Petrochemical product shipping allocation data processing method, medium, device and electronic equipment

Abstract

The embodiment of the invention provides a petrochemical product shipping allocation data processing method, a medium, a device and electronic equipment. The method comprises the following steps: firstly, acquiring related planning reference data including production, inventory, waybills, berths and ship data; then, a mixed integer programming model is constructed, an objective function and constraint functions are defined in the model, and the objective function and the constraint functions comprise a first constraint function for constraining the relation between the reserves of the petrochemical products and the capacity of the storage tank; and based on the planning reference data, shipping deployment planning data of the petrochemical product in the planning period is determined through the model, and the shipping deployment planning data comprises the matching relation of time periods, ships, waybills and berths. And if the model solution result is no solution, adding a slack variable in the first constraint function to form a second constraint function, and performing solution again. And if the re-solving result is that a solution exists, indicating that a conflict exists between the reserves of the petrochemical products and the capacity of the storage tank. According to the technical scheme, the efficiency of positioning the shipping allocation bottleneck of the petrochemical products can be improved.

Description

Technical Field

[0001] The present application relates to the field of data processing and logistics technology, and in particular to a method, device, medium and electronic equipment for processing petrochemical product shipping allocation data. Background Art

[0002] The transportation and allocation of petrochemical products is a key link in the inventory management of petrochemical refining enterprises. Usually, according to the sales characteristics of petrochemical products, in addition to configuring storage tank inventory in the factory area, corresponding storage areas will be set up according to customer areas to replenish stocks from the factory area regularly. When conditions permit, petrochemical products can be directly transported to port berths through pipelines. The main mode of transportation for most crude oil and refined oil is by ship transportation. Since berth resources are limited and under continuous production, it is necessary to comprehensively consider the storage limitations of factory storage tanks. Based on the existing number of berths, it is necessary to reasonably arrange the operating berths and operating hours of ships that transport goods by sea, and comprehensively formulate allocation plans.

[0003] In the prior art, a patent with publication number CN117455343A discloses a method, device and electronic device for processing shipping allocation data of petrochemical products, which is based on planning reference data including at least production data of petrochemical products, inventory data, waybill data, berth data in ports, and ship data for executing waybills, and solves the shipping allocation planning data within the planning period including at least the matching relationship between time periods, ships, waybills, and berths within the planning period through a shipping allocation model defined by a mixed integer programming model. However, if the solution result of the shipping allocation planning data is no solution, the existing scheme does not provide a solution for locating the bottleneck of petrochemical product shipping allocation, and can only be determined based on manual experience analysis. However, the efficiency of manually locating the bottleneck of petrochemical product shipping allocation is low, and it cannot meet the user's demand for high efficiency of petrochemical product shipping allocation data processing. Based on this, how to improve the efficiency of locating the bottleneck of petrochemical product shipping allocation is a technical problem that needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present application provide a method, device, computer program product or computer program, computer-readable medium and electronic device for processing petrochemical product shipping allocation data, which can improve the rationality of petrochemical product shipping allocation data processing at least to a certain extent.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0006] According to one aspect of an embodiment of the present application, a method for processing petrochemical product shipping allocation data is provided, the method comprising: obtaining planning reference data for petrochemical product shipping allocation, the planning parameters comprising at least production data, inventory data, waybill data, berth data in ports, and ship data for executing waybills of petrochemical products; constructing a mixed integer programming model, and defining an objective function and a constraint function for petrochemical product shipping allocation in the mixed integer programming model to obtain a shipping allocation model, the constraint function comprising a first constraint function for constraining the size relationship between petrochemical product reserves and petrochemical product storage tank capacity; based on the planning reference data, The first shipping allocation planning data of the petrochemical product within the planning period is solved by the shipping allocation model, and the first shipping allocation planning data at least includes the matching relationship between the time period, the ship, the waybill, and the berth within the planning period; if the result of solving the first shipping allocation planning data of the petrochemical product within the planning period by the shipping allocation model is that there is no solution, then a slack variable is added to the first constraint function to obtain a second constraint function, and the first shipping allocation planning data of the petrochemical product within the planning period is solved again by the shipping allocation model; if the result of the re-solution is that there is a solution, it is determined that there is a conflict between the reserves of the petrochemical product and the capacity of the petrochemical product storage tank.

[0007] In some embodiments of the present application, based on the above solution, before re-solving the first shipping allocation planning data of petrochemical products within the planning period through the shipping allocation model, the method further includes: further defining the following objective function in the mixed integer programming model:

[0008]

[0009] Among them, R i,t represents the slack variable of petrochemical product storage tank i in time period t; I represents the set of all petrochemical product storage tanks in the planning period; T represents the set of all time periods in the planning period.

[0010] In some embodiments of the present application, based on the aforementioned scheme, after determining that there is a conflict between the reserves of petrochemical products and the capacity of petrochemical product storage tanks, the method also includes: based on the planning reference data, establishing a domain model about ports, berths, ships, refineries, crude oil storage tanks, petrochemical product storage tanks, and refinery production plans; based on the domain model and the first shipping allocation planning data, simulating the petrochemical product shipping allocation within the planning period at least once according to the target time period granularity to obtain the second shipping allocation planning data within the planning period, and the target time period granularity is smaller than the time period granularity of the first shipping allocation planning data.

[0011] In some embodiments of the present application, based on the aforementioned scheme, the shipping allocation of petrochemical products within the planning period is simulated at least once according to the granularity of the target period, including: simulating the shipping allocation of petrochemical products within the planning period according to the granularity of the target period; if the simulation fails, recording the bottleneck data that caused the simulation failure; based on the bottleneck data, adjusting the domain model, and re-simulating the shipping allocation of petrochemical products within the planning period according to the granularity of the target period until the simulation is successful.

