is completed, the M4 machine must spend 15 time units to complete the M4(15) process step, thus completing the M1(12)->M4(15) process in J1; J2 completes the M3(10), M2(09) and M4(15) process steps in sequence; J3 completes the M2(09) and M1(12) process steps in sequence.

[0032] Since the scheduling goal of this example is to minimize the completion time of the last process. Figure 2BIn the work dispatch rule exploration table, the horizontal axis of the table is the work dispatch rule, and the vertical axis is the process number. The work dispatch rule here can refer to Table 1, which has the definition of each work dispatch rule. The types of work dispatch rules of the present invention are not limited to Table 1. In one embodiment, the work dispatch rule exploration table can be stored in the data unit 14.

[0033]

[0034] Table 1

[0035] In one embodiment, Figure 2A The Gantt chart of the scheduling result can be generated by the data unit 14 using the optimal approximate solution technology. This technology obtains the optimal approximate solution in a convergence calculation manner and stores it in the data unit 14. The exploration unit 16 obtains the data unit 14, for example, using a genetic algorithm (GA) to generate Figure 2A The Gantt chart has a completion time unit of 63, and the processes are M2(09), M3(10), M2(09), M1(12), M1(12), M4(15), and M4(15) in order; please refer to Figure 3 , Figure 3 A schematic diagram of an example of a genetic algorithm completing convergence according to an embodiment of the present invention is shown. The X-axis is the number of GA executions. Each execution generates a Gantt chart. The Y-axis is the completion time unit, where the shortest completion time is taken. It can be seen from the figure that the more times the GA is executed, the shorter the completion time is, and the optimal approximate solution can be converged. That is, multiple sets of dispatching rules are obtained to meet the shortest completion time. The optimal approximate solution generator can use non-rule scheduling technology, which has an optimization program. This program can continuously search in the direction of the optimal scheduling solution and gradually obtain the approximate optimal scheduling result. It is not limited to the GA used above. For example, an evolutionary algorithm can also complete the above function.

[0036] Figure 2A The Gantt chart can also be extracted from data unit 14 from a computer equipment manufacturer's recent short-term work order process and corresponding working hours. Please refer to Figure 4 . Figure 4 A Gantt diagram of scheduling data for exploration generated in a rule-based manner according to another embodiment of the present invention is shown. The present invention is not limited thereto.

[0037] In one embodiment, if the first come first service (RT) dispatching rule is adopted in the exploration unit 16, the earlier the process can start, the higher the priority. Figure 2BThe number in the brackets represents the time point when the pending process of the work order can be executed. According to RT, starting from 0 unit time, if M2(9) of the J3 process number 1 is served first, the machine M2 serves 9 time units first, because it meets RT, that is, it meets the dispatching rule RT, so the process with the RT column located at number 1 in the dispatching rule set table can be represented by the binary code 1; starting from 0 unit time, if M3(10) of the J2 process step number 2 is served first, the machine M3 serves 10 time units first, because it meets RT, that is, it meets the dispatching rule RT, so the process step with the RT column located at number 2 in the dispatching rule set table can be represented by the binary code 1; starting from 0 unit time, if M2(09) of the J2 process step number 3 is served first, the machine M2 serves 9 time units first, because it does not meet RT, that is, it does not meet the dispatching rule RT, so the process with the RT column located at number 3 in the dispatching rule set table can be represented by the binary code 0; and so on. Figure 2B In the dispatch rule set table, the RT column is 1100101. Different dispatch rules can be deduced in the same way. For example, the PD column is 0000001, which can fill in the dispatch rule set table of Figure 2; PD is the "dynamic production distance multiple" in Table 1.

[0038] In one embodiment, please refer to Figure 5A and Figure 5B . Figure 5A and Figure 5B FIG. 1 is a schematic diagram showing an example of extracting a dispatch rule using a dispatch rule exploration table established by multiple solutions according to an embodiment of the present invention. In the exploration unit 16, if Figure 2A The Gantt chart is executed 200 times, generating 200 Gantt charts. The participation ratio can be based on the proportion of the dispatching rule, for example: Figure 5A The participation ratio in the example is 0.143 for PD, which is obtained by 1 / 7 based on the number of 0s and 1s in the PD column of the dispatch rule exploration table; the RT column is 0.571 based on 4 / 7, and the total number of processes in this example is 7. The participation ratio can be obtained by, for example, summing up all processes that meet the dispatch rule in the dispatch rule exploration table and dividing it by the total number of processes.

