Chemical material production scheduling optimization method and device

Abstract

A chemical material production scheduling optimization method and device, the method comprises: establishing a target function with profit maximization as the goal, setting constraint conditions, establishing an optimization model of chemical material production scheduling, the constraint conditions include initial constraints, task allocation constraints, time constraints, material constraints, switching time window constraints and raw material inventory constraints; wherein, the switching time window constraint includes that the shutdown time of two similar devices does not overlap and the switching time of the set production event needs to be in working hours; the raw material inventory constraint includes: obtaining the production time of each production event per day within the optimization time, determining the corresponding raw material daily inventory based on the initial production rate of the production event, and setting it within the upper and lower limit range of the daily inventory value; solving the current optimization model, updating the optimization model using the production rate obtained by solving; return to execute the solving of the current optimization model until the iteration end condition is met, and the final optimization result is obtained.

Description

Technical Field

[0001] This article relates to the field of oil and gas field development technology, and in particular to a method and device for optimizing the production scheduling of chemical materials. Background Technology

[0002] The production of chemical materials is characterized by a variety of grade requirements, complex grade switching rules, and difficulty in balancing raw materials. Specifically: (1) Market demand is diversified, and a single unit may need to produce several to dozens of grades within a month; (2) Each grade needs to be produced in sequence, and the grade switching rules are complex, involving factors such as the feasibility of switching, the amount and duration of transition materials generated during switching, whether or not to stop work and the duration of the stop work, and the time window requirements for grade switching (such as some grade switching can only occur during the day shift on weekdays, and the shutdown operations of two adjacent units cannot occur simultaneously); (3) Raw materials such as ethylene, propylene, and butadiene are usually processed and used by multiple units. The consumption rates of raw materials in different units and for different grades are different, which leads to frequent fluctuations in raw material inventory. It is necessary to limit the daily end-of-day inventory of raw materials as an important factor in formulating scheduling and production plans to avoid raw material shortages or overflowing.

[0003] Therefore, how to formulate a production and switching plan for chemical materials that is timely in response to market demands, feasible, and maximizes the value of chemical raw material resources has become a prominent challenge for chemical companies. Summary of the Invention

[0004] This application provides a method and apparatus for optimizing the production scheduling of chemical materials. The application uses profit maximization as the objective function, establishes a mixed integer linear programming model based on basic constraints, and adds switching time window constraints and raw material inventory constraints to obtain the optimal chemical material production scheduling scheme.

[0005] Firstly, this application provides a method for optimizing the production scheduling of chemical materials, the method comprising:

[0006] An objective function is established with profit maximization as the goal, and constraints are set to build an optimization model for chemical material production scheduling. The constraints include initial constraints, task allocation constraints, time constraints, material constraints, switching time window constraints, and raw material inventory constraints. Among them, the switching time window constraints include no overlap in the downtime of two adjacent units and the setting that the switching time of the production event is during working hours.

[0007] The raw material inventory constraints include: obtaining the daily production duration of each production event within the time to be optimized, determining the corresponding daily raw material inventory based on the initial production rate of the production event, and setting it within the upper and lower limits of the daily inventory value;

[0008] Solve the current optimization model, and update the optimization model using the production rate obtained from the solution;

[0009] Return to the solution of the current optimization model until the iteration termination condition is met, and obtain the final optimization result.

[0010] Secondly, embodiments of the present invention also provide a chemical material production scheduling optimization device, the device comprising: a memory and a processor; the memory is used to store a program for optimizing the chemical material production scheduling, and the processor is used to read and execute the program for optimizing the chemical material production scheduling, and execute the method described in any one of the above embodiments.

[0011] Thirdly, embodiments of the present invention also provide a computer-readable storage medium storing a data processing program, wherein the data processing program is executed by a processor using the chemical material production scheduling optimization method described in any one of the above embodiments.

[0012] Compared with related technologies, this application provides a method and apparatus for optimizing the production scheduling of chemical materials. The method includes: establishing an objective function with profit maximization as the goal, setting constraints, and establishing an optimization model for the production scheduling of chemical materials. The constraints include initial constraints, task allocation constraints, time constraints, material constraints, switching time window constraints, and raw material inventory constraints. The switching time window constraints include ensuring that the downtime of two adjacent units does not overlap and that the switching time of a production event must fall within working hours. The raw material inventory constraints include: obtaining the daily production duration of each production event within the time to be optimized, determining the corresponding daily raw material inventory based on the initial production rate of the production event, and setting it within the upper and lower limits of the daily inventory value; solving the current optimization model, updating the optimization model using the solved production rate; and returning to execute the solution of the current optimization model until the iteration termination condition is met, obtaining the final optimization result. This application establishes a mixed-integer linear programming model with profit maximization as the objective function and basic constraints as constraints, while adding switching time window constraints and raw material inventory constraints, ultimately obtaining the optimal production scheduling scheme.

