Method and device for processing transportation information, and method and device for constructing transportation model

Abstract

The invention discloses a method and a device for processing transportation information, and a method and a device for constructing a transportation model.According to the embodiment of the invention, an established logistics sub-model and a pipeline scheduling sub-model are associated and coupled through a transportation connection relation and an association constraint condition; the obtained logistics optimization model can consider the product transportation pipeline and the logistics path at the same time, the transportation plan information of the to-be-transported product is obtained through the logistics optimization model, and technical support is provided for improving the product transportation efficiency.

Description

Technical Field

[0001] The present application relates to but is not limited to logistics and transportation technology, and particularly to a method and device for processing transportation information, and a method and device for constructing a transportation model. Background Art

[0002] As the demand for oil products increases year by year, the scale of refined oil transportation is getting larger and larger, and the transportation cost of oil products is increasing year by year. How refined oil sales companies can reasonably formulate logistics plans and save transportation costs has become an important means for them to improve their competitiveness.

[0003] The refined oil pipeline network refers to the pipeline network that transports refined oil from refineries to gas stations. According to the transportation method, refined oil pipelines can be divided into sequential pipelines and batch pipelines. Sequential pipelines refer to the transportation of different types of refined oil in a certain order, while batch pipelines transport different types of refined oil in batches. The pipeline scheduling model in related technologies generally considers the calculation of a single pipeline or multiple unrelated pipelines.

[0004] The scheduling plan for refined oil pipelines in related technologies is formulated on a relatively small scale, and the resulting pipeline scheduling plan generally considers a single pipeline or multiple unrelated pipelines, which are independent pipeline operation methods; however, pipeline networks, including the western refined oil pipeline network, have multiple pipelines, transit oil depots at pipeline connections, and multiple injection points in a single pipeline; how to establish a transportation pipeline that can be applied to the western refined oil pipeline network, formulate a transportation plan, and improve the transportation efficiency of refined oil has become a problem to be solved. Summary of the invention

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

[0006] The embodiments of the present disclosure provide a method and device for processing transportation information, and a method and device for constructing a transportation model, which can improve the transportation efficiency of refined oil.

[0007] The present disclosure provides a method for processing transportation information, including:

[0008] According to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported;

[0009] According to the predetermined product transportation pipeline information and the second constraint condition, a pipeline scheduling sub-model is established, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported;

[0010] According to the predetermined transport connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model, and the transport connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception;

[0011] The basic information and operation information of the products to be transported are calculated through the logistics optimization model to obtain the transportation plan information of the products to be transported;

[0012] The pipeline for transporting the product includes more than one pipeline having the following characteristics: there is a transfer depot at the connection of the pipeline and / or there are more than two injection stations in a single pipeline.

[0013] On the other hand, an embodiment of the present disclosure further provides a computer storage medium, in which a computer program is stored. When the computer program is executed by a processor, the method for processing transportation information or the method for constructing a transportation model is implemented.

[0014] In another aspect, an embodiment of the present disclosure further provides a terminal, comprising: a memory and a processor, wherein the memory stores a computer program; wherein:

[0015] The processor is configured to execute the computer program in the memory;

[0016] When the computer program is executed by the processor, the method for processing transportation information or the method for constructing a transportation model as described above is implemented.

[0017] In another aspect, the embodiment of the present disclosure further provides a device for processing transportation information, including: a logistics module, a pipeline scheduling module, a correlation module and a processing module; wherein,

[0018] The logistics module is set up as follows: according to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported;

[0019] The pipeline scheduling module is configured to: establish a pipeline scheduling sub-model according to the predetermined pipeline information of the product transportation and the second constraint condition, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported;

[0020] The association module is set as follows: according to the predetermined transportation connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transportation connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception;

[0021] The processing module is configured to: calculate the basic information and operation information of the product to be transported through a logistics optimization model to obtain the transportation plan information of the product to be transported;

[0022] The pipeline for transporting the product includes more than one pipeline having the following characteristics: there is a transfer depot at the connection of the pipeline and / or there are more than two injection stations in a single pipeline.

[0023] In another aspect, the embodiment of the present disclosure further provides a device for constructing a transportation model, including: a logistics module, a pipeline scheduling module, a correlation module and a processing module; wherein:

[0024] Logistics module, pipeline scheduling module, association module and processing module; among them,

[0025] The logistics module is set up as follows: according to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported;

[0026] The pipeline scheduling module is configured to: establish a pipeline scheduling sub-model according to the predetermined pipeline information of the product transportation and the second constraint condition, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported;

[0027] The association module is set as follows: according to the predetermined transportation connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transportation connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception;

[0028] The pipeline for transporting the product includes a pipeline having the following characteristics: there is a transfer warehouse at the connection point of the pipeline, and / or there are multiple injection stations in a single pipeline.

[0029] Compared with the related technologies, the embodiments of the present disclosure establish a logistics sub-model and a pipeline scheduling sub-model, and couple them through transportation connection relationships and associated constraints. The obtained logistics optimization model can simultaneously consider the pipeline and logistics path of product transportation, and obtain the transportation plan information of the products to be transported through the calculation of the logistics optimization model, thereby providing technical support for improving product transportation efficiency.