[0039] In one embodiment, please refer to Figure 5B The contribution ratio can be used to screen the contribution of multiple solutions according to the distribution rule. The contribution ratio can calculate the average participation ratio of Up and Down. In the exploration unit 16, Figure 5A Will Figure 3In the horizontal section, the average participation ratio of Up is taken on the section line, that is, the upper part is taken, and the average participation ratio of Down is taken on the section line, that is, the lower part is taken. In this embodiment, the exploration unit 16 takes the Gantt chart data from the 97th to the 200th time, a total of 103 times of data, that is, the optimal solution area with the shortest completion time is taken. If the number of Up is 51, the number of Down is 52; the average participation ratio of Up is Figure 5B The PD column is Σ51 participation ratio / 51=average participation ratio of Up, here is 0.12; the average participation ratio of Down in the PD column is Σ51 participation ratio / 52=average participation ratio of Down, here is 0.18. Other dispatching rules are similar. The contribution ratio can be calculated by, for example, calculating the summed average of multiple participation ratios above and below a profile line.

[0040] In one embodiment, in the exploration unit 16, the calculation of the filter value is as follows:

[0041] Screening value = (average participation rate of Up + average participation rate of Down) × average participation rate of Down / average participation rate of Up ……………… (1)

[0042] The screening value of the PD column in 5B is 0.45. The higher the screening value here, the better, so that the smaller the dispatching rule in Table 1 can be met. The dispatching rule is selected with a higher screening value. Figure 5B For example, you can select RT, DS_PT and DS_OPN, where DS_PT is the "late delivery crisis degree_time angle" and DS_OPN is the "late delivery crisis degree_process number angle". If it is the dispatching rule of Wangda, the calculation of the screening value is the formula 2:

[0043] Screening value = (average participation rate of Up + average participation rate of Down) × average participation rate of Up / average participation rate of Down ………………(2)

[0044] The screening value can be calculated by, for example, summing up and multiplying and dividing a plurality of the contribution ratios as described above. As long as the method of calculating the screening value does not deviate from the spirit of the method, the screening value of the present invention is not limited to the above formula.

[0045] In one embodiment, a user interface 19 is provided, through which scheduling results and corresponding situations are input, scheduling targets and available resources are selected, and selection dispatching rules are output.

[0046] In one embodiment, the device 10 for quickly screening dispatching rules includes a detection unit 18, which is coupled to the exploration unit 16; the detection unit 18 is coupled to the data unit 14, and the detection unit 18 may be a hardware component that is the same as the hardware component of the aforementioned exploration unit 16, which will not be repeated here. The detection unit 18 detects the similarity between the selection dispatching rule and the scheduling result obtained by the data unit 14 and the original dispatching rule of the corresponding situation. The exploration unit 16 performs multiple calculations on the selection dispatching rule, ranks them in order according to the screening value, and then compares them with the ranking of the original dispatching rule in the data unit 14. Please refer to Table 2, Table 3 and Table 4. With 15 work orders and 5 machines as the field scenario (in one embodiment, the field scenario is included in the corresponding scenario), 10 data sets are simulated, and the working hours are randomly generated from 1 to 100. The vertical axis of Table 2 is the original dispatching rule, and the horizontal axis is the data set, average and ranking. Among them, the dispatching rule ranking is RT first, MOPNR (remaining number of processes to be done_take the most) second, S_OPN (order urgency_process number angle) third, NINQ (machine resource competition_take the least) fourth, WINQ (machine resource competition_take the most) fourth. ) is ranked 5th, and the rest are referred to Table 2; the horizontal axis of Table 3 is the dispatching rule, and the vertical axis is the data set, average and ranking, among which the dispatching rule ranking is RT ranked 1st, S_OPN ranked 2nd, MWKR (measurement of the degree of unfinished orders_shortening) ranked 3rd, MOPNR ranked 4th, and SK (current semi-finished product time progress) ranked 5th, and the rest are referred to Table 3; the vertical axis of Table 4 is the ranking of the original dispatching rule and the ranking of the selected dispatching rule of the present invention, and the horizontal axis is the dispatching rule. The correlation between the two rankings can be calculated to obtain their similarity relationship, for example, the Pearson correlation coefficient method is used. This method is widely used to measure the linear dependence between two variables. The two rankings are brought in, and the value of 0.8 can be obtained, which represents a high correlation, that is, a high similarity in this case. Therefore, the selected dispatching rule has a high similarity with the original dispatching rule ranking, so the selected dispatching rule can replace the original dispatching rule, saving the time of simulating the dispatching rule by rule method and the time of screening the dispatching rule. The present invention may use any method that can calculate the linear dependence between two variables, and is not limited to the Pearson correlation coefficient method.