[0012] According to one aspect of an embodiment of the present application, a petrochemical product shipping allocation data processing device is provided, the device comprising: an acquisition unit, used to acquire planning reference data for petrochemical product shipping allocation, the planning parameters at least including production data, inventory data, waybill data, berth data in the port, and ship data executing the waybill of the petrochemical product; a construction unit, used to construct a mixed integer programming model, and define an objective function and a constraint function for petrochemical product shipping allocation in the mixed integer programming model to obtain a shipping allocation model, the constraint function including a first constraint function for constraining the size relationship between the petrochemical product reserves and the petrochemical product storage tank capacity; a solution unit, used to solve the problem of the relationship between the petrochemical product reserves and the petrochemical product storage tank capacity; Based on the planning reference data, the first shipping allocation planning data of the petrochemical products within the planning period is solved by the shipping allocation model, and the first shipping allocation planning data at least includes the matching relationship between the time period, ship, waybill, and berth within the planning period; if the result of solving the first shipping allocation planning data of the petrochemical products within the planning period by the shipping allocation model is that there is no solution, then a slack variable is added to the first constraint function to obtain a second constraint function, and the first shipping allocation planning data of the petrochemical products within the planning period is solved again by the shipping allocation model; if the result of the re-solution is that there is a solution, it is determined that there is a conflict between the reserves of the petrochemical products and the capacity of the petrochemical product storage tanks.

[0013] In some embodiments of the present application, based on the above solution, the construction unit is configured to: before re-solving the first shipping allocation planning data of petrochemical products within the planning period through the shipping allocation model, further define the following objective function in the mixed integer programming model:

[0014]

[0015] Among them, R i,t represents the slack variable of petrochemical product storage tank i in time period t; I represents the set of all petrochemical product storage tanks in the planning period; T represents the set of all time periods in the planning period.

[0016] In some embodiments of the present application, based on the aforementioned scheme, the device also includes: a simulation unit, which is used to establish a domain model about ports, berths, ships, refineries, crude oil storage tanks, petrochemical product storage tanks, and refinery production plans based on the planning reference data after determining that there is a conflict between the reserves of petrochemical products and the capacity of petrochemical product storage tanks; based on the domain model and the first shipping allocation planning data, simulate the petrochemical product shipping allocation within the planning period at least once according to the target time period granularity to obtain the second shipping allocation planning data within the planning period, and the target time period granularity is smaller than the time period granularity of the first shipping allocation planning data.

[0017] In some embodiments of the present application, based on the aforementioned scheme, the simulation unit is configured to: simulate the shipping allocation of petrochemical products within the planning period according to the granularity of the target time period; if the simulation fails, record the bottleneck data that caused the simulation failure; based on the bottleneck data, adjust the domain model, and re-simulate the shipping allocation of petrochemical products within the planning period according to the granularity of the target time period until the simulation is successful.

[0018] According to one aspect of the embodiments of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method described in the above embodiments.

[0019] According to one aspect of an embodiment of the present application, a computer-readable medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described in the above embodiment is implemented.

[0020] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the methods described in the above embodiments.

[0021] In the present application, after adding a slack variable to the constraint function for constraining the size relationship between petrochemical product reserves and petrochemical product storage tank capacity, if the result of the re-solution is changed from no solution to a solution, it indicates that the reason why the previous solution of the shipping allocation planning data is no solution is that there is a conflict between the petrochemical product reserves and the petrochemical product storage tank capacity at the preset time period granularity. Based on the technical solution proposed in the present application, there is no need to manually locate the bottleneck of petrochemical product shipping allocation, so the bottleneck of petrochemical product shipping allocation can be quickly located, thereby improving the efficiency of locating the bottleneck of petrochemical product shipping allocation.

[0022] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0024] Figure 1 A flow chart showing a method for processing petrochemical product shipping allocation data according to an embodiment of the present application is shown;

[0025] Figure 2 A block diagram of a petrochemical product shipping allocation data processing device according to an embodiment of the present application is shown;

[0026] Figure 3 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0027] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0028] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0029] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0030] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0031] It should be noted that the "multiple" mentioned in this article refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0032] In order to enable those skilled in the art to better understand the present application, before elaborating on the present solution in detail, the application scenario of the petrochemical product shipping allocation solution will be briefly described below.

[0033] Figure 1 The flowchart of a petrochemical product shipping allocation data processing method according to an embodiment of the present application is shown. The petrochemical product shipping allocation data processing method can be executed by a device with a computing and processing function. Figure 1 As shown, the petrochemical product shipping allocation data processing method includes at least steps 110 to 130, which are described in detail as follows:

[0034] In step 110, planning reference data for petrochemical product shipping allocation is obtained, and the planning parameters include at least production data, inventory data, waybill data, berth data in the port, and ship data executing the waybill of the petrochemical product.

[0035] In the present application, the production data of the petrochemical products may include basic production information of different petrochemical products produced by the refinery production equipment within the planning period, such as the daily production volume of each petrochemical product, etc.

[0036] In the present application, the inventory data of petrochemical products may include basic information of each storage tank area (such as crude oil storage tanks, petrochemical product storage tanks) within the planning period, such as the type of petrochemical products stored in the storage tank, the lower capacity limit, the upper capacity limit, etc.

[0037] In the present application, the waybill data of the petrochemical products may include basic information of the waybill within the planning period, such as the number of waybills, the petrochemical products that need to be allocated for each waybill, the time limit required for execution, etc.

[0038] In the present application, the ship data for executing the waybill may include basic information of the ship, such as the number of physical ships, the number of virtual ships, the loading capacity of each ship, the type of ship, etc.

[0039] In the present application, the berth data in the port may include basic information of the berths in the port, such as the number of parent-child berths or non-parent-child berths, the type of ships allowed to enter each berth, the available time of each berth, etc.

[0040] Continue to refer to Figure 1 In step 120, a mixed integer programming model is constructed, and an objective function and a constraint function for shipping allocation of petrochemical products are defined in the mixed integer programming model to obtain a shipping allocation model.

[0041] Specifically, in the present application, the objective function for petrochemical product shipping allocation defined in the mixed integer programming model may include the following formula (1):

[0042]

[0043] Among them, H l Indicates whether waybill l enters the berth for loading within the planning period, represented by 0 or 1, which is a variable; The number of time periods (e.g., days) that the ship executing waybill l enters the berth to load cargo in advance is a variable; The number of time periods that the ship executing waybill l delays entering the berth to load cargo is a variable; K represents the number of time periods for delayed delivery of waybill l, which is a variable; k,p,t Indicates whether ship k occupies berth p in time period r, represented by 0 or 1, which is a variable; C l represents the basic cost of waybill l, which is a constant; M1, M2, M3, M4 represent penalty coefficients, which are constants; L represents the set of all waybills within the planning period; T represents the set of all time periods within the planning period; K represents the set of all ships within the planning period; P represents the set of all berths in the port within the planning period.

