Method, device, computer storage medium and terminal for inventory emergency management

Abstract

The application discloses a method, device, computer storage medium and terminal for inventory emergency management. The embodiments of the present disclosure determine product oil production and sales constraints and inventory management constraints by using product oil management related information such as node supply and demand, channel transportation, node inventory and pipeline correlation, couple inventory emergency management and production and sales to a product oil logistics daily scheduling model, consider product oil logistics planning and inventory emergency management requirements, and thus can obtain a refinery delivery execution plan, an oil depot demand execution plan, a product oil logistics plan, a pipeline scheduling plan and a node inventory plan that meet various constraint conditions, effectively improve the utilization rate of product oil demand prediction, guarantee the oil depot inventory level, achieve the economic and practical purposes of the product oil logistics plan, and improve the efficiency of the product oil inventory emergency management.

Description

Technical Field

[0001] This application relates to, but is not limited to, refined oil inventory management technology, including a method, apparatus, computer storage medium, and terminal for emergency inventory management. Background Technology

[0002] Refined oil products are vital commodities and strategic materials related to national economy and people's livelihood. Refined oil product inventory is a crucial measure to ensure market supply and stabilize prices. Related technologies generally optimize emergency management of refined oil product inventory with the lowest possible economic efficiency, while meeting basic needs. However, because this approach is based on relatively stable market demand, refined oil product inventory often remains at a low level when only economic considerations are taken into account. Therefore, significant market fluctuations or other temporary demands can lead to a shortage of refined oil product inventory, exacerbating market volatility and resulting in low efficiency in emergency inventory management. Furthermore, the significant geographical differences between the supply and demand sides of refined oil product resources make adjusting reserve plans in a short period challenging. Additionally, oil depot inventory plans are strongly coupled with refinery production and transportation plans, meaning that changes in one can have far-reaching consequences. Therefore, while focusing on emergency inventory management needs, attention must also be paid to refined oil product production and logistics.

[0003] For refined oil logistics and transportation, mathematical programming is the primary technology used. By inputting refinery delivery plans, oil depot requisition plans, and transportation route plans, conventional algorithms are used to solve a pre-constructed mathematical model for refined oil logistics optimization, resulting in a monthly refined oil logistics plan. While these mathematical models for refined oil logistics optimization are constantly evolving—for example, incorporating transportation processes such as multi-modal delivery capacity at dispatch points, multi-modal receiving capacity at collection points, and single-route transportation capacity—they still fall short of real-world engineering operations. For instance, when implementing emergency management of refined oil inventory, the optimized mathematical model only considers the upper and lower limits of inventory levels, ensuring that the inventory level meets the safety requirements of refined oil storage tanks at the time points set by the model. However, this method has two problems. First, the model's calculation time points are at the beginning and end of the month, with a total time span of more than 700 hours, which makes it impossible to track inventory and the meaning of inventory constraints is weak. Second, for models that have subdivided time points, although they can track inventory changes (the coarseness of the time span is positively correlated with the coarseness of inventory tracking), the inventory quantity is determined solely by the model with economic objectives, which cannot meet the needs of emergency inventory management, is prone to plan collapse, and has poor executability.

[0004] In conclusion, how to improve the efficiency of emergency management of refined oil inventory has become an issue that needs to be addressed. Summary of the Invention

[0005] The following is an overview of the subject matter described in detail in this application. This overview is not intended to limit the scope of the claims.

[0006] This disclosure provides a method, apparatus, computer storage medium, and terminal for emergency inventory management, which can improve the efficiency of emergency management of refined oil inventory.

[0007] This disclosure provides a method for emergency inventory management, applied to refined oil inventory management, including:

[0008] Based on the refined oil product management information of the refinery, determine the production and sales constraints and inventory management constraints of refined oil products. The refined oil product management information includes: production and operation parameters, oil depot operation parameters, transportation parameters of transportation channels, oil reserve plan information at key points, and inventory emergency plan information.

[0009] Based on the production and operation parameters, oil depot operation parameters, and transportation parameters in the relevant information on refined oil management, the refined oil production and sales constraints, inventory management constraints, oil depot oil preparation constraints, and inventory emergency plan information are determined, and a daytime scheduling model for refined oil logistics is constructed, along with a pre-set objective function.

[0010] Based on the predetermined initial plans for refined oil production and sales and the initial plans for refined oil inventory, the constructed daytime scheduling model for refined oil logistics is solved to obtain the target plans for refined oil production and sales and the target plans for refined oil inventory.

[0011] On the other hand, this disclosure also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the above-described method for emergency inventory management.

[0012] Furthermore, embodiments of this disclosure also provide a terminal, including: a memory and a processor, wherein the memory stores a computer program; wherein,

[0013] The processor is configured to execute computer programs in memory;

[0014] When the computer program is executed by the processor, it implements the inventory emergency management method described above.

[0015] Furthermore, this disclosure also provides an apparatus for emergency inventory management, comprising: a constraint determination unit, a model construction unit, and a processing unit; wherein,

[0016] The constraint unit is set as follows: Based on the refined oil management information of the refinery, the production and sales constraints and inventory management constraints of refined oil are determined. The refined oil management information includes: production operation parameters, oil depot operation parameters, transportation parameters of transportation channels, node oil preparation plan information and inventory emergency plan information.

[0017] The model building unit is set as follows: based on the production and operation parameters, oil depot operation parameters and transportation parameters in the relevant information of refined oil management, the determined refined oil production and sales constraints and inventory management constraints, oil depot oil preparation constraints and inventory emergency plan information, and the pre-set objective function, a refined oil logistics daytime scheduling model is built.

[0018] The processing unit is configured to: solve the constructed daily scheduling model for refined oil logistics based on the pre-determined initial production and sales plan information and initial inventory plan information for refined oil, and obtain the target production and sales plan information and the target inventory plan information for refined oil.