[0030] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by implementing the present application. Other advantages of the present application can be realized and obtained by the schemes described in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings are used to provide an understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0032] Figure 1A flowchart of a method for processing transportation information according to an embodiment of the present disclosure;

[0033] Figure 2 A flow chart of a method for constructing a transportation model for an embodiment of the present disclosure;

[0034] Figure 3 A structural block diagram of a device for processing transportation information according to an embodiment of the present disclosure;

[0035] Figure 4 The present invention is a method flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The present application describes multiple embodiments, but the description is exemplary rather than restrictive, and it is obvious to those skilled in the art that there may be more embodiments and implementations within the scope of the embodiments described in the present application. Although many possible feature combinations are shown in the drawings and discussed in the specific embodiments, 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 any other feature or element in any other embodiment, or may replace any other feature or element in any other embodiment.

[0037] The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in the present application may also be combined with any conventional features or elements to form a unique invention scheme defined by the claims. Any features or elements of any embodiment may also be combined with features or elements from other invention schemes to form another unique invention scheme defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in the present application may be implemented individually or in any appropriate combination. Therefore, except for the limitations made according to the attached claims and their equivalents, the embodiments are not subject to other restrictions. In addition, various modifications and changes may be made within the scope of protection of the attached claims.

[0038] In addition, when describing representative embodiments, the specification may have presented the method and / or process as a specific sequence of steps. However, to the extent that the method or process does not rely on the specific order of the steps described herein, the method or process should not be limited to the steps of the specific order described. As will be understood by those of ordinary skill in the art, other sequences of steps are also possible. Therefore, the specific sequence of the steps set forth in the specification should not be interpreted as a limitation to the claims. In addition, the claims for the method and / or process should not be limited to the steps of performing them in the order written, and those skilled in the art can easily understand that these sequences can be changed and still remain within the spirit and scope of the embodiments of the present application.

[0039] In the related technology, the pipeline scheduling model only considers the calculation of a single pipeline or multiple unrelated pipelines. It is impossible to formulate a joint scheduling plan for the situation where there are transfer stations for multiple pipelines, and it is impossible to use a system with multiple pipelines, multiple injection points, and multiple transportation modes such as the Western Finished Oil Pipeline Network.

[0040] Figure 1 A flowchart of a method for processing transportation information according to an embodiment of the present disclosure is shown in FIG. Figure 1 As shown, including:

[0041] Step 101: Establish a logistics sub-model based on the predetermined logistics information of product transportation and the first constraint condition, where the logistics sub-model is used to determine the logistics path of the product transportation;

[0042] Step 102: Establish a pipeline scheduling sub-model based on the predetermined product transportation pipeline information and the second constraint condition, where the pipeline scheduling sub-model is used to determine the pipeline to be used when transporting the product;

[0043] In an exemplary instance, the logistics information and pipeline information in the embodiments of the present disclosure can be directly obtained from the relevant systems of product transportation by referring to relevant technologies; the logistics information in the embodiments of the present disclosure may include what is well known to those skilled in the art: the transportation methods of product transportation and the transportation routes, transportation times, and transportation product quantities corresponding to each transportation method; the pipeline information in the embodiments of the present disclosure may include: one or more pipelines in the product transportation network, and for each pipeline, whether there is an injection station for each pipeline at the connection of the pipeline.

[0044] In an exemplary embodiment, the embodiment of the present disclosure can be based on an operations optimization algorithm, refer to related technologies, establish the above-mentioned logistics sub-model based on logistics information and the first constraint condition, and establish a pipeline scheduling sub-model based on pipeline information and the second constraint condition. The operations optimization algorithm is a mathematical method used to find the optimal solution or optimal solution set under given constraints; it has a wide range of applications in various fields, such as logistics scheduling, vehicle path planning, facility site selection, network optimization, etc.; the operations optimization algorithms in related technologies include: 1. Mathematical programming algorithms: including linear programming, integer programming, nonlinear programming, etc. These algorithms can solve the optimal solution through mathematical models. Optimal solution; 2. Heuristic algorithm: including genetic algorithm, particle swarm algorithm, simulated annealing algorithm, etc. These algorithms search for the optimal solution by simulating the evolution of nature, the principles of physics, etc.; 3. Branch and bound algorithm: This algorithm decomposes the problem into several sub-problems, and then gradually solves the sub-problems to finally get the optimal solution; 4. Dynamic programming algorithm: This algorithm decomposes the problem into several sub-problems, and then gradually solves the sub-problems to finally get the optimal solution; 5. Greedy algorithm: This algorithm selects the current optimal solution at each step and finally gets the global optimal solution; Through operations research optimization algorithms, the optimal solution or optimal solution set can be found under various constraints.

[0045] Step 103: According to the predetermined transport connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transport connection relationship includes the connection relationship between logistics transportation and pipeline output and pipeline reception.

[0046] Step 104: The basic information and operation information of the products to be transported are calculated through a logistics optimization model to obtain transportation plan information of the products to be transported;

[0047] Among them, the pipeline for product transportation includes more than one pipeline with the following characteristics: there is a transit warehouse at the connection of the pipeline and / or there are more than two injection stations in a single pipeline.