[0013] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application can be realized and obtained by means of the solutions described in the description and the accompanying drawings. Attached Figure Description

[0014] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0015] Figure 1 This is a flowchart of the chemical material production scheduling optimization method according to an embodiment of this application;

[0016] Figure 2 This is a schematic diagram of a chemical material production scheduling optimization device according to an embodiment of this application;

[0017] Figure 3 This is a schematic diagram showing the switching time relationship between different devices in the embodiments of this application;

[0018] Figure 4 This is a schematic diagram illustrating the working time switching restrictions in the embodiments of this application;

[0019] Figure 5 This is a schematic diagram illustrating the overlap between the production interval and the daily interval in an embodiment of this application;

[0020] Figure 6 This is a schematic diagram of the raw material inventory change curve in the embodiments of this application. Detailed Implementation

[0021] This application describes several embodiments, but these descriptions are exemplary and not restrictive, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0022] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive scheme as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive schemes to form another unique inventive scheme as defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in this application may be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.

[0023] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0024] Related technical terms:

[0025] Chemical raw materials can be basic chemicals or monomers that participate in chemical reactions and are consumed to generate target products. Chemical raw materials are the inputs and material basis of the production process. During the production of chemical materials, the inventory of chemical raw materials fluctuates dynamically. They are put into storage, consumed in the equipment, and may be supplied externally; therefore, their inventory levels are constantly changing. Specifically, chemical raw materials can include liquid or gaseous basic chemical monomers such as ethylene, propylene, butadiene, and styrene.

[0026] Chemical materials can be final solid or liquid polymer products transformed from chemical raw materials through processes such as chemical synthesis and polymerization. Specific polymer products can include polyethylene, polypropylene, polystyrene, styrene-butadiene rubber, and cis-butadiene rubber.

[0027] A chemical materials production plant is a general term for large-scale, continuous process production equipment and systems that convert chemical raw materials into chemical materials, including reactors, towers, heat exchangers, and conveying systems. A single chemical materials production plant can produce multiple grades of chemical materials, but its production capacity (such as maximum / minimum feed rate) has a physical upper limit. Chemical raw materials are fed into the chemical materials production plant and processed according to specific grade formulas and processes to produce chemical materials of corresponding specifications.

[0028] The inventor discovered through analysis that:

[0029] Mathematical programming is currently the preferred solution for solving scheduling optimization problems. Although many studies indicate that mathematical programming is an NP-hard problem, with complexity increasing exponentially with problem size, it offers high stability and provides globally optimal solutions compared to other methods, which is crucial for practical factory production. Existing chemical material scheduling optimization methods are mostly based on discrete-time modeling, requiring production events to start and stop at discrete nodes. Using this method, to obtain scheduling plans accurate to the hour for long periods (e.g., monthly, quarterly), time slices need to be divided into hours, resulting in a huge model size that is difficult to solve within a limited time. Furthermore, many studies typically set production rates to fixed values, significantly reducing the scheduling optimization space. In practical production scenarios, variable rates allow for flexible control of product output. Additionally, current research generally does not consider raw material inventory limits, a significant bottleneck for many chemical companies in developing scheduling plans. Achieving daily raw material balance and inventory limits is a critical requirement, and these details often greatly influence the effectiveness of scheduling schemes.

[0030] To achieve multi-factor fusion in optimizing the scheduling of chemical materials, this invention decomposes the problem into three levels:

[0031] The goal of the first level is to address basic needs, which involves optimizing the number of production events, the production sequence, and the production duration.

[0032] The second aspect is addressing the switching time window requirements, such as considering the utilization of human resources, ensuring that the shutdown of two adjacent units does not occur simultaneously, and that some switching needs to be carried out during the day shift on weekdays, etc.

[0033] The final aspect is addressing the issues of variable rates and the high and low limits of raw material inventory.

[0034] Based on the above analysis, the inventors have developed a method for optimizing the production scheduling of chemical materials under multiple constraints.

[0035] This invention provides a method for optimizing the production scheduling of chemical materials, such as... Figure 1 As shown, the method includes steps S1-S3:

[0036] S1: Establish an objective function with the goal of maximizing profits, set constraints, and establish an optimization model for the production scheduling of chemical materials;

[0037] S2: Solve the current optimization model and update the optimization model using the production rate obtained from the solution;

[0038] S3: Return to the current optimization model and continue solving until the iteration termination condition is met to obtain the final optimization result.