[0044] In this application, the port berths can be constrained in the mixed integer programming model:

[0045] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (2) and formula (3):

[0046]

[0047] Among them, K k,p,t Indicates whether ship k occupies berth p in time period k, represented by 0 or 1, which is a variable; K p represents the set of ships allowed to enter berth p during the planning period; P represents the set of all berths in the port during the planning period; K represents the set of all ships during the planning period; T represents the set of all time periods during the planning period.

[0048] In formula (2) and formula (3), the relationship between ships and berths is mainly constrained, that is, only one ship that meets the berth requirements can enter or exit a berth at the same time period, and the same ship can only appear at one berth at the same time period.

[0049] Specifically, the constraint function for petrochemical product shipping allocation defined in the mixed integer programming model may include the following formula (4):

[0050]

[0051] Among them, PO p,t Indicates whether berth p is occupied by a ship in time period t, represented by 0 or 1, which is a variable; represents the set of unavailable periods of berth p within the planning period; P represents the set of all berths in the port within the planning period.

[0052] In formula (4), the main constraint is on the berth availability, that is, the berth cannot accommodate ships during the unavailable period.

[0053] Specifically, the constraint function defined in the mixed integer programming model for petrochemical product shipping allocation may include the following formula (5):

[0054]

[0055] Among them, PO′ p,t Indicates whether the parent berth p is occupied by a ship in time period t, represented by 0 or 1, which is a variable; PN p Indicates the number of child berths contained in the parent berth p, which is a constant; PO′ ps,t Indicates whether the child berth ps is occupied by a ship in time period t, represented by 0 or 1, which is a variable; PS represents the set of all parent berths in the port during the planning period; PS p Represents the set of all child berths of the parent berth p within the planning period.

[0056] In formula (5), the main constraints are imposed on the parent-child berths, that is, the parent-child berths can park ships of different models, and in the same period of time, only the parent berth or multiple child berths can be used in a group of parent-child berths.

[0057] In this application, the constraints of port berths are defined in a mixed integer programming model, and the relationship between berths and ships can be pre-built, where some berths allow one large ship or two small ships to dock, which is achieved by establishing a relationship between a parent berth and a child berth. There are independent restrictions on the number of ships that can be docked and independent petrochemical product loading and unloading rates between the parent berth and the child berth. In the same time period, only one of the parent berth and the child berth can be activated at the same time.

[0058] In this application, the ship can be constrained in the mixed integer programming model:

[0059] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (6):

[0060]

[0061] Among them, K k,p,t Indicates whether ship k occupies berth p in time period t, represented by 0 or 1, which is a variable; Kt l It indicates the number of time periods that a ship executing waybill l needs to occupy at least for loading at a berth, which is a constant. K represents the set of all ships in the planning period; P represents the set of all berths in the port in the planning period; T represents the set of all time periods in the planning period; and L represents the set of all waybills in the planning period.

[0062] In formula (6), the main constraint is on the ship's stay in the port, that is, ships executing the same waybill need to stay in the port for at least the minimum entry, exit and loading period. If there is a queue for entry or an invalid stay at the berth, additional rent will be paid according to the period.

[0063] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (7):

[0064]

[0065] in, K represents the cargo volume of ship k carrying out waybill l, which is a constant; k,p,t Indicates whether ship k occupies berth p in time period t, represented by 0 or 1, which is a variable; CK k represents the ship capacity of ship k, which is a constant; L represents the set of all waybills within the planning period; K represents the set of all ships within the planning period; P represents the set of all berths in the port within the planning period; T represents the set of all time periods within the planning period.

[0066] In formula (7), the relationship between ships and petrochemical products is mainly constrained, that is, the same ship can only load one petrochemical product at the same time, and the planned loading volume of the ship is less than the ship capacity.

[0067] Specifically, the constraint function defined in the mixed integer programming model for petrochemical product shipping allocation may include the following formulas (8) to (13):

[0068]

[0069] Among them, Kk,p,t Indicates whether ship k occupies berth p in time period t, represented by 0 or 1, which is a variable; Y l,t Indicates whether the ship enters the berth to load cargo in time period t when executing waybill l, represented by 0 or 1, which is a variable; YN l,t Indicates whether the ship leaves the berth in time period t when executing the waybill l, represented by 0 or 1, which is a variable; H l Indicates whether waybill l enters the berth for loading within the planning period, represented by 0 or 1, which is a variable; It represents the earliest time period for the ship to execute the waybill l, which is a variable; It represents the number of time periods that the ship executing waybill l enters the berth to load cargo in advance, which is a variable; It indicates the latest time for the ship to execute the waybill l, which is a variable; The number of time periods that the ship executing waybill l delays entering the berth to load cargo is a variable; Indicates the maximum dispatch period for a ship to execute waybill l; l k represents the set of waybills executed by ship k within the planning period; K represents the set of all ships within the planning period; P represents the set of all berths in the port within the planning period; T represents the set of all time periods within the planning period.

[0070] In formula (8) to formula (13), the arrival of ships is mainly constrained. That is, ships with confirmed sailing dates must arrive at the port within the specified time period. If they arrive early, they must pay a dispatch fee. Ships with undetermined sailing dates make arrival plans according to ideal conditions without paying additional dispatch fees. Ships cannot enter and leave the berth in the same time period.

[0071] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (14) and formula (15):

[0072]

[0073] Among them, Y l,t Indicates whether the ship enters the berth to load cargo in time period t when executing waybill l, represented by 0 or 1, which is a variable; YN l,t It indicates whether the ship leaves the berth in time period t when executing waybill l, represented by 0 or 1, which is a variable; L represents the set of all waybills in the planning period; T represents the set of all time periods in the planning period.

[0074] In formula (14) and formula (15), constraints are mainly imposed on the entry and exit of ships. That is, a ship can enter the port at most once and leave the port at most once when executing the same waybill within the planning period. It is not allowed for a ship to enter the berth again to wait after loading at the berth when executing the same waybill.