[0019] Compared with related technologies, this application is applied to refined oil inventory management, including: determining refined oil production and sales constraints and inventory management constraints based on refined oil management information from refineries. This refined oil management information includes: production operation parameters, oil depot operation parameters, transportation parameters of transportation channels, node oil reserve plan information, and inventory contingency plan information; constructing a refined oil logistics daytime scheduling model based on the determined refined oil production and sales constraints, inventory management constraints, oil depot oil reserve constraints, and inventory contingency plan information, and a pre-set objective function; and solving the constructed refined oil logistics daytime scheduling model based on pre-determined initial refined oil production and sales plan information and initial refined oil inventory plan information to obtain refined oil production and sales target plan information and refined oil inventory target plan information. This disclosed embodiment determines refined oil production and sales constraints and inventory management constraints by utilizing information related to node supply and demand, channel transportation, node inventory, and pipelines. It couples emergency inventory management and production and sales into a daytime refined oil logistics scheduling model, simultaneously considering refined oil logistics planning and emergency inventory management needs. This results in refinery delivery execution plans, oil depot requisition execution plans, oil logistics plans, pipeline scheduling plans, and node inventory plans that meet all constraints. This effectively improves the utilization rate of oil demand forecasting, ensures oil depot inventory levels, achieves the goals of economic efficiency and practicality in refined oil logistics planning, and enhances the efficiency of refined oil inventory emergency management.

[0020] 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

[0021] 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.

[0022] Figure 1 This is a flowchart illustrating an embodiment of the inventory emergency management method disclosed herein;

[0023] Figure 2 This is a structural block diagram of an inventory emergency management device according to an embodiment of this disclosure;

[0024] Figure 3 This is a structural block diagram of the terminal according to an embodiment of the present disclosure;

[0025] Figure 4 This is a flowchart illustrating a method for emergency management of refined oil inventory, as described in this embodiment.

[0026] Figure 5 This is a schematic diagram of an emergency management network for refined oil inventory according to an embodiment of this disclosure;

[0027] Figure 6a This is a schematic diagram of the refinery's inventory levels during the cycle in the basic example of the embodiments of this disclosure;

[0028] Figure 6b This is a schematic diagram of the refinery's inventory levels during the cycle in Example 1 of this embodiment of the present disclosure;

[0029] Figure 6c This is a schematic diagram of the refinery's inventory levels during the cycle in Example 2 of this embodiment of the present disclosure;

[0030] Figure 7a This is a schematic diagram of the refinery's inventory levels during the cycle in the basic example of the embodiments of this disclosure;

[0031] Figure 7b This is a schematic diagram of the refinery's inventory levels during the cycle in Example 2 of this embodiment of the present disclosure;

[0032] Figure 8a This is a schematic diagram illustrating the oil depot's inventory level during a period in the basic calculation example of this disclosure embodiment;

[0033] Figure 8b This is a schematic diagram of the oil depot's inventory during the cycle in Example 2 of this embodiment. Detailed Implementation

[0034] 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.

[0035] 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.

[0036] 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.

[0037] Figure 1 This is a flowchart of an inventory emergency management method according to an embodiment of the present disclosure, applied to refined oil inventory management, such as... Figure 1 As shown, it includes:

[0038] Step 101: Based on the refined oil management information of the refinery, determine the production and sales constraints and inventory management constraints of refined oil products; the relevant information of refined oil management includes: production operation parameters, oil depot operation parameters, transportation parameters of transportation channels, node oil preparation plan information and inventory emergency plan information;

[0039] Step 102: Using the production and operation parameters, oil depot operation parameters, and transportation parameters in the relevant information of refined oil management, the determined refined oil production and sales constraints, inventory management constraints, oil depot oil preparation constraints, and inventory emergency plan information, as well as the pre-set objective function, construct a daytime scheduling model for refined oil logistics.

[0040] Step 103: Based on the predetermined initial production and sales plan information and initial inventory plan information of refined oil products, solve the constructed daytime scheduling model of refined oil product logistics to obtain the target production and sales plan information and the target inventory plan information of refined oil products.

[0041] This disclosed embodiment determines refined oil production and sales constraints and inventory management constraints by using information related to node supply and demand, channel transportation, node inventory, and pipelines. It couples inventory emergency management and production and sales into the refined oil logistics daytime scheduling model, while taking into account the needs of refined oil logistics planning and inventory emergency management. This results in refinery delivery execution plans, oil depot demand execution plans, oil logistics plans, pipeline scheduling plans, and node inventory plans that meet all constraints. This effectively improves the utilization rate of oil demand forecasting, ensures oil depot inventory levels, achieves the goals of economic efficiency and practicality in refined oil logistics planning, and enhances the efficiency of refined oil inventory emergency management.

[0042] In one exemplary instance, step 101 of this disclosure embodiment, determining refined oil production and sales constraints based on refined oil management information of the refinery, may include:

[0043] Based on the refinery's production and operation parameters, oil depot operation parameters, and transportation parameters of transportation channels, the constraints on the production and sales of refined oil products are determined. Among them, the constraints on the production and sales of refined oil products include: node supply and demand constraints, node production and sales constraints, channel transportation constraints, pipeline-related constraints, and related constraints.

[0044] In one exemplary instance, the inventory management constraints in this disclosure include: oil depot reserve constraints and inventory contingency constraints; step 101 in this disclosure, based on refined oil product management information, determines the inventory management constraints, which may include:

[0045] Based on the oil depot's operating parameters and the oil reserve plan information at each node, the oil reserve constraints of the oil depot are determined;

[0046] Based on oil depot operating parameters and inventory contingency plan information, inventory contingency constraints are determined.

[0047] In one exemplary instance, the initial production and sales plan information for refined oil products in step 103 of this embodiment includes: refinery pre-delivery plan, oil depot pre-delivery plan, and transportation channel plan; the initial inventory plan information for refined oil products includes: node oil preparation plan information and inventory emergency plan information.

[0048] The initial production and sales plan information for refined oil products in this embodiment can be obtained from the operating system in related technologies. The initial production and sales plan information for refined oil products is a pre-plan, which refers to the pre-delivery plan submitted by the refinery and the pre-requisition plan submitted by the oil depot before the preparation of the transportation channel (logistics) plan. It is usually allowed to fluctuate within the corresponding specified range. Among them, the pre-delivery plan refers to the refinery's plan to produce various oil products every day within the set period; the pre-requisition plan refers to the oil depot's plan to demand various oil products every day within the period; the transportation channel plan refers to the channels that can be put into oil product transportation within the period, including information such as dispatch point, collection point, transportation capacity and transit time. The period of the initial production and sales plan information for refined oil products in this embodiment can be including but not limited to daily, weekly, ten-day, monthly, etc.