[0039] In this embodiment, the relevant parameters are explained as follows:

[0040] 1. Scalar

[0041] name describe value Scheduling cycle length Total scheduling cycle duration, in hours Shortest production time for genuine products within the scheduling cycle The unit is hours. Maximum number Set a value according to the situation, for example: 10000 During work hours The unit is hours. Off-get off work time The unit is hours. Hourly supply of raw materials Determined based on the company's situation.

[0042] 2. Set

[0043] name describe Device Production events One genuine product Subsequent transition material Pre-transition material Maintenance incident Work stoppage Days raw material max is the upper limit, and min is the lower limit. start means beginning, end means end. Workdays that can be switched Correspondence between equipment and production events Production events .msc can be switched to .mmsc

[0044] 3. Parameters

[0045] name describe The beginning and end of each day The start of each day The end of each day Upper and lower limits of production event MSC execution time The maximum execution time of a genuine MP1 player The lower limit of the execution time of genuine MP1 Upper limit of the execution time of the subsequent transition material mp4b Lower limit of the execution time of the subsequent transition material mp4b Upper limit of the execution time of the preceding transition material mp4a Lower limit of the execution time of the preceding transition material mp4a Maximum duration of shutdown events The lower limit of the duration of work stoppage events Production event (transitional material) output Precursor feedstock mp4a production Subsequent transition material mp4b output Production event formula Production rate upper and lower limits of production events on device u Minimum production rate of genuine MP1 on device u Maximum production rate of genuine MP1 on device u Guessed value (initial value) of the rate Upper and lower limits of demand for genuine products The lower limit of demand for genuine MP1 players The upper limit of demand for genuine MP1 players Raw material inventory upper and lower limits

[0046] 4. Binary variables

[0047] name describe Is the production event msc on device u the first to produce? 1 if yes, 0 if no. Is the mp1 event on device u the first one produced? 1 indicates yes, 0 indicates no. Is the production event MSC on device u the last one produced? 1 if yes, 0 if no. Is the genuine product event mp1 on device u the last one produced? 1 indicates yes, 0 indicates no. On device u, the production event msc indicates whether production is in progress; 1 indicates production, and 0 indicates no production. Whether device u is under maintenance: 1 indicates maintenance, 0 indicates no maintenance. On device u, is the genuine product event mp1 in production? 1 indicates production, 0 indicates non-production. Whether the subsequent transition material mp4a on device u is produced is 1 if produced and 0 if not. Whether the preceding transition material mp4b on device u is being produced: 1 indicates production, 0 indicates no production. Whether a switch from production event MSC to production event MMSC has occurred on device u, 1 indicates yes, 0 indicates no. Whether a switch from the preceding transition material mp4b to the production event msc has occurred on device u, 1 indicates yes, 0 indicates no. Whether a production event MSC has occurred on device u, indicating a switch to the subsequent transition material MP4A, is 1 if yes and 0 if no. Whether a switch from the preceding transition material mp4b to the shutdown event ms has occurred on device u, 1 indicates yes, 0 indicates no. Whether a switch from the preceding transition material mp4b to the maintenance event mc has occurred on device u, 1 indicates yes, 0 indicates no. Whether a maintenance event has occurred on device u, and whether the switching from the maintenance event mc to the subsequent transition material mp4a, is 1 if yes and 0 if no. Whether a shutdown event has occurred on device u and the switching of the subsequent transition material mp4a is indicated by a value of 1 if yes and 0 if no. Whether a switch from the preceding transition material mp4b to the production event msc has occurred on device u, 1 indicates yes, 0 indicates no. The production event msc on device u stopped on day d (auxiliary variable) The genuine MP1 on device u stops on day d (auxiliary variable) The production event msc on device u is executed on day d (auxiliary variable). The production event msc on device u begins on day d (auxiliary variable). The production event msc on device u ends on day d (auxiliary variable) u and uu represent two devices, ms represents a shutdown event occurring on device u, and mms represents a shutdown event occurring on device uu (auxiliary variable).

[0048] 5. Continuous variables

[0049] name describe Production duration of production events on device u (MSC) Production duration of the first production event on device u Production time of genuine MP1 on device u Production time of subsequent transition material mp4a on device u Production time of the preceding transition material mp4b on device u Production duration of shutdown events on device u (ms) Production time of maintenance events on device u Start and end times of MSC production on device u Production end time of MSC on device u Production start time of MSC on device u The end time of the shutdown event ms on device u End time of mms on device uu Start time of MMS on device UU Start time of the MMSC production event on device u End time of genuine MP1 on device u Production of mp1 on device u Production of MP4A on device u Production of MP4B on device u Production of genuine MP1 players on all devices MP4A output on all devices MP4B output on all devices Production of MSC on device u The supply of raw material mr on day d Execution duration of MSC on device u on day d Production volume of MSC on device u on day d The consumption of MR on device u on day d mr's consumption on day d The actual production rate obtained after solving the problem. Auxiliary variables Auxiliary variables

[0050] In one exemplary embodiment, the constraints include initial constraints, task allocation constraints, time constraints, material constraints, switching time window constraints, and raw material inventory constraints.