[0047]

[0048]

[0049]

[0050] In one embodiment, the detection unit 18 detects the similarity between the selection and dispatching rules and the scheduling results generated by the data unit 14 according to the optimal approximate solution technology. The exploration unit 16 performs multiple calculations of the selection and dispatching rules, and ranks them in order according to the screening values, and then compares them with the original dispatching rules in the data unit 14. Please refer to Table 5, Table 6 and Table 7, with 10 work orders and 10 machines as the field scenario, simulating 10 data sets, and the working hours are randomly generated from 1 to 100; Table 5, Table 6 and Table 7 are analogous to Table 2, Table 3 and Table 4, wherein the vertical axis of Table 7 is the ranking of dispatching rules generated according to the optimal approximate solution technology and the ranking of the selection and dispatching rules of the present invention, and the horizontal axis is the dispatching rules. The correlation between the two rankings is calculated to obtain their similarity relationship. For example, the Pearson correlation coefficient is widely used to measure the linear dependence between two variables. The two rankings are brought in, and the value 0.811765 can be obtained, which means that the correlation is high, that is, the similarity of this case is high. Therefore, the selected dispatching rule has a high ranking similarity with the original dispatching rule, so the selected dispatching rule can replace the dispatching rule generated by the optimal approximate solution technology, saving the time of simulating the dispatching rule in a rule-based manner and the time of screening the dispatching rule. The present invention can use any method that can calculate the linear dependence between two variables, not limited to the Pearson correlation coefficient method.

[0051]

[0052]

[0053]

[0054] Figure 6 A flowchart of a fast screening and dispatching rule method according to an embodiment of the present invention is shown. The following describes an embodiment of the fast screening and dispatching rule method executed by the fast screening and dispatching rule device 10 .

[0055] In step S62, the exploration unit 16 obtains the stored scheduling results or corresponding scenarios from the data unit 14; in one embodiment, the exploration unit 16 obtains the scheduling results or corresponding scenarios from the user interface 19; in one embodiment, a scheduling target and an available resource are selected to output the selection dispatching rule; in one embodiment, the data unit 14 may execute irregular scheduling techniques such as the scheduling results obtained by the aforementioned GA; in one embodiment, the exploration unit 16 may also execute irregular scheduling techniques to calculate scheduling results and obtain scheduling results; the present invention is not limited to this.

[0056] In step S64, the exploration unit 16 establishes a dispatch rule exploration table according to the scheduling result, wherein the dispatch rule exploration table is composed of dispatch rules and process steps; the horizontal axis of the dispatch rule exploration table is the dispatch rule, and the vertical axis is the aforementioned process; in the dispatch rule exploration table, the process column that meets the dispatch rule is represented by a binary code 1, and the process column that does not meet the dispatch rule is represented by a binary code 0. The present invention is not limited to this representation.

[0057] In step S66, the exploration unit 16 calculates the participation ratio of each dispatch rule in the dispatch rule exploration table. The participation ratio is obtained by summing up all dispatch rules in the dispatch rule exploration table and dividing it by the total number of processes. For example, the participation ratio in FIG5 , where PD is 0.143, is obtained by 1 / 7 according to the number of 0 and 1 in the PD column of the dispatch rule exploration table; the RT column is obtained by 4 / 7 to obtain 0.571, and the total number of processes in this example is 7.

[0058] In step S68, the exploration unit 16 calculates the contribution ratio according to the participation ratio, obtains the screening value, and determines the selection and dispatching rule based on the screening value. The contribution ratio is calculated by calculating the summed average of multiple participation ratios above and below a profile line. The screening value is calculated by summing and multiplying and dividing multiple contribution ratios. The selection and dispatching rule selects the one with the highest screening value.

[0059] According to an embodiment of the present invention, simply calculating the participation ratio and the contribution ratio and then calculating the screening value can save the time and cost of filtering out suitable dispatching rules from the simulation scheduling results, thereby achieving the goal of quickly screening dispatching rules.

[0060] According to an embodiment of the present invention, the similarity with the quick screening dispatching rule of the present invention can be confirmed by detecting the actual field data and the similar field data. From Table 2, Table 3, Table 4, Table 5, Table 6 and Table 7, it can be seen that the selected dispatching rule and the actually executed dispatching rule have a high degree of similarity. Therefore, the quick screening dispatching rule of the present invention is used to replace the screening of the existing regular dispatching rule.

[0061] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific 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 in the scope of protection of the present invention.

Claims

1. A method for rapid screening of work assignment rules, characterized in that: include: A data unit of the processor obtains a plurality of scheduling results and corresponding scenarios, wherein the corresponding scenarios include field scenarios, processes, and start and end times, and the scheduling results are obtained by the processor executing a computer optimization program to obtain an optimal approximate solution, and the scheduling results satisfy the shortest completion time; The exploration unit of the processor establishes a dispatch rule exploration table according to the multiple scheduling results, wherein the dispatch rule exploration table is composed of multiple dispatch rules and multiple process steps, and the dispatch rule exploration table reflects the participation status of the multiple dispatch rules in the multiple process steps respectively; The mining unit of the processor calculates, by means of the mining unit, a participation ratio of each of the dispatching rules in the dispatching rule mining table compared to the plurality of process steps; and The exploration unit of the processor calculates the contribution ratio based on the summed average of the multiple participation ratios above and below the profile, obtains a screening value based on the sum and multiplication and division of the multiple contribution ratios, and uses the screening value to determine a selected dispatching rule from the multiple dispatching rules.