[0049] In one exemplary instance, the production and operation parameters in step 101 of this disclosure include, but are not limited to: maximum delivery capacity, lower storage capacity limit, upper storage capacity limit, delivery volume, production volume, and initial inventory; the oil depot operation parameters in this disclosure include, but are not limited to: oil depot receiving volume, oil depot shipping volume, oil depot shortage volume, market demand, maximum delivery capacity, upper limit of receiving capacity, lower storage capacity limit, upper storage capacity limit, and inventory; the transportation parameters in this disclosure include, but are not limited to: transportation mode, pipeline transportation, non-pipeline transportation, transportation capacity, transit time, and pipeline status. All constraints included in the refined oil production and sales constraints are related to one or more of the production and operation parameters, oil depot operation parameters, and transportation parameters of the transportation channels.

[0050] In this embodiment, nodes include refineries and oil depots. Constraints on refined oil production and sales include one or any combination of the following: node supply and demand constraints, node production and sales constraints, channel transportation constraints, pipeline-related constraints, and associated constraints; each of these constraints is briefly described below.

[0051] The node supply and demand constraints in this embodiment can be for oil depots, and must satisfy the following: within a unit time (cycle) span, the amount of shipments to the local market plus the amount of shortage should equal the demand of the local market within that unit time span; the node supply and demand constraints in this embodiment can satisfy the following formula:

[0052]

[0053] In the formula, D represents the amount of oil product o shipped from oil depot j to the local market within time window t, in cubic meters; t,j,o This represents the demand for oil product o in the local market where oil depot j is located within time window t, in cubic meters; O is the set of oil products; J is the set of oil depots.

[0054] The channel transportation constraints in this embodiment may include: output channel transportation constraints and receiving channel transportation constraints. The output channel transportation constraint may satisfy the condition that the amount of oil shipped by a refinery or oil depot per unit time via a preset transportation method should be less than the upper limit of the shipping capacity of that preset method, as expressed below:

[0055]

[0056] In the formula, Represents the maximum delivery capacity of refinery i or oil depot j via method n, in cubic meters; I is the set of refineries.

[0057] The receiving channel transportation constraint can satisfy the following condition: the amount of oil received by an oil depot per unit time through a preset transportation method should be less than the upper limit of the oil receiving capacity of that preset method, as expressed below:

[0058]

[0059] In the formula, Indicates the maximum receiving capacity of oil depot j' via method n; This refers to the set of refineries that can supply oil to oil depot j'.

[0060] In this embodiment of the disclosure, the node production and sales constraint can be that the inventory of oil depots or refineries should always be within their safety stock range, as expressed below:

[0061]

[0062]

[0063] In the formula, or The lower and upper limits of the storage capacity of refinery i (oil product o) and oil depot j (oil product o) are represented, in cubic meters; T is the set of time windows.

[0064] In this embodiment of the disclosure, the refinery inventory is related to the amount of oil shipped by the refinery to each oil depot (including pipeline injection), its own production volume, and the initial inventory, as expressed below:

[0065]

[0066] In this embodiment of the disclosure, the oil depot inventory is related to the oil depot receiving volume (including pipeline loading volume), the shipping volume (transit oil depot), and the initial inventory, as expressed below:

[0067]

[0068]

[0069] In the formula, This represents the amount of oil product o injected into the pipeline by refinery (first station) i within time window t; Δt represents the production volume of oil product o at refinery i within time window t. i,j,n / Δt j',j,n This indicates the transportation time limit from refinery i or oil depot j' to oil depot j via method n, and the number of time windows (which can be days); This represents the amount of oil product o downloaded from refinery (first station) i by oil depot (distribution station) j within time window t; This represents the set of upstream refineries (first stations) of oil depot (pipeline depot, distribution station) j.

[0070] Pipeline-related constraints in the embodiments of this disclosure include, but are not limited to, one or any combination of the following: oil batch constraints within the pipeline, backflow constraints, injection / downflow constraints, pipeline segment flow constraints, injection flow constraints, and injection and distribution constraints.

[0071] in,

[0072] The constraint on oil batches within the pipeline is as follows: the oil head transport volume of an oil batch within the pipeline per unit time is consistent with the download volume of the previous oil batch at all distribution stations. That is, the oil head transport volume of oil batch b within the pipeline during the time period t to t+1 should be consistent with the download volume of the previous batch b′ < b at all distribution stations. The expression is as follows:

[0073]

[0074] In the formula, This represents the coordinates of the oil head position of batch b injected from the first station i at time t, in cubic meters. This represents the volume of batch b' oil o downloaded by distribution station j from the first station i within the time window t, in cubic meters.

[0075] In this embodiment of the disclosure, the initial location coordinates of the oil batch inside the pipeline are known, as expressed below:

[0076]

[0077] The volume of the uninjected batch is determined by the model, as shown in the following expression:

[0078]

[0079] In the formula, This represents the location coordinates of oil batch b within the pipeline to which the first station i belongs; This represents the volume of oil product o injected from the first station i into batch b within the time window t; These represent the set of oil batches within the pipeline to which the first station i belongs (one more than the number of batches, indicating that the tail position of the oil in this batch is also known) and the set of newly injected batches, respectively.

[0080] In this embodiment of the disclosure, the backflow constraint is that the oil batch in the pipeline cannot flow back over time. That is, for oil batch b in the pipeline, backflow is not allowed over time, and the constraint satisfies the following formula:

[0081]

[0082]

[0083] In this embodiment of the disclosure, to ensure the safe operation of the injection / distribution station during oil injection / discharge, the effective working range of equipment such as flow meters and regulating valves at the injection / distribution station, as well as the limitations imposed by the oil tank on the outflow / inflow, need to be considered when formulating the scheduling plan. Therefore, the injection / discharge flow rate at the injection / distribution station must not exceed the flow limit range, forming an injection / discharge flow constraint, expressed as follows:

[0084]

[0085]

[0086] In the formula, Y represents the maximum injection traffic for the first station i, in cubic meters per hour; τ represents the time window span, in hours; i,b,o Let Y be a binary variable, representing whether batch b injected at the first station i is oil product o, and whether batch b injected at the first station i is oil product o. i,b,o =1, the batch b injected at the first station i is not oil o, Y i,b,o =0; This indicates the maximum download flow rate of distribution station j along the pipeline to which the first station i belongs, in cubic meters per hour.