[0048] The disclosed embodiment will establish a logistics sub-model and a pipeline scheduling sub-model, and couple them through transportation connection relationships and associated constraints. The obtained logistics optimization model can simultaneously consider the pipeline and logistics path of product transportation. The transportation plan information of the products to be transported is obtained through the calculation of the logistics optimization model, which provides technical support for improving product transportation efficiency.

[0049] In an exemplary instance, the product in the embodiment of the present disclosure includes refined oil, and accordingly, the pipeline in the embodiment of the present disclosure may include a refined oil pipeline; the refined oil pipeline in the embodiment of the present disclosure may include the management of an existing network in the relevant technology, such as a pipeline in the western refined oil pipeline network.

[0050] In an exemplary embodiment, before the basic information and operation information of the product to be transported are calculated by the logistics optimization model, the method of the embodiment of the present disclosure further includes:

[0051] Get basic and operational information.

[0052] When formulating a product transportation plan, the disclosed embodiment needs to obtain basic information and operation information of the product to be transported; the basic information is used for calculation by the logistics optimization model, and the operation information is used to formulate a product transportation plan with the logistics optimization model. Bringing the above basic information and operation information into the logistics optimization model to formulate a product transportation plan can improve the transportation efficiency of the product to be transported.

[0053] In an exemplary embodiment, the basic information in the embodiment of the present disclosure includes the following information or any combination of information of the product to be transported:

[0054] Product information, inventory information, pipeline station information, transportation capacity, place of shipment, destination, transportation cost and transit time.

[0055] The basic information of the disclosed embodiment is mainly used for calculation in the logistics optimization model; the product information in the basic information may include the type, density and color of the product; the inventory information may include the name of the transit warehouse, the upper and lower limits of the inventory, etc.; the pipeline station information may include the station mileage elevation, the upper and lower limits of the distribution volume, etc.; the transportation capacity may include the transportation capacity of various transportation modes; the transportation cost may include the transportation cost of various transportation modes; the transit time may include the transit time of various transportation modes. The disclosed embodiment can calculate the relevant data of the product to be transported in the product transportation plan by bringing the basic information into the logistics optimization model.

[0056] In an exemplary embodiment, the operation information in the embodiment of the present disclosure includes one or any combination of the following information:

[0057] Initial state of pipeline, initial inventory and supply plan.

[0058] The operation information of the disclosed embodiment is used to formulate a transportation plan in the logistics optimization model. The initial state of the pipeline in the operation information may include the batch number and the oil head volume coordinates, etc.; the initial inventory may include the initial inventory of the products in each product library; the supply plan may include the supply of the inventory products at the departure point of each product and the product demand supply and demand at the destination. The disclosed embodiment can obtain each step in the product transportation plan by bringing the operation information into the logistics optimization model.

[0059] In an exemplary embodiment, the transport connection relationship in the embodiment of the present disclosure includes the following information:

[0060] Pipelines used to receive products after they have been transported through logistics;

[0061] Logistics used to transport products after they are output from the pipeline.

[0062] The disclosed embodiment establishes a connection between the logistics nodes of the logistics sub-model and the pipeline nodes in the pipeline scheduling sub-model through the transport connection relationship, and combines the associated constraints to achieve the associated coupling of the logistics sub-model and the pipeline scheduling sub-model, thereby obtaining the above-mentioned logistics optimization model.

[0063] In an exemplary embodiment, the first constraint condition in the embodiment of the present disclosure includes:

[0064] Transportation capacity constraints, supply and demand balance constraints, and inventory constraints;

[0065] Among them, the transportation capacity constraints include: for each mode of transportation, the amount of products sent / received through the current mode of transportation per unit time is less than or equal to the upper limit of the amount of products sent / received through this mode of transportation; the supply and demand balance constraints include: the shipment volume of products sent to a region per unit time plus the shortage of products is equal to the demand for products in the region per unit time; the inventory constraints include: the inventory of products is within the safety stock range.

[0066] In the disclosed embodiment, the process of obtaining the logistics optimization model involves constraints such as the first constraint, the second constraint and the associated constraint. Constraints refer to restrictions or requirements imposed on certain variables or behaviors in a certain problem or scenario.

[0067] In the embodiment of the present disclosure, the transport capacity constraint in the first constraint condition refers to the maximum transport volume that can be completed within a certain period of time by transport modes such as railways, water transport, roads and pipelines; by constraining the transport capacity in the logistics sub-model, the transport plan information finally obtained can be implemented in life, avoiding the situation where the transport plan cannot be implemented due to exceeding the maximum transport volume. The transport capacity constraint in the embodiment of the present disclosure includes a receiving capacity constraint and a shipping capacity constraint; wherein, the receiving capacity constraint is that the amount of products received by a certain transport mode in a unit time should be less than the upper limit of the amount of products received by the transport mode; the shipping capacity constraint is that the amount of products sent by a certain transport mode in a unit time should be less than the upper limit of the amount of products sent by the transport mode. The supply and demand balance constraint means that the supply should be equal to the demand. By constraining the supply and demand balance of the logistics sub-model, it can be limited that in the product transportation plan formulated by the logistics sub-model, the amount of products shipped to a certain region in a unit time plus the shortage of the region in a unit time should be equal to the demand of the region in the unit time, thereby ensuring the reasonable quantity of products in the region, avoiding the situation where the products are sold out or the inventory is too much. Inventory constraints refer to the materials stored in the warehouse; by constraining the logistics sub-model, it is possible to limit the inventory of products in the product transportation plan formulated by the logistics sub-model to always be within the safety inventory range, avoiding safety issues caused by excessive inventory. The disclosed embodiment constrains the established logistics sub-model through transportation capacity, supply and demand balance, and inventory, ensuring that the product transportation plan contained in the obtained product transportation information is reasonable and can be implemented in production operations.