[0075] In this application, the constraints on ships are defined in the mixed integer programming model, so that the deployment requirements of leased ships can be matched with available berths according to the length, tonnage and petrochemical products transported. For the deployment requirements of unleased ships, virtual ships can be leased according to the petrochemical products transported and the demand. The tonnage of the virtual ships is consistent with the demand, and the length refers to the historical leased ships to match the expected berths.

[0076] In this application, the petrochemical product storage tank can be constrained in the mixed integer programming model:

[0077] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the first constraint function of the following formula (16):

[0078]

[0079] in, represents the lower limit of the capacity of petrochemical product storage tank i, which is a constant; represents the upper limit of the capacity of petrochemical product storage tank i, which is a constant; represents the initial inventory of petrochemical product c in petrochemical product storage tank i in period t, which is a constant; TI i,c,t represents the flow rate of petrochemical product c input to petrochemical product storage tank i in time period t, which is a variable; TO i,c,t represents the flow rate of petrochemical product c output from petrochemical product storage tank i in time period t, which is a variable; I represents the set of all petrochemical product storage tanks within the planning period; T represents the set of all time periods within the planning period; C represents the set of all petrochemical product types within the planning period.

[0080] In formula (16), the main constraint is on the relationship between the reserves of petrochemical products and the capacity of the petrochemical product storage tank, that is, the reserves of petrochemical products in the petrochemical product storage tank is greater than the lower limit of the capacity of the petrochemical product storage tank and less than the upper limit of the capacity of the petrochemical product storage tank.

[0081] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (17) and formula (18):

[0082]

[0083] Among them, TI i,c,t represents the flow rate of petrochemical product c input to petrochemical product storage tank i in time period t, which is a variable; TO i,c,t represents the flow rate of petrochemical product c output from petrochemical product storage tank i in time period t, which is a variable; C represents the set of all petrochemical product types in the planning period; I represents the set of all petrochemical product storage tanks in the planning period; Represents the set of unavailable periods of petrochemical product storage tank i within the planning period.

[0084] In formula (17) to formula (18), the main constraints are imposed on unusable petrochemical product storage tanks, that is, when a petrochemical product storage tank contains unqualified petrochemical products or mixed products or is in an unusable state such as maintenance, it is not allowed to use the petrochemical product storage tank to mix petrochemical products, nor can the petrochemical product storage tank be used to load newly produced petrochemical products.

[0085] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (19) and formula (20):

[0086]

[0087] Among them, AO a,c,t represents the output flow of petrochemical product c from storage tank area a in time period t, which is a variable; TO i,c,t represents the flow rate of petrochemical product c output from petrochemical product storage tank i in time period t, which is a variable; AI a,c,t represents the flow rate of petrochemical product c input into storage tank area a during period t, which is a variable; TI i,c,t represents the flow rate of petrochemical product c input into petrochemical product storage tank i in time period t, which is a variable; c represents the set of petrochemical product storage tanks that can be loaded with petrochemical product c in oil storage tank area a within the planning period; A represents the set of all oil storage tank areas within the planning period; C represents the set of all petrochemical product types within the planning period; T represents the set of all time periods within the planning period.

[0088] In formula (19) to formula (20), the relationship between the petrochemical product storage tank and the storage tank area is mainly constrained, that is, the total output flow of the storage tank area is equal to the sum of the petrochemical product output flow of each petrochemical product storage tank in the storage tank area; the total input flow of the storage tank area is equal to the sum of the petrochemical product input of the petrochemical product storage tanks in the storage tank area.

[0089] In this application, the storage tank area can be constrained in the mixed integer programming model:

[0090] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (21):

[0091]

[0092] Among them, AI a,c,tIt represents the flow rate of petrochemical product c input into storage tank area a in time period t, which is a variable. One petrochemical product produced by a production unit in one time period is only input into one tank area; SO j,c,t represents the flow rate of petrochemical product c produced by petrochemical product production unit j in time period t according to the production plan, which is a constant; A represents the set of all oil storage tank areas within the planning period; C represents the set of all petrochemical products within the planning period; T represents the set of all time periods within the planning period; J represents the set of production units that produce petrochemical product c within the planning period.

[0093] In formula (21), the inflow flow of petrochemical products into the storage tank area is mainly constrained.

[0094] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (22):

[0095]

[0096] Among them, AO a,c,t V represents the flow rate of petrochemical product c output from storage tank area a during period t, which is a variable; l Indicates the cargo volume of the ship executing the waybill l, which is a constant; YN l,t It indicates whether the ship leaves the berth in time period t when executing waybill l, represented by 0 or 1, which is a variable; A represents the set of all oil storage tank areas in the planning period; C represents the set of all petrochemical products in the planning period; L represents the set of all waybills in the planning period; T represents the set of all time periods in the planning period.

[0097] In formula (22), the outflow rate of petrochemical products from the storage tank area is mainly constrained.

[0098] In this application, constraints on petrochemical product storage tanks and storage tank areas are defined in a mixed integer programming model, so that when a petrochemical refinery enterprise schedules production according to a production plan, it can consider the capacity constraints of petrochemical product storage tanks in the refinery area, and reasonably schedule the selection of shipping berths and delivery periods for various types of refined oil products, thereby minimizing transportation costs and reducing waybill compensation caused by deployment delays. That is, considering the petrochemical product balance relationship of petrochemical product storage tanks in the refinery plant area during transportation deployment, the scheduling plan needs to avoid production stoppages or uneven berth scheduling caused by insufficient capacity of petrochemical product storage tanks in the plant area, thereby avoiding deployment delays.

[0099] In this application, the waybill can be constrained in the mixed integer programming model:

[0100] Specifically, the constraint function defined for petrochemical product shipping allocation in the mixed integer programming model may include the following formula (23):

[0101]

[0102] Among them, Y l,t Indicates whether the ship enters the berth to load cargo in time period t when executing the waybill l, represented by 0 or 1, which is a variable; H l It indicates whether waybill l enters the berth for loading within the planning period, represented by 0 or 1, which is a variable; L represents the set of all waybills within the planning period; T represents the set of all time periods within the planning period.

[0103] In formula (23), the execution of the waybill is mainly constrained, that is, when the waybill is loaded, it is considered as the waybill execution.

