A single-line full-process scheduling algorithm for a silk-making workshop and a coding method thereof

Abstract

The application discloses a coding method for a single-line full-process production scheduling algorithm of a tobacco manufacturing workshop, and is characterized in that the method comprises the following steps: collecting the night rest time of the workshop, and representing the night rest time by a special symbol; and coding the workpiece processing sequence and workpiece interval by using real number coding, and adding the special symbol in the coding to separate the workpieces processed in different days. The application solves the problem that the night rest time cannot be identified in the existing single-line full-process production scheduling algorithm of the tobacco manufacturing workshop, avoids arranging the tobacco batches to the rest time range, and meanwhile, the coding can accurately reflect the production scheduling situation of the workshop and is also convenient for reverse decoding the coding into the production process.

Description

Technical Field

[0001] This invention relates to the tobacco industry, and more specifically to a coding method for a single-line full-process scheduling algorithm in a tobacco processing workshop. Background Technology

[0002] The single-line, full-process manufacturing method in a tobacco processing workshop can be viewed as a production line model with specific technological requirements. During the tobacco processing, according to the process specifications, a batch of tobacco shreds must be stored for a certain period of time after completing the previous processing step before proceeding to the next step. The storage time range varies between different tobacco brands and different processing steps. According to the process specifications, the process can be roughly divided into three stages: initial processing, secondary processing, and cutting and drying. Different groups of machines on the production line are responsible for the corresponding process stages. In particular, a certain brand may undergo a certain process repeatedly. When the production line needs to change the brand of tobacco being produced, the time required for brand change and machine cleaning must be considered.

[0003] The main constraints of single-line full-process production scheduling in the tobacco processing workshop are as follows: 1. Only one process can be performed on a batch at any given time; 2. Only one batch can be processed by a single processing machine at any given time, and multiple batches cannot be processed at the same time; 3. The storage time of a batch of tobacco between two processes should meet the storage time range specified by the process standard for that grade; 4. The same batch must be processed before the next process can begin after the previous process is completed; 5. The processing of tobacco cannot be interrupted; 6. The processing time of tobacco should meet the working hours of the tobacco factory.

[0004] In the production scheduling problem of a single-line, full-process tobacco processing workshop, constraints such as the delivery date of tobacco shreds, storage time between adjacent processes, and the fact that only one batch of tobacco shreds can be produced at a time in a certain process need to be considered. This problem is characterized by multiple objectives, uncertainty, and high complexity. The production scheduling optimization problem in this workshop is a typical NP-hard problem, where a reasonable solution cannot be found within a finite time. Metaheuristic optimization algorithms can be used to solve this problem. Metaheuristic algorithms can be divided into two categories. One category includes swarm search algorithms such as genetic algorithms and ant colony optimization, which, by simulating biological mechanisms in nature, can quickly perform a global search for optimization. Among them, genetic algorithms have been widely used since their inception due to their broad applicability to various problems. The other category includes algorithms such as simulated annealing and tabu search, which are suitable for neighborhood transformation search, enabling them to escape local optima and obtain the global optimum.

[0005] In order to use metaheuristic algorithms to solve the single-line full-process production scheduling problem in the silk-making workshop, the workshop production situation needs to be converted into a code that the algorithm can recognize. The code should be able to accurately reflect the workshop production scheduling situation and be able to be decoded back into the production process.

[0006] Due to the restrictions on working hours at the tobacco factory, and the inability to produce at night and on rest days, the existing real-number coding cannot skip the night and rest downtime. This can lead to situations where tobacco batches are assigned to the rest time range, which cannot intuitively reflect the batch processing situation on different workdays. Summary of the Invention

[0007] The purpose of this invention is to provide an encoding method for a single-line full-process scheduling algorithm in a tobacco processing workshop, addressing the aforementioned problems and resolving the issue of the inability to identify nighttime rest periods in existing single-line full-process scheduling algorithms, thereby preventing tobacco batches from being scheduled within the rest period range.

[0008] The technical solution of the present invention is as follows:

[0009] The present invention discloses an encoding method for a single-line full-process production scheduling algorithm in a silk-making workshop, comprising the following steps: obtaining the workshop's factory calendar, collecting the workshop's start and end times, rest days, and night rest times, with rest days and night rest times represented by special symbols; using real number encoding to encode the workpiece processing sequence and workpiece intervals, adding special symbols to the encoding to separate workpieces processed on different days.