[0068] In an exemplary embodiment, the second constraint condition in the embodiment of the present disclosure includes:

[0069] Batch constraints, flow limit constraints, and injection and distribution constraints;

[0070] Among them, the batch constraint is: for each batch, the oil head movement of the batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the flow limit constraint is: the download amount of the pipeline distribution station is within the download amount limit range of the distribution station; the injection and distribution constraints are: if and only if the batch belongs to the batch that is passing through the station, the first station or distribution station of the pipeline can perform corresponding operations on the products of the batch; among them, the batch constraints include batch tracking and position constraints; batch tracking is that the oil head movement of a batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the position constraint is: for each batch, as time increases, the position coordinates of the batch products in the pipeline at the next moment are greater than or equal to their position coordinates in the pipeline at the previous moment.

[0071] The disclosed embodiment imposes batch constraints on the pipeline scheduling submodel so that the products passing through the pipeline will not be reduced; for a certain batch, position constraints are used to avoid the phenomenon of product backflow over time. In order to ensure the safe operation of the sub-transmission station when downloading products, when formulating the product transportation plan through the pipeline scheduling submodel, the effective working range of the sub-transmission station flowmeter, regulating valve and other equipment and the restriction conditions of the oil tank on the inlet flow must be considered. Therefore, the disclosed embodiment imposes flow restriction constraints on the pipeline scheduling submodel, that is, it is limited that in the product transportation plan formulated by the pipeline scheduling submodel, the download volume of the sub-transmission station cannot exceed the download volume restriction range. The disclosed embodiment imposes injection and distribution constraints on the pipeline scheduling submodel, that is, it is limited that in the product transportation plan formulated by the pipeline scheduling submodel, the first station or sub-transmission station of the pipeline can perform corresponding operations on it only when the batch belongs to the batch that is passing through the station, that is, only when the batch is in the state of passing through the station, the first station or sub-transmission station can operate on the batch. The disclosed embodiment performs batch constraints, flow limit constraints, and injection and distribution constraints on the pipeline scheduling submodel, so that the product transportation plan formulated by the pipeline scheduling submodel can formulate a reasonable product transportation plan in a system with multiple pipelines and multiple injection points.

[0072] In an exemplary embodiment, the association constraint conditions in the embodiment of the present disclosure include:

[0073] The injection volume at the first station of the pipeline is consistent with the shipment volume output by the product manufacturer through the pipeline, and the time corresponds.

[0074] The embodiment of the present disclosure constrains the associative coupling between the pipeline scheduling submodel and the logistics submodel through associative constraints. The associative constraints in the embodiment of the present disclosure are used to associate batches in the pipeline scheduling submodel with products in the logistics submodel. By associating batches in the pipeline scheduling submodel with products in the logistics submodel, the pipeline scheduling submodel can be associated and coupled with the logistics submodel.

[0075] In an exemplary embodiment, the objective function of the logistics optimization model in the embodiment of the present disclosure includes:

[0076] min f=f 1 +f 2 +f 3 +f 4 ;

[0077] Among them, f is the target cost, min f means the lowest cost, and f 1 The logistics cost of the product shipment. 2 is the logistics fee of the product transfer warehouse, 3 is the inventory management fee, f 4 A stock-out penalty fee at the location where the product is received.

[0078] The disclosed embodiment adds up the logistics costs of the product delivery location, the logistics costs of the product transit warehouse, the inventory management fee, and the out-of-stock penalty fee of the product receiving location in each product transportation plan, and determines the product transportation plan with the least cost as the optimal product transportation plan, that is, the product transportation information output by the logistics optimization model. By setting the objective function of the logistics optimization model, the cost of the obtained product transportation plan is minimized, providing technical support for saving product transportation costs.

[0079] Figure 2 A flow chart of a method for constructing a transportation model according to an embodiment of the present disclosure, such as Figure 2 As shown, including:

[0080] Step 201: Establish a logistics sub-model based on the predetermined logistics information of product transportation and the first constraint condition, where the logistics sub-model is used to determine the logistics path of the product transportation;

[0081] Step 202: Establish a pipeline scheduling sub-model based on the predetermined product transportation pipeline information and the second constraint condition, where the pipeline scheduling sub-model is used to determine the pipeline to be used when transporting the product;

[0082] Step 203: According to the transport connection relationship between pipeline and logistics and the pre-determined associated constraints between pipeline and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transport connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception;

[0083] Among them, the pipelines for product transportation include pipelines with the following characteristics: there are transit warehouses at the connection points of the pipelines, and / or there are multiple injection stations in a single pipeline.

[0084] The disclosed embodiment will establish a logistics sub-model and a pipeline scheduling sub-model, and couple them through transportation connection relationships and associated constraints. The obtained logistics optimization model can simultaneously consider the combined transportation of pipelines and other logistics paths when transporting products, thereby providing technical support for improving the transportation efficiency of products.