[0104] Continue to refer to Figure 1 In step 130, based on the planning reference data, the first shipping allocation planning data of the petrochemical products within the planning period is solved by the shipping allocation model, and the first shipping allocation planning data at least includes the matching relationship between the time period, the ship, the waybill, and the berth within the planning period.

[0105] In the present application, based on the planning reference data, the first shipping allocation planning data of the petrochemical products within the planning cycle is determined through the shipping allocation model. The planning reference data can be input into the shipping allocation model, and solved by a commercial solver (Gurobi, Cplex, Copt, etc.), so as to determine the first shipping allocation planning data of the petrochemical products within the planning cycle.

[0106] Specifically, the first shipping allocation planning data at least includes the matching relationship between time periods, ships, waybills, and berths within the planning cycle, that is, determining which ship executes which waybill in which time periods (when solving the first shipping allocation planning data, 1 day can be defined as 1 time period), and selecting which berth at the port to dock and load the cargo.

[0107] Continue to refer to Figure 1 In step 140, if the result of solving the first shipping allocation planning data of petrochemical products within the planning period through the shipping allocation model is that there is no solution, then a slack variable is added to the first constraint function to obtain a second constraint function, and the first shipping allocation planning data of petrochemical products within the planning period is solved again through the shipping allocation model.

[0108] Specifically, the second constraint function defined in the mixed integer programming model for petrochemical product shipping allocation may include the following formula (24):

[0109]

[0110] in, represents the lower limit of the capacity of storage tank i, which is a constant; Represents the upper limit of the capacity of storage tank i, which is a constant; represents the initial inventory of petrochemical product c in storage tank i during period t, which is a constant; TI i,c,t represents the flow rate of petrochemical product c input to storage tank i in time period t, which is a variable; TO i,c,t represents the flow rate of petrochemical product c output from storage tank i in time period t, which is a variable; R i,t represents the slack of storage tank i in time period t; I represents the set of all storage tanks in the planning period; T represents the set of all time periods in the planning period; C represents the set of all petrochemical product types in the planning period.

[0111] It can be seen that in the present application, by adding a slack variable to the first constraint function to obtain the second constraint function, the first constraint function can be replaced by the second constraint function for subsequent model solving.

[0112] Furthermore, in the present application, before resolving the first shipping allocation planning data of petrochemical products within the planning period through the shipping allocation model, an objective function of the following formula (25) may be further defined in the mixed integer programming model:

[0113]

[0114] Among them, R i,t represents the slack variable of petrochemical product storage tank i in time period t; I represents the set of all petrochemical product storage tanks in the planning period; T represents the set of all time periods in the planning period.

[0115] Based on the objective function as shown in formula (25), the relaxation amount can be minimized when solving the model.

[0116] Continue to refer to Figure 1 In step 150, if the result of the re-solution is that there is a solution, it is determined that there is a conflict between the petrochemical product reserves and the petrochemical product storage tank capacity.

[0117] It is understandable that after adding a slack variable to the constraint function for constraining the size relationship between petrochemical product reserves and petrochemical product storage tank capacity, if the result of the re-solution is changed from no solution to a solution, it indicates that the reason why the previous solution of the shipping allocation planning data was no solution is that there is a conflict between the petrochemical product reserves and the petrochemical product storage tank capacity at the preset time period granularity. Based on the technical solution proposed in this application, there is no need to manually locate the bottleneck of petrochemical product shipping allocation, so the bottleneck of petrochemical product shipping allocation can be quickly located, thereby improving the efficiency of locating the bottleneck of petrochemical product shipping allocation.

[0118] Based on this, if the solution is successful after adding slack variables, it means that the previous lack of solution is due to the tank problem, such as the mixing of the tank, the need for oil to stand, and the refining, which are difficult to characterize in the model. After obtaining the model output, further bottleneck analysis can be performed through simulation calculations.

[0119] Furthermore, in the present application, after determining that there is a conflict between the petrochemical product reserves and the petrochemical product storage tank capacity, the following steps 160 to 170 may also be performed:

[0120] Step 160, based on the planning reference data, establish a domain model about ports, berths, ships, refineries, crude oil storage tanks, petrochemical product storage tanks, and refinery production plans.

[0121] Step 170, based on the domain model and the first shipping allocation planning data, perform at least one simulation on the shipping allocation of petrochemical products within the planning period according to the target time period granularity to obtain the second shipping allocation planning data within the planning period, and the target time period granularity is smaller than the time period granularity of the first shipping allocation planning data.

[0122] In some embodiments, domain models for ports, berths, ships, refineries, crude oil storage tanks, petrochemical product storage tanks, and refinery production plans are established as follows:

[0123] 1. Port

[0124] Attributes: Number of berths: the number of berths that the port can accommodate at the same time; Occupancy status: records the current occupancy status of each berth (free or occupied); Unloading facilities: the capacity of the unloading facilities at the berth (unloading rate of each berth); Queue: the queue of ships waiting to enter the berth.

[0125] Functions: Ship dispatch: dispatch ships to berth according to the availability of berths; manage berth occupancy: update the berth occupancy status when ships dock or leave berths; oil unloading operations: manage the use of oil unloading facilities and control the transfer of crude oil from ships to crude oil storage tanks.

[0126] 2. Berth

[0127] Attributes: Berth ID: unique identifier of each berth; Unloading rate: capacity of the unloading facility connected to the berth (the amount of crude oil that can be unloaded per unit time); Berth status: records whether the berth is free or occupied by a ship.

[0128] Functions: Ship berthing: receiving dispatched ships and starting the oil unloading process; Oil unloading management: controlling the transfer of crude oil from ships to crude oil storage tanks and updating the inventory of crude oil storage tanks; Ship unberthing: when the oil unloading is completed, the berth is released and the occupancy status of the port is updated.

[0129] 3. Ships

[0130] Attributes: Oil capacity: the capacity of crude oil transported in a single trip; Arrival schedule: the time schedule for arrival at the port; Unloading rate: the speed at which crude oil is unloaded from the ship to the crude oil storage tank; Status: whether it is currently unloading, sailing, waiting, etc.

[0131] Functions: Unloading: transfer crude oil to the crude oil storage tanks at the port; Navigation: calculate the sailing time and adjust the arrival time according to the schedule (queue waiting: if all berths in the port are occupied, the ship enters the queue waiting for berthing; berthing request: when there is a vacant berth in the port, the ship requests berthing and enters the berth for unloading; unberthing: after unloading is completed, leave the berth and continue the next voyage or return to the oil field.)