[0010] Preferably, the special symbol is a day separator.

[0011] As a preferred method, the encoding method for workpiece processing sequence and workpiece interval is as follows: For a batch order with n workpieces, the encoding length of its scheduling problem is 2n+1. The first n positions are the first chromosome segment, representing the workpiece processing sequence; the last n+1 positions are the second chromosome segment, representing the time interval between the workpieces corresponding to the first chromosome segment, including the start time and the end time, which are represented by randomly generated real numbers.

[0012] As a preferred option, the following are specifically included:

[0013] S1: For n batches of tobacco that need to be scheduled within m days, determine the coding length of the first chromosome segment as n+m+1, set the value of the first position gene to n+m, and set the value of the last position gene to n+m+1. The first position gene and the last position gene are the first day separator and the last day separator, respectively.

[0014] S2: Randomly arrange the real genes in the range [1, m+n-1], where the real gene values ​​less than or equal to n represent tobacco batches, and the rest are day separators; the coding length of the second chromosome segment is n+m;

[0015] S3: Adjust the positions of each gene on the chromosome in steps one and two.

[0016] As a preferred method, during the adjustment, the production date of the tobacco is determined based on the relative position of the day separators, and the production volume of the day is determined by the total production time of the tobacco between two consecutive separators.

[0017] As a preferred option, the adjustment method specifically includes:

[0018] S10: Identify the position of each delimiter in the chromosome. The real genes with i≤n between the j-th and j+1-th delimiters represent the batch of tobacco produced on day j, where i is the i-th batch of tobacco. The working time T on day j is obtained by summing the production time of the tobacco batch produced on day j and the time for changing labels between two consecutive batches of tobacco. j Available time on day j minus working time T j The sum of these values ​​gives the free time MT on day j. j If MT j If the value is less than or equal to 0, meaning the available processing time is not met, then the last batch of cigarettes on day j is moved to day j+1, and code i is placed after the (j+1)th separator. This process is repeated to ensure that the daily working time meets the available time requirement.

[0019] S20: Adjust the production date of the tobacco shreds according to the delivery date k of each batch;

[0020] S30: Obtain daily machine idle time (MT) j The time interval between different tobacco production areas on the same day is randomly generated.

[0021] Preferably, step S20 specifically includes: identifying the position array K of m+1 day separators in the chromosome; comparing the position of the day separator with the position of the last process of tobacco shred numbered i; and determining the shredding time of tobacco shred i. If the production time is after the delivery date k, then adjusting tobacco shred i to K. k Previously, we guaranteed that production would be completed before the delivery date.

[0022] Preferably, S30 specifically includes: if the j-th and j+1-th day separators are located in chromosome M respectively j and M j+1 The position of the Mth chromosome in the latter half of the chromosome. j To the Mth j+1 The position represents the empty space between tobacco leaves on day j, and the idle time MT j The value is assigned to a space; or MT is... j The value is all assigned to the Mth element. j+1 With one position, continuous production can be achieved without gaps between batches of tobacco. This method can meet the requirements of continuous production or rest and maintenance between batches.

[0023] This invention discloses a coding method for single-line full-process production scheduling in a yarn processing workshop. The coding method of the single-line full-process production scheduling algorithm in the yarn processing workshop is randomly generated three times to obtain the production batch order of the first processing, second processing, and cutting and drying stages, i.e., the production scheduling plan. The second processing production plan is adjusted not only according to the production time within a day, but also according to the number of days of the first processing of each batch and the storage time range between the first and second processing, and the processing time of the second processing is adjusted. The initial production scheduling plan for cutting and drying is also generated based on the second processing. The adjacent processes are adjusted according to the sequential relationship of the processes and the storage time range between the processes.

[0024] This invention discloses a single-line full-process production scheduling algorithm for tobacco processing workshops. Its features include: acquiring factory calendar data, the required batches and delivery dates of tobacco shreds for each brand within the scheduling time range, and process-related data for each brand; using the coding method of a single-line full-process production scheduling algorithm for tobacco processing workshops for initial coding; performing selection, crossover, and mutation in each generation; obtaining a production scheduling scheme after several generations of inheritance; and outputting the specific start and end times of each process for each batch of tobacco shreds.