[0085] It should be noted that the same parts of the method for constructing a transportation model as those of the method for processing transportation information may use the same processing facilities as those of the method for processing transportation information, and will not be elaborated in detail in the embodiments of the present disclosure.

[0086] The embodiment of the present disclosure also provides a computer storage medium, in which a computer program is stored. When the computer program is executed by a processor, the above-mentioned method for processing transportation information is implemented.

[0087] The embodiment of the present disclosure also provides a terminal, including: a memory and a processor, wherein a computer program is stored in the memory;

[0088] in,

[0089] The processor is configured to execute the computer program in the memory;

[0090] When the computer program is executed by a processor, the method for processing transportation information as described above is implemented.

[0091] The embodiment of the present disclosure also provides a computer storage medium, in which a computer program is stored. When the computer program is executed by a processor, the method for constructing a transportation model is implemented.

[0092] The embodiment of the present disclosure also provides a terminal, including: a memory and a processor, wherein a computer program is stored in the memory;

[0093] in,

[0094] The processor is configured to execute the computer program in the memory;

[0095] When the computer program is executed by a processor, the method for constructing a transportation model is implemented.

[0096] Figure 3 The structure block diagram of the device for processing transportation information according to the embodiment of the present disclosure is as follows: Figure 3 As shown, it includes: logistics module, pipeline scheduling module, association module and processing module; among which,

[0097] The logistics module is set up as follows: according to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported;

[0098] The pipeline scheduling module is configured to: establish a pipeline scheduling sub-model according to the predetermined pipeline information of the product transportation and the second constraint condition, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported;

[0099] The association module is set as follows: according to the predetermined transportation connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transportation connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception;

[0100] The processing module is configured to: calculate the basic information and operation information of the product to be transported through a logistics optimization model to obtain the transportation plan information of the product to be transported;

[0101] Among them, the pipeline for product transportation includes more than one pipeline with the following characteristics: there is a transit warehouse at the connection of the pipeline and / or there are more than two injection stations in a single pipeline.

[0102] In an exemplary embodiment, the apparatus of the embodiment of the present disclosure further includes an acquisition unit, which is configured to:

[0103] Get basic and operational information.

[0104] In an exemplary embodiment, the basic information in the embodiment of the present disclosure includes the following information or any combination of information of the product to be transported:

[0105] Product information, inventory information, pipeline station information, transportation capacity, place of shipment, destination, transportation cost and transit time.

[0106] In an exemplary embodiment, the operation information in the embodiment of the present disclosure includes one or any combination of the following information:

[0107] Initial state of pipeline, initial inventory and supply plan.

[0108] In an exemplary embodiment, the transport connection relationship in the embodiment of the present disclosure includes the following information:

[0109] Pipelines used to receive products after they have been transported through logistics;

[0110] Logistics used to transport products after they are output from the pipeline.

[0111] In an exemplary embodiment, the first constraint condition in the embodiment of the present disclosure includes:

[0112] Transportation capacity constraints, supply and demand balance constraints, and inventory constraints;

[0113] Among them, the transportation capacity constraints include: for each mode of transportation, the amount of products sent / received through the current mode of transportation per unit time is less than or equal to the upper limit of the amount of products sent / received through this mode of transportation; the supply and demand balance constraints include: the shipment volume of products sent to a region per unit time plus the shortage of products is equal to the demand for products in the region per unit time; the inventory constraints include: the inventory of products is within the safety stock range.

[0114] In an exemplary embodiment, the second constraint condition in the embodiment of the present disclosure includes:

[0115] Batch constraints, flow limit constraints, and injection and distribution constraints;

[0116] Among them, the batch constraint is: for each batch, the oil head movement of the batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the flow limit constraint is: the download amount of the pipeline distribution station is within the download amount limit range of the distribution station; the injection and distribution constraints are: if and only if the batch belongs to the batch that is passing through the station, the first station or distribution station of the pipeline can perform corresponding operations on the products of the batch; the batch constraint includes batch tracking and position constraints; batch tracking is that the oil head movement of a batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the position constraint is: for each batch, as time increases, the position coordinates of the batch products in the pipeline at the next moment are greater than or equal to their position coordinates in the pipeline at the previous moment.

[0117] In an exemplary embodiment, the association constraint conditions in the embodiment of the present disclosure include:

[0118] The injection volume at the first station of the pipeline is consistent with the shipment volume output by the product manufacturer through the pipeline, and the time corresponds.

[0119] In an exemplary embodiment, the objective function of the logistics optimization model in the embodiment of the present disclosure includes:

[0120] min f=f 1 +f 2 +f 3 +f 4 ;

[0121] Among them, f is the target cost, min f means the lowest cost, and f 1 The logistics cost of the product shipment. 2 is the logistics fee of the product transfer warehouse, 3 is the inventory management fee, f 4 A stock-out penalty fee at the location where the product is received.

[0122] The disclosed embodiment also provides a device for constructing a transportation model, including: a logistics module, a pipeline scheduling module, a correlation module and a processing module; wherein:

[0123] Logistics module, pipeline scheduling module, association module and processing module; among them,

[0124] The logistics module is set up as follows: according to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported;

[0125] The pipeline scheduling module is configured to: establish a pipeline scheduling sub-model according to the predetermined pipeline information of the product transportation and the second constraint condition, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported;

[0126] The association module is set as follows: according to the predetermined transportation connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transportation connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception;

[0127] Among them, the pipelines for product transportation include pipelines with the following characteristics: there are transit warehouses at the connection points of the pipelines, and / or there are multiple injection stations in a single pipeline.