[0051] The switching time window constraint includes that the downtime of two adjacent devices does not overlap and that the switching time of the set production event must be during working hours.

[0052] The raw material inventory constraints include obtaining the daily production duration of each production event within the time to be optimized, determining the corresponding daily raw material inventory based on the initial production rate of the production event, and limiting it within a set upper and lower limit range.

[0053] In one exemplary embodiment, production operations that can occur on the device are defined as production events, which include five types: positive product, preceding transition material, subsequent transition material, shutdown, and maintenance.

[0054] Whether each production event occurs on the unit is determined by a binary variable. The decision-making process, the execution order of production events, is determined by a binary variable. The decision-making process involves determining the production duration of each production event using continuous variables. decision making.

[0055] The correspondence between devices and production events in the set As defined in [the text], the feasibility of switching production events is determined by a set of [the relevant data]. Definition; that is, the optimization model for chemical material production scheduling. In the optimization process, each unit can only produce the corresponding product, and the current production event can only be based on the set of switching feasibility. Once the switch to the appropriate production event is confirmed, the final raw material consumption will be determined from the formula parameter table. Decide.

[0056] In one exemplary embodiment, step S1 involves setting initial constraints, including:

[0057] 1. Set the initial production event for the device;

[0058] Initial production events for each unit:

[0059]

[0060] in, This represents the initial production event for each device and is a fixed parameter. Indicates whether the first production event has occurred on device u. This indicates that the first production event has occurred on device u.

[0061] 2. Is the production duration of the initial production event of the device subject to constraints?

[0062] The constraints on the production duration of the initial production event are:

[0063]

[0064] This serves as the identifier for the production duration of the first production event on device u. When the initial production event of the device has a production duration constraint, the corresponding duration constraint binary variable is... The value is assigned to 1.

[0065] 3. Set whether the device needs to undergo maintenance production events within the scheduling cycle.

[0066] The constraints for determining whether maintenance is required within the current scheduling cycle are:

[0067]

[0068] Indicates whether device u is under maintenance; This indicates that maintenance is being carried out. This indicates that maintenance is not required.

[0069] By using constraint (3), when the target device u needs to be repaired within the scheduling cycle, a binary variable representing whether the maintenance production event "mc" occurs can be implemented. The value is assigned to 1.

[0070] In one exemplary embodiment, task allocation constraints are key to determining the sequence of start and end events and production events for each device through logical relationships. In step S1, setting task allocation constraints includes:

[0071] 1. Set the initial and final events of the device;

[0072] Each device must have only one initial event and one termination event, subject to the following constraint:

[0073]

[0074]

[0075] In the above formula, This is a binary variable indicating whether the production event msc on device u is an initial event. This is a binary variable indicating whether the production event msc on device u is a termination event.

[0076] 2. Configure the execution logic relationship between the device's initial or final events and production events;

[0077] If a production event is the first or last to be executed within the scheduling cycle, i.e., it is the initial or final event, then it will definitely be executed. However, the converse is not true; that is, an event is not necessarily an initial or final event. The execution logic relationship between the initial or final event and the production event of this device is constrained by the following conditions:

[0078]

[0079] This is a binary variable representing whether the production event msc is executed on device u.

[0080] 3. Set the switching logic relationship between the initial event and the end event of the device.

[0081] If a production event is an initial event, then that production time has no preceding events; if an event is an ending event, then it has no following events. The specific switching logic constraints for the initial or ending events of a device are as follows:

[0082]

[0083]

[0084] A binary variable representing whether there is a sequential switching relationship between events mmsc and msc on device u. =1 indicates the switching from production event msc to production event mmsc on device u.

[0085] In one exemplary embodiment, since production events consist of five types of operations, determining the production duration of different types of events requires categorized discussion and setting time constraints, including:

[0086] 1. Set production duration constraints when the device production event is an initial event or an end event;

[0087] Taking the production event "Genuine mp1" as an example, when "Genuine mp1" is the initial event or the final event, the production duration constraint for this production event is as follows:

[0088]

[0089]

[0090]

[0091]

[0092] In the above formula, As a variable characterizing the production duration of production event mp1, A binary variable characterizing whether production event mp1 is an initial event. M is a binary variable used to characterize whether the production event mp1 is a termination event. M is a large M constant, which can be set according to specific circumstances, such as 10000. To achieve the shortest production time during the scheduling cycle, This represents the scheduling cycle length.