[0025] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0026] 1. This invention uses a special symbol, namely the day separator, to separate workpieces processed on different days, thereby accurately arranging the workpieces for processing on different working days and avoiding the situation where tobacco batches are arranged within the rest time range.

[0027] 2. The special symbols of this invention require a certain duration, occupying a certain amount of time within a day, which is equal to the nighttime rest time in the workshop, reflecting the nighttime rest time.

[0028] 3. The encoding of this invention reflects the batch sequence and the rest time between adjacent batches, and further, the start time and end time of each batch, as well as the production sequence of a certain batch in different processes can be obtained; by subtracting the end time of the previous stage from the start time of the next process of a certain batch, the storage time of that batch between two adjacent processes can be obtained.

[0029] The start time of the workpiece at the first position of the first chromosome segment corresponds to the EM at the first position of the second chromosome segment. [1] The value is represented as ts [1] The completion time of this workpiece is te. [1] =ts [1] +t [1] The start and end times of the workpiece at the next position can be determined by the end time of the workpiece at the previous position and the interval EM between the two workpieces. [i] We obtain that the start time of workpiece [i] is ts.[i] =te [i-1] +EM [i] Its end time te [i] =ts [i] +t [i] , where [·] represents the workpiece number at the ·th position.

[0030] 4. The encoding of this invention can accurately reflect the production scheduling in the workshop, making it easy to decode the encoding into the production process later. Attached Figure Description

[0031] The present invention will be described by way of example and with reference to the accompanying drawings, wherein:

[0032] Figure 1 This is a schematic diagram of the two-stage encoding method in the embodiment.

[0033] Figure 2 This is a schematic diagram of the encoding method that uses day separators to constrain idle time in the embodiment.

[0034] Figure 3 This is a graph showing the decreasing trend of the penalty function value of the group search module in the embodiment.

[0035] Figure 4 This is a graph showing the downward trend of domain search in the embodiment.

[0036] Figure 5 This is a Gantt chart of the production scheduling results in the example. Detailed Implementation

[0037] All features disclosed in this specification, or all steps in all disclosed methods or processes, may be combined in any way, except for mutually exclusive features and / or steps.

[0038] Any feature disclosed in this specification (including any appended claims and abstract) may be replaced by other equivalent or similar features, unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is merely one example of a series of equivalent or similar features.

[0039] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0040] This invention discloses an encoding method for a single-line full-process scheduling algorithm in a silk-making workshop, comprising the following steps: obtaining the workshop's factory calendar, collecting the workshop's start and end times, rest days, and night rest times, with rest days and night rest times represented by special symbols; encoding the workpiece processing sequence and workpiece intervals using real number encoding, and adding special symbols to the encoding to separate workpieces processed on different days. In an embodiment, the special symbol used is a day separator, which is a separating symbol used to separate workpieces processed on different days.

[0041] In this embodiment, considering the characteristics of the single-line full-process scheduling in the yarn-making workshop, a two-stage coding method is adopted for the coding of a certain process within a certain time range. The workpiece processing sequence and workpiece interval are encoded separately, and the specific processing time period for each workpiece can be quickly calculated through decoding. The specific method is as follows: Figure 1 As shown.

[0042] Suppose there are n jobs in a batch of orders, and the coding length of its scheduling problem is 2n+1. The first n positions form the first chromosome, representing the processing order of the jobs. Here, real numbers are used for coding, rather than the general setting where the first n real numbers represent the jobs in the order and the last m real numbers represent the jobs to be maintained. The initial chromosome's order of these jobs is randomly generated. The last m+1 positions form the second chromosome, representing the time interval (including the start and end times) between the jobs corresponding to the first chromosome, and are represented by randomly generated real numbers in the range [0, EM].

[0043] Furthermore, there are a total of n+1 intervals from the start time to the end time for n workpieces, and the k-th processing interval is denoted as EM. k The sum of all interval durations should equal the delivery date d. max Subtract the processing time of all workpieces, which is the total interval time EM, i.e.