[0128] In an exemplary embodiment, the transport connection relationship in the embodiment of the present disclosure includes the following information:

[0129] Pipelines used to receive products after they have been transported through logistics;

[0130] Logistics used to transport products after they are output from the pipeline.

[0131] In an exemplary embodiment, the first constraint condition in the embodiment of the present disclosure includes:

[0132] Transportation capacity constraints, supply and demand balance constraints, and inventory constraints;

[0133] Among them, the transportation capacity constraints include: for each mode of transportation, the amount of products sent / received through the current mode of transportation per unit time is less than or equal to the upper limit of the amount of products sent / received through this mode of transportation; the supply and demand balance constraints include: the shipment volume of products sent to a region per unit time plus the shortage of products is equal to the demand for products in the region per unit time; the inventory constraints include: the inventory of products is within the safety stock range.

[0134] In an exemplary embodiment, the second constraint condition in the embodiment of the present disclosure includes:

[0135] Batch constraints, flow limit constraints, and injection and distribution constraints;

[0136] Among them, the batch constraint is: for each batch, the oil head movement of the batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the flow limit constraint is: the download amount of the pipeline distribution station is within the download amount limit range of the distribution station; the injection and distribution constraints are: if and only if the batch belongs to the batch that is passing through the station, the first station or distribution station of the pipeline can perform corresponding operations on the products of the batch; the batch constraint includes batch tracking and position constraints; batch tracking is that the oil head movement of a batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the position constraint is: for each batch, as time increases, the position coordinates of the batch products in the pipeline at the next moment are greater than or equal to their position coordinates in the pipeline at the previous moment.

[0137] In an exemplary embodiment, the association constraint conditions in the embodiment of the present disclosure include:

[0138] The injection volume at the first station of the pipeline is consistent with the shipment volume output by the product manufacturer through the pipeline, and the time corresponds.

[0139] In an exemplary embodiment, the objective function of the logistics optimization model in the embodiment of the present disclosure includes:

[0140] min f=f 1 +f 2 +f 3 +f 4 ;

[0141] Among them, f is the target cost, min f means the lowest cost, and f 1 The logistics cost of the product shipment. 2 is the logistics fee of the product transfer warehouse, 3 is the inventory management fee, f 4 A stock-out penalty fee at the location where the product is received.

[0142] The following briefly describes the embodiments of the present disclosure through application examples. The application examples are only used to illustrate the embodiments of the present disclosure and are not used to limit the protection scope of the embodiments of the present disclosure.

[0143] Application Examples

[0144] This application example takes the product of refined oil as an example to briefly illustrate the embodiment of the present disclosure.

[0145] The following is a description of the first constraint condition of the logistics sub-model in the embodiment of the present disclosure:

[0146] First, the set of all moments in the logistics cycle is T (for example, there are 30 days in a month, and if the span is days, then the number of moments is 31), the set of refineries (or pipeline first stations) is I, the set of oil depots is J, the set of transportation methods is N, and the set of oil products is P.

[0147] The transportation capacity of the embodiment of the present disclosure includes receiving capacity and shipping capacity. For receiving capacity, the amount of oil products received by oil depot j' through transportation mode n per unit time should be less than the upper limit of the receiving capacity of this mode. The formula for the receiving capacity constraint is expressed as follows:

[0148]

[0149] In this formula, It represents the amount of oil product o delivered by refinery i to oil depot i' by mode n in time window t, in cubic meters (m 3 ); It indicates the amount of oil product o sent from oil depot j (transit oil depot) to oil depot j' by mode n in time window t, in m3 ; Indicates the maximum receiving capacity of oil depot j' through mode n, in m 3 ; It represents the set of refineries that can deliver oil to oil depot j'; Represents the set of tank depots that can deliver oil to tank j'.

[0150] For the shipping capacity constraint, the amount of oil products shipped by a refinery or oil depot through transportation mode n per unit time should be less than the upper limit of the oil shipping capacity of this mode. Since shipping involves refineries and oil depots, it is necessary to limit refineries and oil depots respectively. The formula for the refinery's shipping capacity constraint is as follows:

[0151]

[0152] In this formula, Represents the maximum delivery capacity of refinery i through mode n, in m 3 .

[0153] The formula for the shipping capacity constraint of the oil depot is as follows:

[0154]

[0155] In this formula, Indicates the maximum delivery capacity of oil depot j through mode n, in m 3 .

[0156] The disclosed embodiment imposes transport capacity constraints on the logistics sub-model, thereby limiting the amount of oil products received by the oil depot through the transportation method in a unit time to be less than the upper limit of the oil receiving capacity of the transportation method; and the amount of oil products sent by the refinery or oil depot through the transportation method in a unit time to be less than the upper limit of the oil sending capacity of the transportation method; thereby enabling the obtained refined oil transportation plan to be implemented in life, avoiding the situation where the refined oil cannot be transported due to exceeding the upper limit of the oil receiving or sending of the transportation method.