[0087] In this embodiment of the disclosure, for the pipeline flow constraint, at any given time, the flow rate of the pipeline segment should be consistent with the total download volume of the downstream distribution station, as shown in the following formula:

[0088]

[0089] In the formula, This indicates the upper limit of the outflow from pipeline distribution station j to which the first station i belongs, in cubic meters per hour.

[0090] Within the same time window, the injected traffic equals the download traffic, forming an injected traffic constraint, expressed as follows:

[0091]

[0092] In this embodiment of the disclosure, the injection and distribution constraints are such that the first station or distribution station can perform corresponding operations on the batch of oil if and only if the batch belongs to a batch that is currently transiting through a station. The judgment condition is that at the beginning of the time window, the tail of the batch of oil has not yet passed through this station, as expressed below:

[0093]

[0094] At the end of this time window, the oil head of the batch has passed the station, as shown in the following expression:

[0095]

[0096] Therefore, the expression for the constraint is as follows:

[0097]

[0098]

[0099] In the formula, z i Represents the volume coordinates of the first station i (usually 0), in cubic meters; This is a binary variable, representing whether the first station i can perform an injection operation on batch b within time window t. The first station i can perform an injection operation on batch b within time window t. Within time window t, the first station i cannot perform injection operations on batch b. M represents the maximum value.

[0100] In this embodiment, the judgment condition is the same as that for injection judgment, and the expression is as follows:

[0101]

[0102]

[0103]

[0104]

[0105] In the formula, z i,j The coordinates of the station area of ​​pipeline distribution station j to which distribution station i belongs are shown, in cubic meters. This is a binary variable, representing whether pipeline distribution station j, belonging to the first station i, can perform a download operation on batch b within time window t. Within time window t, pipeline distribution station j, belonging to the first station i, can perform a download operation on batch b. Within time window t, pipeline distribution station j belonging to the first station i cannot perform download operations on batch b.

[0106] The associated constraints in this embodiment of the disclosure can be that the initial injection volume should be consistent with the refinery's pipeline shipment volume, and that the timing should correspond. These constraints can include the following:

[0107]

[0108] The amount of goods received at the pipeline distribution station should be consistent with the amount received by the oil depot via pipeline, and the timing should correspond. This can include the following constraints:

[0109]

[0110] The initial planned information for refined oil inventory in this embodiment of the disclosure can be obtained from the initial planned information for refined oil inventory of oil plants, including: node oil reserve plan information and inventory emergency plan information;

[0111] In one exemplary instance, the node oil reserve plan information in this disclosure embodiment can be in units of periods, and the inventory contingency plan information can be in units of a specific day or several days within the period of the node oil reserve plan information. The node oil reserve plan information can be the required inventory levels of various oil products in a refinery or oil depot over a relatively long period of time; the inventory contingency plan information can be the required inventory levels of a certain oil product in a refinery or oil depot over a relatively short period of time (or even a specific day). Table 1 provides examples of node oil reserve plan information and inventory contingency plan information.

[0112] node oil products Inventory planning time Planned inventory (tons) Plan type R1001 92# gasoline Full month 1000 fuel preparation plan D2006 95# gasoline Day 10 2000 emergency plan

[0113] Table 1

[0114] In this embodiment, the oil depot's oil reserve constraints correspond to the oil reserve plan. In this embodiment, for the oil depot, based on historical operating experience or forecasts, the required inventory level for each type of oil over a longer period in the next cycle can be obtained. Therefore, the following formula is used to ensure that the inventory level meets the requirements:

[0115]

[0116] In the formula, This represents the required inventory level of oil product o at time t node i, in cubic meters; RES Represents the set of nodes with oil reserve plans; O i RES Let represent the set of oil products o involved in the oil preparation plan of node i.

[0117] In this embodiment, the inventory contingency constraint corresponds to the contingency plan. The inventory contingency plan information is a temporary inventory level requirement and is highly volatile. Similar to the oil depot reserve constraint, the main difference lies in the shorter time span and stronger randomness. The expression for the inventory contingency constraint is as follows:

[0118]

[0119] In the formula, This represents the required emergency inventory level of oil product o at time t node i, expressed as: I CON T represents the set of nodes with inventory contingency plan information; i CON This represents the set of time nodes t involved in the inventory contingency plan information of node i; O i CON This represents the set of oil products o involved in the inventory emergency plan information of node i.

[0120] In one exemplary instance, embodiments of this disclosure may construct a daytime scheduling model for refined oil logistics based on neural network algorithms or deep learning methods in related technologies;

[0121] This embodiment of the disclosure, after considering constraints such as node supply and demand, channel transportation, node inventory and pipeline-related factors, takes into account multimodal transport modes, establishes a daytime scheduling model for refined oil logistics, realizes inventory tracking function while compiling logistics plans, and provides an interface for emergency inventory management.

[0122] In one exemplary embodiment of this disclosure, the objective function is a function that minimizes the total cost of refined oil logistics and emergency management, and its expression is as follows:

[0123] f = min(f1 + f2 + f3 + f4)

[0124] In the formula, f1 is the refinery logistics cost, f2 is the transit oil depot logistics cost, f3 is the inventory management cost, and f4 is the stockout penalty cost.

[0125] In this embodiment of the disclosure, refinery logistics costs include, but are not limited to: transportation costs incurred by the refinery when shipping goods to its affiliated oil depots via non-pipeline methods, and pipeline transportation costs incurred by the refinery when shipping goods to its affiliated oil depots via pipeline methods. Refinery logistics costs can be calculated using the following formula in this embodiment of the disclosure:

[0126]

[0127] In the formula, This represents the unit freight cost for refinery i to ship oil product o to oil depot j via method n, in yuan / cubic meter.