[0132] 4. Refinery

[0133] Attributes: Processing capacity: the amount of crude oil that can be processed per unit time; Production plan: daily and weekly crude oil processing volume arrangements; Operation status: current operating status (normal, shutdown, maintenance); Finished oil output rate: the rate at which finished oil is produced.

[0134] Functions: Extracting crude oil: extracting crude oil from crude oil storage tanks for processing; Refining crude oil: converting crude oil into finished oil (including multiple processes such as distillation, cracking, etc.); Monitoring efficiency: monitoring and adjusting processing efficiency, and adjusting production plans according to market demand.

[0135] 5. Crude oil storage tank

[0136] Attributes: Capacity: Maximum storage capacity of the crude oil storage tank; Current inventory: The amount of crude oil currently stored in the crude oil storage tank; Input rate: The rate at which crude oil is injected into the crude oil storage tank (unloaded from the ship); Output rate: The rate at which crude oil enters the refinery from the crude oil storage tank; Warning lines: Upper and lower limits of storage levels, exceeding these lines will trigger an alarm.

[0137] Functions: Receiving crude oil: receiving crude oil from ships and updating storage capacity; Supplying crude oil: extracting crude oil according to the needs of refineries and updating storage capacity; Monitoring inventory: real-time monitoring and reporting of inventory changes, triggering alarms (for example, when approaching full load or below the safety line).

[0138] 6. Petrochemical product storage tanks

[0139] Attributes: Capacity: Maximum storage capacity of a petrochemical storage tank; Current Stock: Current amount of refined oil stored in the petrochemical storage tank; Input Rate: Rate at which refined oil is injected into the petrochemical storage tank (from the refinery production line); Output Rate: Rate at which refined oil is output from the petrochemical storage tank to the transportation channel; Warning Lines: Upper and lower limits of storage levels, exceeding these lines will trigger an alarm.

[0140] Functions: Receiving finished oil: receiving finished oil from refineries and updating storage volume; Supplying finished oil: exporting finished oil to transportation channels or customers based on demand; Monitoring inventory: real-time monitoring and reporting of inventory changes, triggering alarms (for example, when approaching full load or falling below the safety line).

[0141] 7. Production Planning

[0142] Attributes: Date: the date on which the production plan is implemented; Petrochemical products: the petrochemical products that need to be produced; Formula: the same petrochemical product may be produced from different oils in different proportions, and the formula will store its proportions and raw materials; Production rate: the refining production rate.

[0143] Furthermore, in the above step 170, the simulation of the petrochemical product shipping allocation within the planning period is performed at least once according to the target time period granularity, which can be performed according to the following steps 171 to 173:

[0144] Step 171 , simulating the shipping allocation of petrochemical products within the planning period according to the granularity of the target time period.

[0145] Step 172: If the simulation fails, the bottleneck data causing the simulation failure is recorded.

[0146] Step 173, based on the bottleneck data, adjust the domain model, and re-simulate the shipping allocation of petrochemical products within the planning period according to the target time period granularity until the simulation is successful, and the calculation is successfully completed and a reasonable shipping allocation plan with a finer time period granularity than the shipping allocation model is output.

[0147] In this application, before simulating the petrochemical product shipping allocation within the planning period according to the target time granularity, it is also necessary to define all the production rules of the detailed storage tanks as discrete events. The events will modify the attributes in the entity such as the storage tank level, whether the berth is in use, etc. Specifically, it can be defined as the following discrete events:

[0148] 1. Crude oil supply events:

[0149] o Extract crude oil from crude oil storage tanks according to the production schedule of the refinery.

[0150] oUpdate the inventory of crude oil storage tanks to ensure that the inventory is within safe range.

[0151] 2. Refinery production events:

[0152] After receiving the crude oil, the refinery conducts routine refining according to the plan to produce finished oil.

[0153] oStore refined oil in petrochemical product storage tanks and update the inventory of petrochemical product storage tanks.

[0154] o Sealing the tank: After the oil is produced, it needs to stay in the tank for a certain period of time before it can be produced or transported.

[0155] 3. Refining event:

[0156] o If the quality of finished oil in the petrochemical product storage tank does not meet the standard, or according to market demand, it is necessary to trigger the refining process. Refining will be used as a special production plan.

[0157] 4. Recycled oil storage incident:

[0158] oThe oil products that need to be recycled are transferred to the recycled crude oil storage tank, and the inventory of the recycled crude oil storage tank is updated.

[0159] 5. Recycling production events:

[0160] o Extract oil from the recycling tank for recycling, recover valuable components and store them in the recycling petrochemical product storage tank.

[0161] o Update the inventory of recycled petrochemical storage tanks and handle the waste generated by the recycling process.

[0163] 6. Ship arrival at port event:

[0164] oAfter the ship arrives at the port, it first checks the availability of port berths.

[0165] o If there is a free berth, the vessel berths and starts unloading; if there is no free berth, the vessel enters the queue.

[0166] 7. Vessel berthing and oil unloading incidents:

[0167] oThe port schedules ships to berth based on the availability of berths.

[0168] oAfter the vessel docks, it starts unloading crude oil into crude oil storage tanks using the unloading facilities at the berth.

[0169] 8. Completion of oil unloading and departure of the vessel:

[0170] o After unloading is completed, the vessel leaves the berth and updates the occupancy status of the port and berth.

[0171] o If there is a ship in the queue, dispatch the next ship to berth.

[0172] In the present application, after all production rules of detailed storage tanks are defined as discrete events, the petrochemical product shipping allocation within the planning period can be simulated according to the target period granularity, and the target period granularity is smaller than the period granularity of the first shipping allocation planning data. For example, the target period granularity can be minutes, that is, the production and transportation scheduling of the refinery is simulated in units of minutes, and the storage bottleneck is recorded at the time point when the storage space is insufficient (that is, the bottleneck data that causes the simulation failure is recorded). Among them, the storage bottlenecks include the following:

[0173] 1. Berth restrictions at the port result in ships arriving at inappropriate times, and crude oil cannot be loaded or petrochemical products cannot be transported away.