[0044]

[0045] like Figure 1 As shown, in the embodiment, the first 10 positions (Chromosome part 1) represent the processing sequence of 10 workpieces, which is 4→5→3→6→9→10→1→8→7→2; the last 11 positions (Chromosome part 2) represent the intervals between the 10 workpieces. The interval between workpiece 4 and the start time is 1, and the interval between workpiece 4 and workpiece 5 is 0. The sum of the interval times in Chromosome part 2 must satisfy the formula for total interval time EM.

[0046] By randomly generating this code three times, the production batches for the first, second, and cutting / drying stages can be ordered, forming a chromosome. The code reflects the batch sequence and the rest time between adjacent batches. Further, the start and end times of each batch, as well as the production sequence of a batch in different processes, can be obtained. Subtracting the end time of the previous stage from the start time of the next process for a batch yields the storage time of that batch between two adjacent processes.

[0047] The start time of the workpiece at the first position of the first chromosome segment corresponds to the EM at the first position of the second chromosome segment. [1] The value is represented as ts [1] The completion time of this workpiece is te. [1] =ts [1] +t [1] The start and end times of the workpiece at the next position can be determined by the end time of the workpiece at the previous position and the interval EM between the two workpieces. [i] We obtain that the start time of workpiece [i] is ts. [i] =te [i-1] +EM [i] Its end time te [i] =ts [i] +t [i] , where [·] represents the workpiece number at the ·th position.

[0048] In this embodiment, a day separator is used to constrain idle time:

[0049] Due to the factory's get off work schedule restrictions, production is prohibited at night and on rest days. Simple numerical coding cannot bypass downtime or clearly reflect batch processing within different workdays. Therefore, a day separator symbol is added to the coding. This method uses a special symbol to separate workpieces processed on different days. This separator symbol also occupies a certain processing time, equivalent to the factory's nighttime rest period. In other words, the nighttime rest period is approximated as a special batch, and only this specific workpiece can be processed during the factory's off-hours, preventing the scheduling of tobacco batches within the rest period. In short, using a separator not only accurately schedules workpieces for processing on different workdays but also carries a physical meaning, reflecting the nighttime rest period. Details are as follows: Figure 2 As shown.

[0050] The production of tobacco shreds in the tobacco processing workshop is mainly divided into three processes: primary processing, secondary processing, and cutting and drying. Figure 2During the first working day, within the machine's available range (i.e., working hours), batches numbered 1, 2, and 3 will undergo one processing step, and batches numbered 1 and 2 will undergo two processing steps. There will be no cutting or drying work scheduled. On the second working day, within the machine's available range, batches numbered 4 and 5 will undergo one processing step, and batches numbered 3, 4, and 5 will undergo two processing steps. There will be no cutting or drying work scheduled. On the third working day, within the machine's available range, there will be no one-step processing step or two-step processing step. Batches numbered 1 and 2 will undergo cutting and drying. On the fourth working day, within the machine's available range, there will be no one-step processing step or two-step processing step. Batches numbered 3, 4, and 5 will undergo cutting and drying.

[0051] To facilitate crossover in later stages, if production needs to be scheduled for n batches within m days, the first code segment becomes n+m+1 in length. The first position of the code is the first day separator with a value of n+m, and the last position is the last day separator with a value of n+m+1. The remaining values ​​are randomly arranged, with values ​​less than or equal to n representing tobacco batches, and the rest representing day separators. The second code segment also becomes n+m in length. It's important to note that the time interval within the same day should be calculated based on the workpieces' distribution within that day.

[0052] To meet the process time requirements, storage time requirements, and production continuity and logic of tobacco production, the processing time of the next process should be after the previous process is completed, and the time interval between adjacent processes should meet the storage time requirements of the tobacco. Therefore, the initial feeding time of the tobacco affects the specific time range of each subsequent processing step. To reduce the error of the initial chromosome, the position of each gene on the initial chromosome will be adjusted by studying the process standards of the tobacco factory. For example: 1. If it is found that the subsequent process is processed before the preceding process, the position of the subsequent process will be postponed to after the preceding process; 2. If it is known from the analysis of process standards and actual production data that there should be an interval of [48-72] hours between two processes, that is, the subsequent process is processed on the third to fourth day after the completion of the preceding process, and if the randomly generated subsequent process is not within this range, the position of the process will be adjusted; 3. It should be ensured that all production processes of a certain brand of tobacco are carried out before the delivery date. If the processing time of a certain process exceeds the delivery date, the position of the process also needs to be adjusted.