[0128] This represents the amount of oil product o shipped from refinery i to oil depot j via method n within a time window (period), expressed in cubic meters.

[0129] This represents the unit pipeline transportation fee for transporting oil product o from the first station (refinery) i to the distribution station (oil depot) j, in yuan / cubic meter.

[0130] This represents the amount of oil product o downloaded from refinery (first station) i to oil depot (distribution station) j within time window t, in cubic meters;

[0131] This represents the set of oil depots that can receive oil from oil depot j (non-pipeline); This represents the set of oil depots that can receive oil from refinery i (pipeline).

[0132] In this embodiment of the disclosure, the logistics cost of the transit oil depot includes the secondary transportation costs between all oil depots (without pipelines), which can be expressed by the following formula:

[0133]

[0134] In the formula, This represents the unit freight cost for oil depot j to ship oil product o to oil depot j' via method n, in yuan / cubic meter. This indicates the amount of oil product o sent from oil depot j (transfer oil depot) to oil depot j' via method n within time window t, in cubic meters.

[0135] In this embodiment of the disclosure, the inventory management fee includes all costs incurred by refineries and oil depots for storing oil products within a time window (cycle), as shown in the following expression:

[0136]

[0137] In the formula, This represents the unit inventory cost of oil product o for refinery i or oil depot j within each time window, expressed in yuan / cubic meter. This indicates the inventory of oil products at refinery i or oil depot j at time t, in cubic meters.

[0138] In this embodiment of the disclosure, the purpose of setting a shortage penalty fee is to allow shortages to occur at oil depots, thereby improving the model's versatility and prompting supply and demand to reach equilibrium as quickly as possible. The expression is shown below:

[0139]

[0140] In the formula, This represents the unit shortage penalty fee charged by oil depot j for oil product o, in yuan / cubic meter. This indicates the amount of oil product o in oil depot j within the time window t, in cubic meters.

[0141] In one exemplary instance, the refined oil production and sales target plan information in this embodiment of the disclosure may include: refinery delivery execution plan, oil depot demand execution plan, oil logistics plan, pipeline scheduling plan, and refined oil inventory target plan information including node inventory plans, etc.; wherein,

[0142] Refinery delivery execution plans and petroleum product demand execution plans are executable plans obtained after solving mathematical models (daily scheduling models for refined petroleum product logistics) and eliminating the impact of petroleum product shortages. The execution plans may differ slightly from the pre-planned plans.

[0143] Oil product logistics planning refers to the transportation of various oil products between refineries and oil depots. Pipeline scheduling planning refers to the batch movement, injection at injection stations, and distribution at distribution stations of pipelines involved in the logistics system during the solution cycle. Node inventory planning refers to the node inventory levels, including reserve plans and contingency plans.

[0144] In one exemplary instance, embodiments of this disclosure use the Gurobi solver (a new generation of large-scale mathematical programming optimizer) to solve the constructed daytime scheduling model for refined oil logistics, thereby obtaining refined oil production and sales target plan information and refined oil inventory target plan information.

[0145] Figure 2 This is a structural block diagram of the inventory emergency management device according to an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes: a constraint determination unit, a model construction unit, and a processing unit; wherein,

[0146] The constraint unit is set as follows: Based on the refined oil management information of the refinery, the production and sales constraints and inventory management constraints of refined oil are determined. The refined oil management information includes: production operation parameters, oil depot operation parameters, transportation parameters of transportation channels, node oil preparation plan information and inventory emergency plan information.

[0147] The model building unit is set as follows: based on the production and operation parameters, oil depot operation parameters and transportation parameters in the relevant information of refined oil management, the determined refined oil production and sales constraints and inventory management constraints, oil depot oil preparation constraints and inventory emergency plan information, and the pre-set objective function, a refined oil logistics daytime scheduling model is built.

[0148] The processing unit is configured to: solve the constructed daily scheduling model for refined oil logistics based on the pre-determined initial production and sales plan information and initial inventory plan information for refined oil, and obtain the target production and sales plan information and the target inventory plan information for refined oil.

[0149] This disclosed embodiment determines refined oil production and sales constraints and inventory management constraints by using information related to node supply and demand, channel transportation, node inventory, and pipelines. It couples inventory emergency management and production and sales into the refined oil logistics daytime scheduling model, while taking into account the needs of refined oil logistics planning and inventory emergency management. This results in refinery delivery execution plans, oil depot demand execution plans, oil logistics plans, pipeline scheduling plans, and node inventory plans that meet all constraints. This effectively improves the utilization rate of oil demand forecasting, ensures oil depot inventory levels, achieves the goals of economic efficiency and practicality in refined oil logistics planning, and enhances the efficiency of refined oil inventory emergency management.

[0150] See Figure 3 This disclosure also provides a terminal, including a memory 101 (e.g., non-volatile memory), a processor 102, and a computer program stored on the memory 101 and executable on the processor 102. When the processor 102 executes the program, it implements any possible steps of the aforementioned inventory emergency management method, which can be equivalent to the aforementioned inventory emergency management device. Of course, the processor can also be used to process other data or perform calculations. This electronic device can be a PC, server, terminal, or other similar device. Figure 3 As shown, the terminal may also include: memory 103, network interface 104, and internal bus 105. Other hardware may also be included besides these components, which will not be described in detail here.

[0151] This disclosure also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the above-described method for emergency inventory management.

[0152] This disclosure also provides a terminal, including: a memory and a processor, wherein the memory stores a computer program;

[0153] in,

[0154] The processor is configured to execute computer programs in memory;

[0155] When a computer program is executed by a processor, it implements the inventory emergency management method described above.

[0156] The following application examples briefly illustrate the embodiments of this disclosure. These application examples are only used to illustrate the embodiments of this disclosure and are not intended to limit the scope of protection of the embodiments of this disclosure.