[0174] 2. The production plan is unreasonable.

[0175] 3. The number and capacity of storage tanks are insufficient.

[0176] Specifically, in this application, the simulation of petrochemical product shipping allocation within the planning period can be performed according to the following process:

[0177] The domain models for ships, refineries, ports, storage tanks, etc. are placed as entity classes in the discrete event simulation engine. The earliest event is selected from the discrete event event list, processed, and the system status is updated. If the event triggers other events (for example, the completion of ship unloading may trigger the refinery to start processing), these events are added to the event list. Continue to process the next earliest event, and repeat this process until the simulation end condition is met (such as all ships have completed unloading, or the predetermined simulation time limit is reached).

[0178] Initialization: At the beginning of the simulation, the initial status of the refinery, port, storage tank and ship is set, including oil inventory, ship arrival plan, etc.

[0179] Ship arrival and berthing: The mathematical model algorithm outputs the ship arrival schedule, which gradually simulates the ship's arrival and berthing. If the berth is free, the oil unloading event is triggered.

[0180] Oil unloading and storage: After the ship berths, the oil is unloaded into the tank. Monitor the capacity changes of the tank and trigger the event of the tank being full or the ship unloading completed.

[0181] Refinery production: Based on the output of the mathematical model algorithm, the refinery plans to regularly extract oil products from storage tanks for processing. According to the simulation logic, the refinery processing speed and output variety will affect the subsequent storage and transportation of oil products.

[0182] Cycle: When a ship unloads oil and leaves the port, a new ship docks and unloads oil, and the refinery continues to process. The simulation continuously processes these discrete events and updates the system state.

[0183] In practical applications, this application proposes a comprehensive optimization solution for the inventory management problems of petrochemical refineries in oil production, transportation, blending and storage. The production and storage of oil products are key links in refinery management. Because the start-up and shutdown costs of production units are high and they usually need to be operated continuously, product storage has become a focus of attention. Current technical solutions often focus on a single bottleneck area, lack industry attributes, and fail to effectively consider the material balance of port berth scheduling and storage tanks, which may lead to production suspension or delivery delays due to insufficient tank capacity.

[0184] This application aims to reasonably schedule the shipping berths and delivery time of refined oil products, and locate the oil storage bottleneck by establishing a mathematical model, taking into account the production plan and storage tank capacity of the refinery, thereby optimizing the production process. This solution combines mathematical models with discrete event simulation to effectively solve the problem of the difficulty in accurately locating the storage tank bottleneck, guide the refinery to adjust the production plan, and avoid losses caused by insufficient storage tank capacity.

[0185] The innovation of this application is to accurately locate the bottleneck of refinery storage tank capacity, optimize production plans, and guide refineries to add storage tanks that are actually needed during planning and construction. By comprehensively considering multiple factors, the efficiency of berth scheduling is improved, while transportation costs are reduced and the risk of order compensation caused by delivery delays is reduced. Overall, this application provides an effective solution for inventory management in the refining industry and has important practical application value.

[0186] The following describes an apparatus embodiment of the present application, which can be used to execute the petrochemical product shipping allocation data processing method in the above embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the above embodiment of the petrochemical product shipping allocation data processing method in the present application.

[0187] Figure 2 A block diagram of a petrochemical product shipping allocation data processing device according to an embodiment of the present application is shown.

[0188] Reference Figure 2 As shown, a petrochemical product shipping allocation data processing device 200 according to an embodiment of the present application includes: an acquisition unit 201, a construction unit 202 and a solution unit 203.

[0189] The acquisition unit 201 is used to acquire planning reference data for petrochemical product shipping allocation, wherein the planning parameters include at least production data, inventory data, waybill data, berth data in the port, and ship data for executing the waybill of the petrochemical product; the construction unit 202 is used to construct a mixed integer programming model, and define the objective function and constraint function for petrochemical product shipping allocation in the mixed integer programming model to obtain a shipping allocation model, wherein the constraint function includes a first constraint function for constraining the size relationship between the reserves of petrochemical products and the capacity of petrochemical product storage tanks; the solution unit 203 is used to solve the problem of the shipping allocation model based on the planning reference data through the The shipping allocation model solves the first shipping allocation planning data of the petrochemical products within the planning period, and the first shipping allocation planning data at least includes the matching relationship between the time period, the ship, the waybill, and the berth within the planning period; if the result of solving the first shipping allocation planning data of the petrochemical products within the planning period through the shipping allocation model is that there is no solution, then a slack variable is added to the first constraint function to obtain a second constraint function, and the first shipping allocation planning data of the petrochemical products within the planning period is solved again through the shipping allocation model; if the result of the re-solution is that there is a solution, it is determined that there is a conflict between the reserves of the petrochemical products and the capacity of the petrochemical product storage tanks.

[0190] In some embodiments of the present application, based on the above solution, the construction unit 202 is configured to: before re-solving the first shipping allocation planning data of the petrochemical product within the planning period through the shipping allocation model, further define the following objective function in the mixed integer programming model:

[0191]

[0192] Among them, R i,t represents the slack variable of petrochemical product storage tank i in time period t; I represents the set of all petrochemical product storage tanks in the planning period; T represents the set of all time periods in the planning period.

[0193] In some embodiments of the present application, based on the aforementioned scheme, the device also includes: a simulation unit, which is used to establish a domain model about ports, berths, ships, refineries, crude oil storage tanks, petrochemical product storage tanks, and refinery production plans based on the planning reference data after determining that there is a conflict between the reserves of petrochemical products and the capacity of petrochemical product storage tanks; based on the domain model and the first shipping allocation planning data, simulate the petrochemical product shipping allocation within the planning period at least once according to the target time period granularity to obtain the second shipping allocation planning data within the planning period, and the target time period granularity is smaller than the time period granularity of the first shipping allocation planning data.

[0194] In some embodiments of the present application, based on the aforementioned scheme, the simulation unit is configured to: simulate the shipping allocation of petrochemical products within the planning period according to the granularity of the target time period; if the simulation fails, record the bottleneck data that caused the simulation failure; based on the bottleneck data, adjust the domain model, and re-simulate the shipping allocation of petrochemical products within the planning period according to the granularity of the target time period until the simulation is successful.