[0053] In the embodiment, the specific encoding implementation process is as follows:

[0054] Suppose there are n batches of tobacco that need to be produced within m days. Each batch of tobacco has its own brand j, corresponding to a specific production process, including the processing time at each stage and the storage time between two batches. Each batch of tobacco also has its own delivery date d. iDuring encoding, the encoding length is first determined to be n+m+1. The value of the first position gene is set to n+m, and the value of the last position gene is set to n+m+1, serving as the start and end day separators. These two position values ​​remain unchanged in subsequent calculations. Then, the real-valued genes in the range [1, m+n-1] are randomly arranged to obtain a production scheduling scheme, which is then further adjusted.

[0055] During adjustment, the relative position of the tobacco shreds is used to determine which day the tobacco shreds were produced, and the total production time of the tobacco shreds between two consecutive separators is used to determine whether the production volume of the day exceeds the production capacity of the production line.

[0056] First, identify the locations of gene points where i>n, which are the positions of each separator on the chromosome. The real genes with i≤n between the j-th and j+1-th separators represent the tobacco batch produced on day j. Summing the production time and repackaging time of the tobacco batches produced on day j yields the working time T for day j. j The sum of available time and working time on day j is JT. j Get the free time MT on day j j If MT j If the value is ≤0, it means that too much tobacco has been prepared and the available processing time is not met. In this case, the last batch of tobacco on day j is moved to j+1 and placed after the j+1 separator. This process is repeated to ensure that the daily working time meets the available time requirements.

[0057] Next, the production date of the tobacco is adjusted based on the delivery date k of each batch. The positions of m+1 separators in the chromosome are identified in array K. The position of the day separator is compared sequentially with the tobacco shredded tobacco numbered i to determine the production date of shredded tobacco i. If the production date is after the delivery date k, then shredded tobacco i is adjusted to K. k Previously, we guaranteed that production would be completed before the delivery date.

[0058] The daily machine idle time MT was obtained j Randomly generate the interval time between different tobacco production processes on the same day. The specific method is as follows: if the j-th and j+1-th separators are located in chromosome M respectively... j and M j+1 The position of the Mth chromosome in the latter half of the chromosome. j To the Mth j+1 -1 positions represent the empty spaces between tobacco leaves on day j, and the idle time MT j The values ​​are assigned to these vacant positions, accurately reflecting the specific time schedule expressed by that chromosome. To achieve compact, continuous production, the MT... j The value is all assigned to the Mth element. j+1-1 position, to achieve continuous production without leaving gaps between batches of tobacco.

[0059] In this embodiment, when scheduling tobacco production, the factory calendar data is first obtained to determine the workshop working hours and rest periods within the scheduling timeframe. This includes information such as whether there is a single day off, which days are off within the scheduling timeframe, and the start and end times of each workday. After processing the working hours, the number of day separators needed within the scheduling timeframe and the duration of each separator are determined. If a day is a rest day, its duration is incorporated into the next day's nighttime rest interval to avoid scheduling production on rest days. Then, the tobacco demand is obtained from the MES system, specifically the required batches and delivery dates for each brand of tobacco within the scheduling timeframe. The algorithm retrieves process-related data for each brand from the database, such as the number of processes required, the processing time for each process, and the storage time after each process.

[0060] When generating the initial code, the production schedule for the first process step is first set. The first and last positions of the first code segment are set as day separators. The real number batch codes and the remaining day separators are randomly sorted to obtain the daily tobacco arrangement and sequence. The total processing time for the day is calculated based on the tobacco production situation. If the total time exceeds the available time range for that day, the production batch for that day is adjusted.

[0061] After the adjustments are completed, the scheduling method for the second processing step (processing step 2) is randomly generated using the same method. In addition to adjusting the daily production time, the scheduling for processing step 2 also needs to be adjusted based on the number of days the first processing step (processing step 1) falls on and the storage time range between processing step 1 and processing step 2. Specifically, if the randomly generated processing step 2 occurs before processing step 1, it needs to be moved to the same day as processing step 1 or later. Then, based on the storage time range between processing step 1 and processing step 2, the number of days the processing step 2 falls on is adjusted to a reasonable range. The initial scheduling plan for cutting and drying shreds is also generated based on processing step 2. Adjustments are made between adjacent processes based on their sequential relationship and the storage time range between processes.