[0093] The above four constraints ensure that if the genuine mp1 is the initial event or the end event, then the production duration will be between the set minimum duration and the length of the scheduling interval, such as 24h~744h.

[0094] Because the minimum production time for initial and final events differs from that for intermediate events, they need to be handled separately.

[0095] 2. Set production duration constraints when the device's production event is an intermediate event;

[0096] When a production event is an intermediate event, the switching feasibility rules determine that the good product of the intermediate event is obtained by switching the preceding transition material corresponding to the good product, and can only be switched to the corresponding subsequent transition material. Therefore, the production duration constraints when the production event of the unit is an intermediate event include:

[0097]

[0098]

[0099] In the above formula, A binary variable characterizing whether production event mp1 was executed. This is the minimum production time corresponding to intermediate event mp1, which is the lower limit of the execution time from switching from the preceding transition material (mp4a) of genuine event mp1 to genuine event mp1, and then switching to the following transition material of genuine event mp1. This represents the maximum production time corresponding to intermediate event mp1, i.e., the upper limit of the execution time from switching from the preceding transition material (mp4a) of genuine event mp1 to genuine event mp1, and then switching back to the following transition material of genuine event mp1. The variable represents the actual production duration of production event mp1.

[0100] For production events including preceding transition material, subsequent transition material, shutdown, and maintenance, the corresponding production duration constraints are determined based on the switchover feasibility rules as follows:

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109] 3. Establish the relationship between the end time of the first production event and the start time of the second production event in two adjacent production events on the device. The specific constraints are as follows:

[0110] The relationship between the start and end times of production and the production duration:

[0111]

[0112] The start time of the production event msc. The end time of the production event MSC. The production duration for the production event msc.

[0113] Since the equipment operates in a continuous production state for each production event, the start time of the next production event should be the end time of the previous production event. The specific constraint is as follows:

[0114]

[0115] A binary variable representing the switching from production event msc to production event mmsc on device u.

[0116] 4. Set a constraint that the total duration of production events in the unit is equal to the scheduling cycle;

[0117] The total duration of all production events occurring on the unit should equal the entire scheduling cycle. The constraint that the total duration of unit production events equals the scheduling cycle is as follows:

[0118]

[0119] 5. Set constraints on the end time of the termination event and the scheduling cycle on the device;

[0120] The end time of a termination event on the device cannot be later than the scheduling cycle. The constraint between the end time of a termination event on the device and the scheduling cycle is set as follows:

[0121]

[0122] in, A binary variable characterizing whether the production event msc is executed. This represents the scheduling cycle length.

[0123] In an exemplary embodiment, material constraints are used to calculate the production volume of products on each device and to summarize the production volume of a certain product across all devices. In this embodiment, products include main products, preceding transition materials, and subsequent transition materials; in step S1, setting material constraints includes:

[0124] 1. Determine the production volume of products on all units;

[0125] For genuine products, with production volume as the variable, their size must fall within the range of the upper and lower limits of the production rate multiplied by the corresponding production time to determine the range of genuine product production volume:

[0126]

[0127] In the above formula, This represents the minimum production rate of the genuine product mp1 on device u. This represents the maximum production rate of the genuine MP1 on device u. The production time of the genuine MP1 on device u. The production volume of genuine MP1 for device u.

[0128] After determining the range of genuine product production volume using the above formula, we can further calculate the daily inventory of raw materials.

[0129] The yields of the preceding and subsequent transition materials in the product are obtained from the following equation:

[0130]

[0131]

[0132] The total output of a certain product on all devices can be calculated using equations (27) to (29):

[0133]

[0134]

[0135]

[0136] 2. Set the production volume of genuine products on all devices to meet the demand constraints.

[0137] After obtaining the total output of a certain product across all equipment, set a constraint that the production volume of the product on all equipment meets the demand:

[0138]

[0139] In the above formula, For the production of genuine MP1s on all devices, This represents the lower limit of demand for genuine MP1 players. This represents the upper limit of demand for genuine MP1 players.