[0195] Figure 3 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0196] It should be noted that Figure 3 The computer system 300 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0197] like Figure 3 As shown, the computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, ROM 302 and RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0198] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, etc.; an output section 307 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0199] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 309, and / or installed from a removable medium 311. When the computer program is executed by a central processing unit (CPU) 301, various functions defined in the system of the present application are executed.

[0200] It should be noted that the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, - but not limited to - an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0201] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0202] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0203] As another aspect, the present application further provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method described in the above embodiment.

[0204] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiment; or may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the method described in the above embodiment.

[0205] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being embodied by multiple modules or units.

[0206] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation methods of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation methods of the present application.

[0207] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0208] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for processing petrochemical product shipping allocation data, characterized in that: The method comprises: Acquire planning reference data for petrochemical product shipping allocation, wherein the planning parameters include at least production data, inventory data, waybill data, berth data in the port, and ship data executing the waybill of the petrochemical product; Constructing a mixed integer programming model, and defining an objective function and a constraint function for petrochemical product shipping allocation in the mixed integer programming model to obtain a shipping allocation model, wherein the constraint function includes a first constraint function for constraining the size relationship between the petrochemical product reserves and the petrochemical product storage tank capacity; Based on the planning reference data, solving the first shipping allocation planning data of the petrochemical product within the planning period through the shipping allocation model, wherein the first shipping allocation planning data at least includes the matching relationship between the time period, the ship, the waybill, and the berth within the planning period; If the result of solving the first shipping allocation planning data of the petrochemical product within the planning period by using the shipping allocation model is that there is no solution, then adding a slack variable to the first constraint function to obtain a second constraint function, and re-solving the first shipping allocation planning data of the petrochemical product within the planning period by using the shipping allocation model; If the result of the re-solution is that there is a solution, it is determined that there is a conflict between the petrochemical product reserves and the petrochemical product storage tank capacity.

2. The method according to claim 1, characterized in that Before re-solving the first shipping allocation planning data of the petrochemical product within the planning period through the shipping allocation model, the method further includes: The following objective function is also defined in the mixed integer programming model: Among them, R i,t represents the slack variable of petrochemical product storage tank i in time period t; I represents the set of all petrochemical product storage tanks in the planning period; T represents the set of all time periods in the planning period.

3. The method according to claim 1, characterized in that After determining that there is a conflict between the petrochemical product reserves and the petrochemical product storage tank capacity, the method further includes: Based on the planning reference data, establishing domain models for ports, berths, ships, refineries, crude oil storage tanks, petrochemical product storage tanks, and refinery production plans; Based on the domain model and the first shipping allocation planning data, the shipping allocation of petrochemical products within the planning period is simulated at least once according to the target time period granularity to obtain the second shipping allocation planning data within the planning period, and the target time period granularity is smaller than the time period granularity of the first shipping allocation planning data.

4. The method according to claim 3, characterized in that The simulating the petrochemical product shipping allocation within the planning period at least once according to the target time period granularity includes: Simulate the shipping allocation of petrochemical products within the planning period according to the granularity of the target period; If the simulation fails, record the bottleneck data that caused the simulation failure; Based on the bottleneck data, the domain model is adjusted, and the shipping allocation of petrochemical products within the planning period is re-simulated according to the granularity of the target period until the simulation is successful.

5. A petrochemical product shipping and dispatching data processing device, characterized in that: The device comprises: An acquisition unit, used to acquire planning reference data for petrochemical product shipping allocation, wherein the planning parameters at least include production data, inventory data, waybill data, berth data in the port, and ship data executing the waybill of the petrochemical product; A construction unit is used to construct a mixed integer programming model, and define an objective function and a constraint function for petrochemical product shipping allocation in the mixed integer programming model to obtain a shipping allocation model, wherein the constraint function includes a first constraint function for constraining the size relationship between the petrochemical product reserves and the petrochemical product storage tank capacity; A solving unit is used to solve the first shipping allocation planning data of the petrochemical product within the planning period through the shipping allocation model based on the planning reference data, wherein the first shipping allocation planning data at least includes the matching relationship between the time period, the ship, the waybill, and the berth within the planning period; if the result of solving the first shipping allocation planning data of the petrochemical product within the planning period through the shipping allocation model is that there is no solution, then a slack variable is added to the first constraint function to obtain a second constraint function, and the first shipping allocation planning data of the petrochemical product within the planning period is solved again through the shipping allocation model; if the result of the re-solution is that there is a solution, it is determined that there is a conflict between the reserves of the petrochemical product and the capacity of the petrochemical product storage tank.

6. The device according to claim 5, characterized in that The construction unit is configured as follows: Before resolving the first shipping allocation planning data of petrochemical products in the planning period through the shipping allocation model, the following objective function is further defined in the mixed integer programming model: Among them, R i,t represents the slack variable of petrochemical product storage tank i in time period t; I represents the set of all petrochemical product storage tanks in the planning period; T represents the set of all time periods in the planning period.

7. The device according to claim 5, characterized in that The device also includes: A simulation unit is used to establish, based on the planning reference data, a domain model of ports, berths, ships, refineries, crude oil storage tanks, petrochemical product storage tanks, and refinery production plans after determining that there is a conflict between the reserves of petrochemical products and the capacity of petrochemical product storage tanks; based on the domain model and the first shipping allocation planning data, simulate the petrochemical product shipping allocation within the planning period at least once according to the target time period granularity to obtain the second shipping allocation planning data within the planning period, the target time period granularity being smaller than the time period granularity of the first shipping allocation planning data.

8. The device according to claim 7, characterized in that The simulation unit is configured to: simulate the shipping allocation of petrochemical products within the planning period according to the granularity of the target period; if the simulation fails, record the bottleneck data causing the simulation failure; Based on the bottleneck data, the domain model is adjusted, and the shipping allocation of petrochemical products within the planning period is re-simulated according to the granularity of the target period until the simulation is successful.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one program code, and the at least one program code is loaded and executed by a processor to implement the operations performed by the method according to any one of claims 1 to 4.

10. An electronic device, characterized in that: The electronic device includes one or more processors and one or more memories, wherein the one or more memories store at least one program code, and the at least one program code is loaded and executed by the one or more processors to implement the operations performed by the method according to any one of claims 1 to 4.

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