[0062] This invention also discloses a single-line full-process production scheduling algorithm for a tobacco processing workshop: After obtaining the initial code, a reasonable production scheduling scheme is obtained through the selection, crossover, and mutation processes of each generation of the algorithm after several generations of inheritance. The algorithm outputs the specific start and end times of each process for each batch of tobacco. The day separator indicates which day each process is produced on, and the storage time between processes is obtained based on the processing time of adjacent processes. It is important to note that the coding structure must not change during each generation's crossover and mutation processes to avoid scheduling errors. The algorithm ensures that the production time of the tobacco is within the workshop's working hours, that the storage time between processes for each batch of tobacco meets the process specifications, and that each batch of tobacco is completed before the delivery date to meet subsequent cigarette production needs. The algorithm output can be used to draw a Gantt chart of workshop production and a detailed production timetable.

[0063] The encoding method of this invention is applicable to the encoding of all heuristic algorithms used in the production scheduling problem of a single line in a silk-making workshop, such as genetic algorithms, ant colony algorithms, simulated annealing, tabu search, etc.

[0064] To verify the algorithm's performance, actual production data from the tobacco factory's database was used to schedule production based on this data, and the algorithm's performance was studied. The production demand requests for some brands from the actual production line between May 9th and May 20th, 2022 are summarized in the table below:

[0065]

[0066] Input the production grade, batch number, and scheduling time range into the algorithm. The algorithm will retrieve the corresponding production process data and the factory calendar in the system, obtain the initial code according to the encoding method, and begin calculation through the algorithm flow. In the objective function value, PT is the penalty value for working time not meeting the start time, Q is the penalty value for storage time not meeting the process requirements, PD is the penalty value for delivery time not meeting the requirements, and P is the sum of all penalties, i.e., P = PT + Q + PD. The minimum time unit of the algorithm is 10 minutes, meaning that every increase of 1 in the penalty function value represents 10 minutes of scheduling results not meeting the requirements.

[0067] Figure 3 The penalty function value of the group search module shows a decreasing trend, from Figure 3 As can be seen, the group search module showed a significant downward trend in the early stages, with the P-value decreasing from nearly 1400 to 153, demonstrating the rapid search capability of the group search. However, the downward trend gradually slowed down in the latter half of the group search module, indicating that the group search had entered a local optimum. The entire genetic process took 187 seconds.

[0068] like Figure 4As shown, after the group search, the result is used as input for the neighborhood search, and a single-point transformation search is performed. The neighborhood search further reduces the penalty function value from 153 to 4. The entire process takes only 20 seconds. In the figure, sp1 and sp represent the reduction of the two neighborhood search schemes. First, the sp1 method is used for the neighborhood search, and then the sp method is used to continue the search based on sp1. This demonstrates the efficiency and effectiveness of the neighborhood search. Finally, the production scheduling result is converted into a Gantt chart as shown in Figure 5. The horizontal axis represents the production scheduling time axis, and the vertical axis represents the process segment. 1 represents the first-stage processing segment, 2 represents the second-stage processing segment, and 3 represents the cutting and drying segment. White blocks in the production scheduling represent high-grade tobacco, and gray blocks represent other tobacco. The numbers in the gray blocks represent the tobacco number, and the long squares represent rest time. The numbers in the long squares represent the weekdays. It can be seen that the unavailable time on Monday of the second week is very long, which is the result of incorporating the weekend rest time.

[0069] The embodiments described above merely illustrate specific implementation methods of this application, and while the descriptions are detailed and specific, they should not be construed as limiting the scope of protection of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the technical solution of this application, and these modifications and improvements all fall within the scope of protection of this application.