[0157] Application Examples

[0158] Figure 4 As an embodiment of this disclosure, a flowchart of a method for emergency management of refined oil inventory is shown below. Figure 4As shown, the input parameters consist of two parts. The first part includes: refinery pre-delivery plan, oil depot pre-requisition plan, and transportation channel plan. The second part includes: node oil preparation plan information and inventory contingency plan information. The first and second parts of the input parameters are input into the refined oil logistics daytime scheduling model. The constructed node supply and demand constraints, node production and sales constraints, channel transportation constraints, pipeline-related constraints, correlation constraints, oil depot oil preparation constraints, and inventory contingency constraints are used to constrain the refined oil logistics daytime scheduling model. Through the constrained refined oil logistics daytime scheduling model, the model outputs refined oil production and sales target plan information and refined oil inventory target plan information. The refined oil production and sales target plan information includes: refinery delivery execution plan, oil depot requisition execution plan, oil logistics plan, and pipeline scheduling plan. The refined oil inventory target plan information includes node inventory plans.

[0159] Figure 5 This is a schematic diagram of an emergency management network for refined oil inventory according to an embodiment of this disclosure, as shown below. Figure 5 As shown, this refined oil emergency management network includes 8 refineries (R1-R8), 19 oil depots (D1-D19), and 1 refined oil pipeline. The pipeline starts at R4 and ends at D19, with an intermediate injection station (refinery) at R7. The entire pipeline has 8 distribution stations (D11, D13, D14-D19), including the terminal station. Assume that this refined oil emergency management system transports 5 types of oil: 0# diesel, -35# diesel, 92# gasoline, 95# gasoline, and 98# gasoline. The R4-D19 pipeline only transports 0# diesel and 92# gasoline.

[0160] The pre-delivery plans for refinery R1 to R8 are shown in Table 2, and the pre-request plans for oil depots D1 to D19 are shown in Table 3. Nodes with no delivery or request plans within this cycle (a total of 28 days) have been omitted from the tables.

[0161] refinery oil products Delivery quantity (tons) refinery oil products Delivery quantity (tons) R1 0# Diesel 71000 R3 98# gasoline 700 R1 -35# Diesel 1000 R4 0# Diesel 70000 R1 92# gasoline 38000 R5 0# Diesel 113300 R1 95# gasoline 9000 R5 -35# Diesel 4000 R2 0# Diesel 35000 R5 92# gasoline 41000 R2 -35# Diesel 5000 R5 95# gasoline 26000 R2 92# gasoline 20000 R6 92# gasoline 6700 R2 95# gasoline 4000 R6 95# gasoline 5300 R3 0# Diesel 91700 R7 0# Diesel 25000 R3 92# gasoline 80000 R8 92# gasoline 23300 R3 95# gasoline 14300 R8 95# gasoline 4700

[0162] Table 2

[0163] oil depot oil products Quantity required (tons) oil depot oil products Quantity required (tons) D1 0# Diesel 30000 D8 95# gasoline 12000 D2 0# Diesel 10000 D8 98# gasoline 700 D3 0# Diesel 35000 D9 0# Diesel 61000 D3 -35# Diesel 1000 D9 -35# Diesel 4000 D3 92# gasoline 18000 D9 92# gasoline 22000 D3 95# gasoline 5000 D9 95# gasoline 13300 D4 0# Diesel 30000 D10 0# Diesel 20000 D4 92# gasoline 20000 D11 0# Diesel 45000 D4 95# gasoline 4000 D11 92# gasoline 10000 D5 0# Diesel 30000 D12 0# Diesel 10000 D5 92# gasoline 25000 D13 95# gasoline 3000 D5 95# gasoline 5000 D14 0# Diesel 10000 D6 92# gasoline 20000 D14 92# gasoline 2000 D6 95# gasoline 10000 D14 95# gasoline 1000 D7 0# Diesel 35000 D15 0# Diesel 15000 D7 -35# Diesel 5000 D15 92# gasoline 15000 D7 92# gasoline 20000 D15 95# gasoline 2000 D7 95# gasoline 4000 D17 0# Diesel 25000 D8 0# Diesel 50000 D17 92# gasoline 13000 D8 92# gasoline 44000 D17 95# gasoline 4000

[0164] Table 3

[0165] In this embodiment of the disclosure, three calculation cases are set up, including a basic calculation case, calculation case 1, and calculation case 2. The basic calculation case is a calculation case that does not consider contingencies in the relevant technology (Tables 1 and 2). Calculation case 1 only involves the oil preparation plan of one refinery, that is, R4 ensures that the inventory level of 0# diesel, 92# gasoline, and 95# gasoline is not less than 1,000 tons on any day in this cycle. Calculation case 2 adds the oil preparation plan of R1 and the contingency plan of D5 on the basis of calculation case 1. D5 requires that the inventory of 95# gasoline is not less than 500 tons on the 10th and 20th days, as shown in Table 4.

[0166]

[0167] Table 4

[0168] In this embodiment of the disclosure, based on Tables 2 and 3, the parameter values ​​involved in the basic calculation examples are input into the daily scheduling model of refined oil logistics without inventory management constraints. Based on the Gurobi solver, the daily scheduling model of refined oil logistics without inventory management constraints is solved. Based on Tables 2, 3, and 4, the parameter values ​​involved in Calculation Example 1 and Calculation Example 2 are input into the daily scheduling model of refined oil logistics, respectively. Based on the Gurobi solver, the daily scheduling model (mathematical model) of refined oil logistics is solved to obtain the refinery delivery execution plan, oil depot demand execution plan, oil logistics plan, pipeline scheduling plan, and node inventory plan. The solution results mainly show the inventory changes (a total of 28 days).