[0140] In one exemplary embodiment, two adjacent devices, a first device u and a second device uu, are determined, along with a shutdown event ms on the first device u and a shutdown event mms on the second device uu; the possible switching event relationships between the two devices are decomposed as follows: Figure 3 As shown in the figure, there are two possibilities for achieving non-simultaneous shutdown of the two devices: non-overlapping lag and non-overlapping advance, meaning as long as there is no partial overlap. Based on the above analysis, adding a binary auxiliary variable... Set constraints to ensure that the downtime of two adjacent devices does not overlap, including:

[0141] If the shutdown event ms on the first device u ends first and the shutdown event mms on the second device uu starts later, then the end time of the shutdown event ms on the first device u is set to be earlier than the start time of the shutdown event mms on the second device uu.

[0142]

[0143]

[0144] If the shutdown event mms of the second device uu ends first and the shutdown event ms of the first device u begins later, then the end time of the shutdown event mms of the second device uu is set to be earlier than the start time of the shutdown event ms of the first device u.

[0145]

[0146]

[0147] The above constraints are designed to address the problem of limited human resources for shutdown operations and to prevent two adjacent units from undergoing shutdown operations simultaneously.

[0148] In one exemplary embodiment, due to the involvement of multiple conversions involving catalysts, formulations, and other aspects, the operation is relatively complex. The switching times for some production events need to be restricted to weekday daytime working hours, such as 9:00 AM to 5:00 PM from Monday to Friday. For example, 9:00 AM on the first day is used as the scheduling starting point, and the scheduling starting point for each subsequent day is also set to 9:00 AM, i.e., as shown in the parameter table. The corresponding work time ends at 8 hours, which is also the time specified in the parameter table. Add a binary auxiliary variable This is used to indicate the number of days corresponding to the end of production for a genuine product. For example, if genuine MP1 ends production at 12 noon on the 10th day and is about to switch to another production event, then... .like Figure 4 As shown in the diagram of work time switching constraints, based on the above limitations, the constraint that the switching time of a production event must fall within work time is set as follows:

[0149] The switching time for production events should be set no earlier than the start time of the day shift and no later than the end time of the day shift, i.e., limited to a range. Inside:

[0150]

[0151]

[0152] In one exemplary embodiment, setting raw material inventory constraints includes: obtaining the daily production duration of each production event within the time to be optimized, determining the corresponding daily raw material inventory based on the initial production rate of the production event, and limiting it within a set upper and lower limit range.

[0153] In one exemplary embodiment, setting raw material inventory constraints includes:

[0154] 1. Calculate the overlap duration of each production event with each natural day to obtain the daily production duration of the production event;

[0155] 2. Calculate the daily production volume based on the initial production rate of daily production duration and production events;

[0156] 3. Calculate daily raw material inventory based on daily production and raw material consumption;

[0157] 4. Set the daily raw material inventory within the upper and lower limits of the daily inventory value.

[0158] In one exemplary embodiment, calculating the overlap duration of each production event with each natural day to obtain the daily production duration of the production event includes:

[0159] 1. Set a constraint that the overlap start time is no earlier than the production event start time and no earlier than the start time of the current calendar day. If the constraint is not met, relax the constraint using the Big M method.

[0160] 2. Set a constraint that the overlap end time is no later than the production event end time and no later than the end time of the current calendar day. If the constraint is not met, relax the constraint using the Big M method.

[0161] 3. Based on the difference between the determined overlap end time and overlap start time, calculate the daily production duration of the production event on the corresponding natural day.

[0162] In one exemplary embodiment, the raw materials used in chemical material production are generally liquids with low compressibility and strict storage conditions. Inventory overflow or shortage can lead to serious production accidents. Therefore, actual production requires daily material balance calculations. However, for scheduling optimization models, especially continuous-time modeling, there is generally no strict time division; the start and end times of production on each unit are different, making it difficult to find synchronized time nodes for material balance calculations. This invention proposes an expression method for overlapping time, such as... Figure 5 The diagram illustrates the overlap between production intervals and daily intervals. This invention proposes a method for expressing overlapping time. For example, if the production interval for a certain production event is 12-60 hours, then this means the overlap with the first day is 12 hours, the overlap with the second day is 24 hours, and the overlap with the third day is 12 hours. This allows us to obtain the production duration of the event each day, multiply it by the corresponding production rate to obtain the production quantity, and then, based on the product formula, obtain the daily raw material consumption, achieving the goal of daily raw material inventory balance.

[0163] Based on the above illustration, the overlap duration of each production event with each natural day is calculated to obtain the daily production duration of the production event, which is obtained through the following nonlinear equation:

[0164]

[0165] Solving the above nonlinear equations is quite difficult and requires corresponding linearization. Equation (40) can be solved by introducing continuous auxiliary variables. and binary auxiliary variables To achieve linearization, the linearization formula is:

[0166]

[0167]

[0168]

[0169]

[0170]

[0171]

[0172]

[0173]

[0174]

[0175]

[0176]

[0177] The overlap duration of each production event with each natural day can be calculated using equations (41) to (51) above, thus obtaining the daily production duration of the production event. .