2. The rapid screening method according to claim 1, characterized in that: The scheduling result is a Gantt chart.

3. The rapid screening method of claim 1, characterized in that: The scheduling result is obtained by the optimal approximate solution generator in a calculation convergence manner.

4. The rapid screening method of claim 1, wherein: The field context includes scheduling targets and available resources, and the available resources include work orders and machines; The process comprises at least a process step.

5. The rapid screening method of claim 1, characterized in that: In the work dispatch rule exploration table, the process field that complies with the work dispatch rule is represented by a binary code 1, and the process field that does not comply with the work dispatch rule is represented by a binary code 0.

6. The rapid screening method of claim 1, characterized in that: The participation ratio is obtained by summing up all processes that meet the dispatch rule in the dispatch rule column of the dispatch rule exploration table and dividing it by the total number of processes.

7. The rapid screening method of claim 1, characterized in that: The selection and dispatching rule selects the one with the higher screening value.

8. The rapid screening method of claim 1, characterized in that: It includes a user interface, through which the scheduling result and the corresponding situation are input, the scheduling target and available resources are selected, and the selection and dispatching rule is output.

9. The rapid screening method of claim 1, wherein: The method includes detecting the similarity between the selection and dispatching rule and the original dispatching rule of the corresponding situation.

10. The rapid screening method of claim 1, wherein: It includes detecting the similarity between the selection and dispatching rule and the scheduling result generated by the optimal approximate solution technology.

11. A device for rapid screening of work rules, characterized in that: include: The data unit of the processor obtains a plurality of scheduling results or corresponding scenarios, wherein the corresponding scenarios include field scenarios, processes and start and end times, and the scheduling results are obtained by the processor executing a computer optimization program to obtain an optimal approximate solution, and the scheduling results satisfy the shortest completion time; The processor has an exploration unit, which is coupled to the data unit, and establishes a dispatching rule exploration table based on the multiple scheduling results, wherein the dispatching rule exploration table is composed of multiple dispatching rules and multiple process steps, calculates the participation ratio of each dispatching rule in the dispatching rule exploration table compared to the multiple process steps, calculates the contribution ratio based on the summed average of the multiple participation ratios above and below the section line, obtains a screening value based on the sum and multiplication and division of the multiple contribution ratios, and uses the screening value to determine a selected dispatching rule from the multiple dispatching rules, and the dispatching rule exploration table reflects the participation status of the multiple dispatching rules for the multiple process steps respectively.

12. The rapid screening and dispatching rule device according to claim 11, characterized in that: The processing unit is coupled to the data unit and the exploration unit, obtains the scheduling result or the corresponding situation through a user interface, selects and uses the scheduling target and available resources, and outputs the selection and dispatching rule.

13. The rapid screening and dispatching rule device according to claim 11, characterized in that: The scheduling result is a Gantt chart.

14. The rapid screening and dispatching rule device according to claim 11, characterized in that: The scheduling result is obtained by the optimal approximate solution generator in a calculation convergence manner.

15. The rapid screening and dispatching rule device according to claim 11, characterized in that: The field context includes scheduling targets and available resources, and the available resources include work orders and machines; The process comprises at least a process step.

16. The rapid screening and dispatching rule device according to claim 11, characterized in that: In the work dispatch rule exploration table, the process field that complies with the work dispatch rule is represented by a binary code 1, and the process field that does not comply with the work dispatch rule is represented by a binary code 0.

17. The rapid screening and dispatching rule device according to claim 11, characterized in that: The participation ratio is obtained by summing up all processes that meet the dispatch rule in the dispatch rule column of the dispatch rule exploration table and dividing it by the total number of processes.

18. The rapid screening and dispatching rule device according to claim 11, characterized in that: The selection and dispatching rule selects the one with the higher screening value.

19. The rapid screening and dispatching rule device according to claim 11, characterized in that: A detection unit is included, which is coupled to the exploration unit and detects the similarity between the selected dispatching rule and the original dispatching rule of the corresponding situation.

20. The rapid screening and dispatching rule device according to claim 11, characterized in that: The method comprises a detection unit, which is coupled to the exploration unit and detects the similarity between the selection and dispatching rule and the scheduling result generated by the optimal approximate solution technology.

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