[0169] Taking Refinery R4 as an example, Figure 6a This is a schematic diagram of the refinery's inventory levels during the cycle in the basic example of the embodiments of this disclosure; Figure 6b This is a schematic diagram of the refinery's inventory levels during the cycle in Example 1 of this embodiment of the present disclosure, as shown below. Figure 6b As shown, between time points 2 and 29, inventory increased significantly, meeting the requirements for oil reserves (≥1000 tons); Figure 6c This is a schematic diagram of the refinery's inventory levels during the cycle in Example 2 of this embodiment of the present disclosure, as shown below. Figure 6c As shown, between time points 2 and 29, inventory levels increased significantly, meeting the requirements for oil reserves; taking refinery R1 as an example, Figure 7a This is a schematic diagram of the refinery's inventory levels during the cycle in the basic example of the embodiments of this disclosure; Figure 7b This is a schematic diagram of the refinery's inventory levels during the cycle in Example 2 of this embodiment of the present disclosure, as shown below. Figure 7b As shown, for the entire month (28 days, from time points 2 to 29), the reserve of 0# diesel and 92# gasoline must meet the requirement of no less than 2000 tons, the reserve of -35# diesel must meet the requirement of no less than 200 tons, and the reserve of 95# gasoline must meet the requirement of 500 tons; taking oil depot D5 as an example, Figure 8a This is a schematic diagram illustrating the oil depot's inventory level during a period in the basic calculation example of this disclosure embodiment; Figure 8b This is a schematic diagram illustrating the oil depot's inventory level during a period in Example 2 of this embodiment. Figure 8b As shown, around time points 11 (day 10) and 21 (day 20), the inventory increased significantly, meeting the requirements for oil reserves.

[0170] See Figures 6a-6c For examples 7a-7b and 8a-8b, compared to the basic examples of related technologies, the results of examples 1 and 2 both meet the requirements for oil reserves or emergency needs. For example, the monthly requirement is that the inventory level of 0# diesel, 92# gasoline and 95# gasoline of R4 should not be less than 1,000 tons; the monthly requirement is that the inventory level of 0# diesel and 92# gasoline of R1 should not be less than 2,000 tons, -35# diesel should not be less than 200 tons and 95# gasoline should not be less than 500 tons; the emergency quantity of 95# gasoline of D5 should reach 500 tons on the 10th day (the 11th time node in the figure) and the 20th day (the 21st time node in the figure).

[0171] This disclosed embodiment improves the practicality of logistics planning by comprehensively considering refined oil logistics optimization and inventory management. It comprises five main parts: a refined oil logistics daytime scheduling model considering multimodal transport, inventory management constraints, and output results. The core parts are the refined oil logistics daytime scheduling model considering multimodal transport and inventory management constraints. The outputs include refinery delivery execution plans, oil depot requisition execution plans, oil product logistics plans, pipeline scheduling plans, and node inventory plans. This addresses the long-standing uneconomical phenomena and poor executability of logistics plans caused by separating logistics optimization and inventory management, effectively meeting the oil depot's oil reserve needs and emergency inventory requirements. This disclosure coupling inventory management constraints to a daytime scheduling model for refined oil logistics that considers multimodal transport, optimizes logistics while simultaneously considering node oil preparation plans and inventory contingency plans. This effectively reduces manual intervention, improves the practicality of logistics planning, lowers the economic expenditure of the logistics system, and enhances emergency management efficiency. The refined oil inventory emergency management method based on logistics optimization utilizes a daytime scheduling model for refined oil logistics that considers multimodal transport. This model aims to minimize oil logistics costs, inventory management costs, and shortage penalty fees, considering constraints such as node supply and demand, channel transportation, node inventory, and pipeline-related factors, as well as inventory management constraints including oil depot preparation constraints and emergency constraints. Based on logistics optimization, the refined oil inventory emergency management method, after inputting refinery pre-delivery plans, oil depot pre-requisition plans, transportation channel plans, node oil preparation plans, and inventory contingency plans, can obtain refinery delivery execution plans, oil depot requisition execution plans, oil logistics plans, pipeline scheduling plans, and node inventory plans that meet all constraints.

[0172] 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 emergency inventory management, applied to refined oil inventory management, characterized in that, include: Based on the refined oil product management information of the refinery, determine the production and sales constraints and inventory management constraints of refined oil products. The refined oil product management information includes: production and operation parameters, oil depot operation parameters, transportation parameters of transportation channels, oil reserve plan information at key points, and inventory emergency plan information. Based on the production and operation parameters, oil depot operation parameters, and transportation parameters in the relevant information on refined oil management, the production and sales constraints and inventory management constraints of refined oil are determined, and a pre-set objective function is used to construct a daytime scheduling model for refined oil logistics. Based on the predetermined initial plans for refined oil production and sales and the initial plans for refined oil inventory, the constructed daytime scheduling model for refined oil logistics is solved to obtain the target plans for refined oil production and sales and the target plans for refined oil inventory. The step of determining refined oil production and sales constraints and inventory management constraints based on refined oil management information includes: determining the refined oil production and sales constraints based on the production operation parameters, oil depot operation parameters, and transportation parameters of the transportation channels in the refined oil management information, wherein the refined oil production and sales constraints include one or any combination of the following: node supply and demand constraints, node production and sales constraints, channel transportation constraints, pipeline-related constraints, and associated constraints; and determining the inventory management constraints based on the oil depot operation parameters, node oil reserve plan information, and inventory contingency plan information in the refined oil management information, wherein the inventory management constraints include: oil depot oil reserves. Constraints and inventory contingency constraints, wherein determining inventory management constraints includes: determining the oil depot's oil reserve constraints based on the oil depot's operating parameters and the node oil reserve plan information; determining the inventory contingency constraints based on the oil depot's operating parameters and the inventory contingency plan information; when the refined oil production and sales constraints include the channel transportation constraints, the channel transportation constraints include output channel transportation constraints and receiving channel transportation constraints, wherein the output channel transportation constraint is: for a refinery or oil depot, the amount of oil products it sends out per unit time through a preset transportation method should be less than the upper limit of the oil delivery capacity of that preset method; the receiving channel transportation constraint is: for an oil depot, the amount of oil products it sends out per unit time through a preset transportation method should be less than the upper limit of the oil delivery capacity of that preset method; the receiving channel transportation constraint is: for an oil depot, the amount of oil products it sends out per unit time through a preset transportation method should be less than the upper limit of the oil delivery capacity of that preset method. The amount of oil received is less than the upper limit of the oil receiving capacity of the preset method; when the refined oil production and sales constraints include the associated constraints, the associated constraints include: the injection volume at the first station should be consistent with the amount shipped by the refinery via pipeline, and the time should correspond; and the unloading volume at the pipeline distribution station should be consistent with the amount received by the oil depot via pipeline, and the time should correspond; when the refined oil production and sales constraints include the pipeline-related constraints, the pipeline-related constraints include: oil batch constraints within the pipeline, backflow constraints, injection / unloading flow constraints, pipeline segment flow constraints, injection flow constraints, and injection and distribution constraints; wherein, the oil batch constraints within the pipeline are the oil head transport volume of the oil batch within the pipeline per unit time and the total oil head transport volume of all distribution stations. The download volume of the oil batch in the previous pipeline is consistent; the backflow constraint is that the oil batch in the pipeline does not backflow over time; the injection / download flow constraint is that the injection flow rate of the injection station is less than or equal to the flow limit range, and the download flow rate of the distribution station is less than or equal to the flow limit range; the pipeline segment flow constraint is that at any given time, the flow rate of the pipeline segment should be consistent with the total download volume of the downstream distribution station; the injection flow constraint is that the injection flow rate is equal to the download flow rate; the injection and distribution constraints are that the first station or distribution station can perform corresponding operations on the oil batch if and only if the batch belongs to the batch that is currently passing through the station; the objective function is the function that minimizes the total cost of refined oil logistics and emergency management.