[0178] In one exemplary embodiment, based on the obtained production event duration per day... Further, the daily inventory balance of raw materials is calculated according to the following steps:

[0179] Step 1: Calculate the daily output for each production event using the estimated rate.

[0180] Since both rate and duration are continuous variables, and the multiplication of two continuous variables constitutes a nonlinear equation, it is very difficult to solve directly. Therefore, the rate is set as a guess value here, thereby transforming the nonlinear equation into a linear equation.

[0181]

[0182] The second step is to calculate the daily raw material consumption for each production event.

[0183]

[0184] Step 3: Calculate daily raw material consumption.

[0185]

[0186] Step 4: Calculate the daily raw material supply

[0187]

[0188] Step 5: Calculate daily raw material inventory

[0189]

[0190] Step 6: Limit daily inventory value to upper and lower limits.

[0191]

[0192] In one exemplary embodiment, establishing the objective function with profit maximization as the goal includes:

[0193] The first step is to determine the product's sales profit, raw material consumption cost, processing fee cost, and downtime cost;

[0194] The second step is to determine the profit based on the product's sales profit, raw material consumption cost, processing fee cost, and downtime cost, and then obtain the total profit from the profit of each product.

[0195] The third step is to establish an objective function with the goal of maximizing total profit.

[0196] In this embodiment, the objective function is:

[0197] (1)

[0198] in, Indicates the product's sales profit;

[0199] This indicates the cost of raw materials consumed by the product;

[0200] This indicates the processing cost of the product;

[0201] This indicates the cost of work stoppage.

[0202] In an exemplary embodiment, in step S2, the current optimization model is solved, and the optimization model is updated using the production rate obtained from the solution. Specifically, based on the established objective function, combined with the optimization model of chemical material production scheduling with constraints (2) to (57), a commercial solver such as Gurobi is used to solve the model and obtain the production rate variable.

[0203] In one exemplary embodiment, the rate prediction value in formula (52) is updated using the value of the rate variable obtained from the solution, and then the optimization model for chemical material production scheduling is iteratively solved until the iteration termination condition is met, at which point the iteration ends and the final optimization result is obtained. The iteration termination condition is, for example, that the relative error of the rate variable obtained from the two solutions is less than a set accuracy requirement, such as 0.001.

[0204] The method for optimizing the production scheduling of chemical materials implemented in this embodiment has the following technical effects:

[0205] 1. Based on meeting the basic requirements, by adding a switching time window constraint, it is achieved that shutdowns of similar devices cannot occur simultaneously, and some switching is carried out within a set time range;

[0206] 2. By obtaining the daily production duration of each production event within the time to be optimized, and based on the initial production rate of the production event, the corresponding daily raw material inventory is determined, thus realizing raw material inventory constraints and solving the problems of variable rate and high and low limits of raw material inventory.

[0207] Secondly, embodiments of the present invention also provide a chemical material production scheduling optimization device, such as... Figure 2 As shown, the device includes a memory S200 and a processor S210; the memory is used to store a program for optimizing the production scheduling of chemical materials, and the processor is used to read and execute the program for optimizing the production scheduling of chemical materials, and execute the method described in any of the above embodiments.

[0208] Thirdly, embodiments of the present invention also provide a computer-readable storage medium storing a data processing program, wherein the data processing program is executed by a processor using the chemical material production scheduling optimization method described in any one of the above embodiments.

[0209] Example 1

[0210] The above-mentioned optimization method for chemical material production scheduling, which integrates constraints from multiple factors such as time and materials, was used to optimize a certain production system. The basic information of the production system is shown in Table 1. The production system comprises 5 polyethylene units, capable of producing 40 grades. The established optimization model for chemical material production scheduling contains over 70,000 equations and over 40,000 variables (including over 10,000 binary variables). The solution time for the optimization model was 216 seconds.

[0211] Table 1

[0212]

[0213] Based on the optimization results of chemical material production scheduling, the five units were switched 2, 1, 2, 4 and 1 times respectively. A total of 13 grades were selected from 40 grades for scheduling and production. The switching time between grades met the time window requirements of the day shift on weekdays, and the downtime of the several units did not overlap.

[0214] Raw material inventory changes such as Figure 6 As shown in the raw material inventory change curve, there were no instances of inventory overflow or shortage throughout the entire cycle, verifying the effectiveness of the method.