[0157] The supply and demand balance constraint in the embodiment of the present disclosure is that the oil depot's shipment volume to the local market within a unit time span plus the shortage volume should be equal to the demand volume within this time span in the local area, and the formula is as follows:

[0158]

[0159] In this formula, It represents the quantity of oil product o delivered by oil depot j to the local area within the time window t, in m 3 ; Indicates the shortage of oil product o in oil depot j within time window t, in units of m 3 ;D t，j，oIt represents the demand for oil product o in the local oil depot j within the time window t, in units of m 3 By constraining the supply and demand balance of the logistics sub-model, the quantity of refined oil in the local market is rationalized to avoid the situation where the refined oil is sold out or there is too much reserve.

[0160] The inventory constraints in the embodiments of the present disclosure mainly include inventory capacity constraints and inventory change constraints. Since the product transportation plan requires storage in both the oil depot and the refinery, the refinery and the oil depot need to be limited respectively for inventory constraints; the inventory capacity constraint in the embodiments of the present disclosure means that the inventory of the oil depot or refinery oil depot should always be within its safety inventory range. The formula for the inventory capacity constraint of the refinery in the embodiments of the present disclosure is as follows:

[0161]

[0162] In this formula, Respectively represent the lower and upper limits of the storage capacity of oil product o in refinery i, in m 3 ; Represents the inventory of oil product o in refinery i at time t, in m 3 .

[0163] In the embodiment of the present disclosure, the formula for the inventory capacity constraint of the oil depot is as follows:

[0164]

[0165] In the formula, They represent the lower and upper limits of the storage capacity of oil product o in oil depot j, in m 3 ; It represents the inventory of oil product o in oil depot j at time t, in m 3 .

[0166] Since the inventory is constantly changing during the transportation of refined oil products, it is also necessary to constrain the inventory change. The inventory change of the refinery is related to its shipment volume to each oil depot (including pipeline injection volume), its own production volume and initial inventory. Therefore, the formula for the inventory change constraint of the refinery is as follows:

[0167]

[0168] In this formula, It represents the amount of oil product o delivered by refinery i to oil depot j' in time window t by mode n, in m 3 ; Represents the inventory of the refinery in time window t+1, in m 3 ; Represents the refinery inventory within time window t, in m 3 ; It indicates the amount of oil product o injected into the pipeline by refinery (first station) i within time window t, in m 3 ; Represents the production of oil product o in refinery i within time window t, in units of m 3 Among them, because it needs to be coupled with the pipeline scheduling sub-model in the end, the pipeline injection volume Will be associated with the pipeline scheduling submodel.

[0169] The change in the inventory of the oil depot is related to its receipt volume (including pipeline download volume), delivery volume (transit oil depot), and initial inventory volume. Therefore, the formula for the inventory change constraint of the oil depot is as follows:

[0170]

[0171] In this formula, Represents the inventory of the refinery in time window t+1, in m 3 ; Represents the refinery inventory within time window t, in m 3 ; Δt i，i，n Indicates the transportation time limit from refinery i to oil depot j via mode n, the number of time windows (can be days); Δt j′，j，n Indicates the number of time windows (which can be days) from tank j′ to tank j via mode n; It indicates the amount of oil product o downloaded from refinery (first station) i by oil depot (distribution station) j in time window t, in m 3 ; represents the set of upstream refineries (first stations) of oil depot (pipeline depot, distribution station) j; Represents the time window t-Δt i，j，n The amount of oil product o delivered by refinery i to oil depot j by means n, in m 3 ; Represents the time window t-Δt i，j，n The amount of oil product o sent from internal oil depot j (transit oil depot) to oil depot j' by means n, in m 3 ; It indicates the amount of oil product o sent from oil depot j (transit oil depot) to oil depot j' by mode n in time window t, in m 3 ; It represents the quantity of oil product o delivered by oil depot j to the local area within the time window t, in m 3 .

[0172] The disclosed embodiment avoids safety problems caused by excessive inventory by imposing inventory constraints on the logistics sub-model.

[0173] The disclosed embodiment constrains the established logistics sub-model through transportation capacity, supply-demand balance and inventory, thereby ensuring that the transportation plan for refined oil products is reasonable and can be implemented in the operational production process.

[0174] The following is an example of the second constraint condition of the pipeline scheduling sub-model:

[0175] First, the set of all pipeline first stations (refineries) is I, and the set of pipeline injection batches corresponding to the first station i is The set of distribution stations (oil depots) along the pipeline corresponding to the first station i is The other sets are the same as the logistics sub-model, that is, the time set is T, the oil depot set is J, the transportation mode set is N, and the oil product set is P.

[0176] Regarding batch constraints, batch constraints include batch tracking and location constraints. For batch tracking, the pipeline scheduling submodel is limited to the oil head movement of batch b in the time period t~t+1 should be consistent with the download volume of the previous batch b′<b by all distribution stations. The formula is as follows:

[0177]

[0178] In this formula, It represents the position coordinates of the oil head of batch b injected by the first station i at time t+1, in m 3 ; It represents the position coordinates of the oil head of batch b injected by the first station i at time t, in m 3 ; It represents the volume of batch b' oil product o downloaded from the first station i by the distribution station j' within the time window t, in m 3 ; In this formula, at the initial moment, the location coordinates of the pipe storage batch are known, and the volume of the uninjected batch is determined by the pipeline scheduling sub-model, and the formula is as follows:

[0179]

[0180]

[0181] In the above formula, It represents the position coordinates of the oil head of batch b injected by the first station i at the initial time, in m 3 ; Indicates the location coordinates of the pipe storage batch b of the pipeline belonging to the first station i, in m 3 ; It represents the volume of oil product o of batch b injected by the first station i within the time window t, in m 3 ; They respectively represent the pipeline storage batch set of the pipeline belonging to the first station i (one more than the batch number, indicating that the oil tail position of the batch is also known) and the new injection batch set.