Claims

1. A coding method for a single-line full-process scheduling algorithm in a silk-making workshop, characterized in that, Includes the following steps: Obtain the workshop and factory calendar, collect the workshop's start and end times, rest days and night rest times, and use special symbols to represent rest days and night rest times; use real number coding to encode the processing sequence and interval of tobacco batches, and add special symbols to the coding to separate tobacco batches processed on different days; The special symbol used is the sky separator; The encoding methods specifically include: S1: For those who need to Production scheduled within one day Using a batch of tobacco shreds, the coding length of the first chromosome segment was determined to be... The value of the first position gene encoded is set to The value of the last position gene is set to The first and last positional genes encoded are the first and last day separators, respectively; the first chromosome segment indicates the batch processing order of the tobacco shreds. S2: Will The real-valued genes within the range are randomly arranged, wherein the value of the real-valued genes is less than or equal to This refers to the tobacco batch; the rest are separated by days. The coding length of the second chromosome segment is... The second chromosome segment represents the time interval between batches of tobacco corresponding to the first chromosome segment, including the start and end times, and is represented by randomly generated real numbers. S3: Adjust the positions of each gene on the chromosome in steps one and two; The adjustment methods specifically include: S10: Identify the location of each delimiter within the chromosome, the... Individual and Between separators The real number of genes is this first one. The batches of tobacco produced by Tianzhong For the first Piece of tobacco; the first The sum of the batch production time and the brand change time between two consecutive batches of tobacco produced by Tianzhong yielded the [number]. Working hours per day , No. Available time per day minus working hours The sum of the first and second halves of the first half ... second half of the third half of the second half of the Free time of day ;like If the value is less than or equal to 0, meaning the available processing time is not met, then the first... The last batch of cigarettes of the day went to the... Adjustments will be made to the encoding. Placed in the first After each separator, repeat the check sequentially to ensure that the daily working hours meet the available time requirements; S20: Delivery time for each batch of tobacco Adjust the production date of the tobacco; S30: Obtain daily machine idle time The time interval between different tobacco production lines on the same day is randomly generated.

2. The coding method for the single-line full-process scheduling algorithm in a silk-making workshop according to claim 1, characterized in that, During the adjustment, the production date of the tobacco is determined based on the relative position of the day separators, and the production volume of the day is determined by the total production time of the tobacco between two consecutive separators.

3. The coding method for the single-line full-process scheduling algorithm in a silk-making workshop according to claim 1, characterized in that, include: S20 specifically includes: identifying The array of positions of the day separator in the chromosome The position of the sky separator is related to the number. The positions of the tobacco shreds in the last process are compared sequentially to determine... The time it takes for tobacco shreds to form into shreds; if the production time is within the delivery period... After that, Adjust the tobacco to Previously, we guaranteed that production would be completed before the delivery date.

4. The coding method for the single-line full-process scheduling algorithm in a silk-making workshop according to claim 1, characterized in that, S30 specifically includes: if the first Individual and Each of the day separators is located in the chromosome. and The position of the chromosome, then the second half of the chromosome... To the The position represents the empty space between tobacco leaves on day j, indicating the free time. The value is assigned to a space; or the value is assigned to a space. The value is all assigned to the first This allows for continuous production without gaps between batches of tobacco.

5. A coding method for single-line full-process production scheduling in a silk-making workshop, characterized in that, The coding method of the single-line full-process scheduling algorithm of the filament processing workshop as described in any one of claims 1-4 is randomly generated three times to obtain the production batch sorting of the first processing, second processing, and filament cutting and drying stages, i.e., the scheduling plan; the scheduling plan of the second processing stage is adjusted according to the production time within a day, and the processing time of the second processing stage is also adjusted according to the number of days of the first processing stage of each batch and the storage time range between the first and second processing stages; the initial scheduling plan of the filament cutting and drying stage is also generated on the basis of the second processing stage; the adjacent processes are adjusted according to the sequential relationship of the processes and the storage time range between the processes.

6. A method for scheduling production across the entire process of a single-line silk-making workshop, characterized in that, Obtain factory calendar data, the required batches and delivery dates of each brand of tobacco within the production scheduling time range, and process-related data for each brand. Use the coding method of the single-line full-process scheduling algorithm for the tobacco processing workshop as described in any one of claims 1-4 for initial coding. Perform selection, crossover, and mutation for each generation, and obtain the scheduling scheme after several generations of inheritance. Output the specific start and end times of each process for each batch of tobacco.

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