[0215] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

Claims

1. A method for optimizing the production scheduling of chemical materials, characterized in that, include: An objective function is established with profit maximization as the goal, and constraints are set to build an optimization model for chemical material production scheduling. The constraints include initial constraints, task allocation constraints, time constraints, material constraints, switching time window constraints, and raw material inventory constraints. Among them, the switching time window constraints include no overlap in the downtime of two adjacent units and the setting that the switching time of the production event is during working hours. The raw material inventory constraints include obtaining the daily production duration of each production event within the time to be optimized, determining the corresponding daily raw material inventory based on the initial production rate of the production event, and setting it within the upper and lower limits of the daily inventory value. Solve the current optimization model, and update the optimization model using the production rate obtained from the solution; Return to the solution of the current optimization model until the iteration termination condition is met, and obtain the final optimization result.

2. The chemical material production scheduling optimization method as described in claim 1, characterized in that, Set initial constraints, including: Set the initial production event of the device; Is the production duration of the initial production event of the device subject to constraints? The system determines whether a maintenance or production event needs to occur within the scheduling cycle.

3. The chemical material production scheduling optimization method as described in claim 1, characterized in that, Set task assignment constraints, including: Set the initial and final events of the device; Configure the execution logic relationship between the initial or final events of the device and production events; Configure the switching logic between the initial event and the end event of the device.

4. The chemical material production scheduling optimization method as described in claim 1, characterized in that, Set time constraints, including: Set production duration constraints when the device production event is set as an initial event or an end event; Set production duration constraints when the device production event is an intermediate event; Establish the relationship between the end time of the first production event and the start time of the second production event in two adjacent production events on the device; Set a constraint that the total duration of production events in the unit equals the scheduling cycle; Set constraints on the end time of the termination event and the scheduling cycle on the device.

5. The chemical material production scheduling optimization method as described in claim 1, characterized in that, Set material constraints, including: Determine the production volume of genuine products on all devices; Set the production volume of genuine products on all devices to meet the demand constraint.

6. The chemical material production scheduling optimization method as described in claim 1, characterized in that, The constraints for setting downtime non-overlapping for two adjacent devices include: Identify two adjacent devices, device 1 and device 2, and shutdown events on device 1 and device 2; If the shutdown event on the first device ends first and the shutdown event on the second device begins later, then the end time of the shutdown event on the first device is set to be earlier than the start time of the shutdown event on the second device. If the shutdown event of the second device ends first and the shutdown event of the first device begins later, then the end time of the shutdown event of the second device is set to be earlier than the start time of the shutdown event of the first device.

7. The chemical material production scheduling optimization method as described in claim 1, characterized in that, The constraint is set that the switching time of production events falls within working hours: The switching time for production events should be set no earlier than the start time of the day shift and no later than the end time of the day shift.

8. The chemical material production scheduling optimization method as described in claim 1, characterized in that, Obtain the daily production duration for each production event within the timeframe to be optimized. Based on the initial production rate of the production event, determine the corresponding daily raw material inventory and set it within the upper and lower limits of the daily inventory value, including: Calculate the overlap duration of each production event with each natural day to obtain the daily production duration of the production event; Calculate daily production volume based on the initial production rate of daily production duration and production events; Calculate daily raw material inventory based on daily production volume and raw material consumption; Set the daily raw material inventory to be within the upper and lower limits of the daily inventory value.

9. The chemical material production scheduling optimization method as described in claim 8, characterized in that, The calculation of the overlap duration of each production event with each natural day to obtain the daily production duration of the production event includes: Set constraints that the overlap start time is no earlier than the production event start time and no earlier than the start time of the current calendar day. If the constraints are not met, relax the constraints using the Big M method. Set a constraint that the overlap end time is no later than the production event end time and no later than the end time of the current calendar day. If the constraint is not met, relax the constraint using the Big M method. Based on the difference between the determined overlap end time and overlap start time, the daily production duration of the production event on the corresponding natural day is calculated.

10. The chemical material production scheduling optimization method as described in claim 8, characterized in that, The objective function established with profit maximization as its goal includes: Determine the product's sales profit, raw material consumption cost, processing fee cost, and downtime cost; Profit is determined based on the product's sales profit, raw material consumption cost, processing fee cost, and downtime cost. The total profit is obtained from the profit of each product. Establish an objective function with the goal of maximizing total profit.

11. A chemical material production scheduling optimization device, characterized in that, The device includes a memory and a processor; the memory is used to store a chemical material production scheduling optimization program, and the processor is used to read and execute the chemical material production scheduling optimization program to perform the method according to any one of claims 1-10.

12. A computer-readable storage medium storing a data processing program, the data processing program being executed by a processor according to any one of claims 1-10, the chemical material production scheduling optimization method.

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