2. The method according to claim 1, characterized in that, When the refined oil production and sales constraints include the node supply and demand constraints, the node supply and demand constraints include: The amount of oil shipped from the oil depot to the local market within a given time period, plus the amount of stockouts, equals the demand in that local market within that time period.

3. The method according to claim 1, characterized in that, When the refined oil production and sales constraints include the node production and sales constraints, the node production and sales constraints include: Oil depots or refineries always maintain their corresponding safety stock levels.

4. The method according to any one of claims 1 to 3, characterized in that, The objective function is: The expression is: In the formula, For refinery logistics costs, For the transit oil depot logistics costs, For inventory management fees, Penalty fee for stockouts.

5. A computer storage medium storing a computer program that, when executed by a processor, implements the method for emergency inventory management as described in any one of claims 1 to 4.

6. A terminal, comprising: A memory and a processor, wherein the memory stores a computer program; wherein, The processor is configured to execute computer programs in memory; When the computer program is executed by the processor, it implements the method for emergency inventory management as described in any one of claims 1 to 4.

7. An inventory emergency management device, comprising: Define constraint units, construct model units, and process units; among them, The constraint unit is set as follows: Based on the refined oil management information of the refinery, the production and sales constraints and inventory management constraints of refined oil are determined. The refined oil management information includes: production operation parameters, oil depot operation parameters, transportation parameters of transportation channels, node oil preparation plan information and inventory emergency plan information. The model building unit is set as follows: based on the production and operation parameters, oil depot operation parameters and transportation parameters in the relevant information of refined oil management, the determined refined oil production and sales constraints and inventory management constraints, oil depot oil preparation constraints and inventory emergency plan information, and the pre-set objective function, a refined oil logistics daytime scheduling model is built. The processing unit is set to: solve the constructed daytime scheduling model of refined oil logistics based on the predetermined initial production and sales plan information and initial inventory plan information of refined oil, and obtain the target production and sales plan information and the target inventory plan information of refined oil. The step of determining refined oil production and sales constraints and inventory management constraints based on refined oil management information includes: determining the refined oil production and sales constraints based on the production operation parameters, oil depot operation parameters, and transportation parameters of the transportation channels in the refined oil management information, wherein the refined oil production and sales constraints include one or any combination of the following: node supply and demand constraints, node production and sales constraints, channel transportation constraints, pipeline-related constraints, and associated constraints; and determining the inventory management constraints based on the oil depot operation parameters, node oil reserve plan information, and inventory contingency plan information in the refined oil management information, wherein the inventory management constraints include: oil depot oil reserves. Constraints and inventory contingency constraints, wherein determining inventory management constraints includes: determining the oil depot's oil reserve constraints based on the oil depot's operating parameters and the node oil reserve plan information; determining the inventory contingency constraints based on the oil depot's operating parameters and the inventory contingency plan information; when the refined oil production and sales constraints include the channel transportation constraints, the channel transportation constraints include output channel transportation constraints and receiving channel transportation constraints, wherein the output channel transportation constraint is: for a refinery or oil depot, the amount of oil products it sends out per unit time through a preset transportation method should be less than the upper limit of the oil delivery capacity of that preset method; the receiving channel transportation constraint is: for an oil depot, the amount of oil products it sends out per unit time through a preset transportation method should be less than the upper limit of the oil delivery capacity of that preset method; the receiving channel transportation constraint is: for an oil depot, the amount of oil products it sends out per unit time through a preset transportation method should be less than the upper limit of the oil delivery capacity of that preset method. The amount of oil received is less than the upper limit of the oil receiving capacity of the preset method; when the refined oil production and sales constraints include the associated constraints, the associated constraints include: the injection volume at the first station should be consistent with the amount shipped by the refinery via pipeline, and the time should correspond; and the unloading volume at the pipeline distribution station should be consistent with the amount received by the oil depot via pipeline, and the time should correspond; when the refined oil production and sales constraints include the pipeline-related constraints, the pipeline-related constraints include: oil batch constraints within the pipeline, backflow constraints, injection / unloading flow constraints, pipeline segment flow constraints, injection flow constraints, and injection and distribution constraints; wherein, the oil batch constraints within the pipeline are the oil head transport volume of the oil batch within the pipeline per unit time and the total oil head transport volume of all distribution stations. The download volume of the oil batch in the previous pipeline is consistent; the backflow constraint is that the oil batch in the pipeline does not backflow over time; the injection / download flow constraint is that the injection flow rate of the injection station is less than or equal to the flow limit range, and the download flow rate of the distribution station is less than or equal to the flow limit range; the pipeline segment flow constraint is that at any given time, the flow rate of the pipeline segment should be consistent with the total download volume of the downstream distribution station; the injection flow constraint is that the injection flow rate is equal to the download flow rate; the injection and distribution constraints are that the first station or distribution station can perform corresponding operations on the oil batch if and only if the batch belongs to the batch that is currently passing through the station; the objective function is the function that minimizes the total cost of refined oil logistics and emergency management.

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