[0182] The position constraint in the embodiment of the present disclosure is to prevent the backflow phenomenon. For batch b, the backflow phenomenon is not allowed to occur over time. The formula of the position constraint is as follows:

[0183]

[0184] In this formula, Indicates the position coordinates of the pipe storage batch b of the pipeline belonging to the first station i within the time window t+1, in m 3 ; Indicates the position coordinates of the pipe storage batch b of the pipeline belonging to the first station i within the time window t, in m 3 ; It can be seen that the position constraint limits the position coordinates of batch b at the next moment in the pipeline to be greater than or equal to the position coordinates at the previous moment in the pipeline as time increases, thereby avoiding the phenomenon of backflow of finished oil in the pipeline. The embodiment of the present disclosure also includes the following formula:

[0185]

[0186] In this formula, Indicates the position coordinates of the pipe storage batch b of the pipeline belonging to the first station i within the time window t, in m 3 ; Indicates the position coordinates of the pipe storage batch b of the pipeline belonging to the first station i within the time window t, in m 3 ; It can be seen that the position constraint also limits the position coordinates of the subsequent batches to be less than or equal to the position coordinates of the previous batch, so that the circulation of the product oil in the pipeline is in the order of the finished oil batches.

[0187] In pipeline transportation, flow rate is a very important factor, so it is necessary to impose flow restriction constraints on the pipeline scheduling sub-model. There are many types of flow rates, such as the initial injection flow, the final outbound flow, and the flow balance in the pipeline. Therefore, flow restriction constraints can include injection or downloading volume constraints, outbound (pipeline section) flow constraints, and flow balance constraints. In order to ensure the safe operation of the distribution station when downloading oil products, the effective working range of the distribution station flowmeter, regulating valve and other equipment and the restrictions of the oil tank on the inlet flow must be considered when formulating the scheduling plan. Therefore, the download volume of the distribution station cannot exceed the download volume limit range. For the injection of the first station, that is, the initial flow constraint sent from the refinery through the pipeline, the formula is as follows:

[0188]

[0189] In this formula, It represents the volume of oil product o of batch b injected by the first station i within the time window t, in m 3 ; Indicates the upper limit of the injection flow of the first station i, in m 3 / h; τ represents the time window span, in h; Y i，b，o is a binary variable, indicating whether the batch b injected at the first station i is oil product o. If batch b is oil product o, Y i，b，o =1; if batch b is not oil product o, Y i，b，o = 0. By limiting the flow rate injected into the first station to be less than or equal to the upper limit of the injection flow rate of the first station, the obtained product transportation plan is more reasonable and reliable.

[0190] For the download volume of a distribution station or oil depot, the formula is as follows:

[0191]

[0192] In this formula, It represents the volume of batch b oil product o downloaded from the first station i by the distribution station j' within the time window t, in m 3 ; Indicates the download limit of the distribution station j' along the pipeline to which the first station i belongs, in m 3 / h; This formula limits the download volume of the distribution station or oil depot to be less than the upper limit of the download volume.

[0193] When the refined oil is transported in the pipeline, it is not only injected and discharged, but also flows out of the pipeline. Therefore, it is necessary to constrain the outbound or pipeline flow. At a certain moment, the flow of the pipeline section should be consistent with the total discharge volume of the downstream distribution station. The formula is as follows:

[0194]

[0195] In this formula, Indicates the upper limit of the outbound flow of the pipeline distribution station j' to which the first station i belongs, in m 3 / h; This formula limits the flow rate of finished oil in the pipeline at a certain moment to be less than or equal to the total download volume of the downstream distribution station or oil depot.

[0196] In the embodiment of the present disclosure, flow balance needs to be maintained in pipeline transportation, that is, the amount of refined oil entering the pipeline must be the same as the amount of refined oil downloaded, and the formula is as follows:

[0197]

[0198] In this formula, by limiting the injected flow to be equal to the downloaded flow within the same time window, the flow balance in the pipeline is ensured.

[0199] In the disclosed embodiment, in pipeline transportation, it is also necessary to limit that the first station or the sub-transmission station can perform corresponding operations on the batch only when the batch belongs to the batch that is passing through the station, that is, the injection and sub-transmission constraints; that is, the first station or the sub-transmission station can control the batch of finished oil only when the finished oil of the batch is located at the first station or the sub-transmission station. For the injection constraint, the judgment condition is that at the start time of the time window, the oil tail of the batch of oil has not passed this station, and at the end time of the time window, the oil head of the batch of oil has passed the station. The formula is as follows:

[0200]

[0201]

[0202]

[0203]

[0204] In this formula, z i represents the volume coordinate of the first station i (usually 0), m 3 ; is a binary variable, indicating whether the first station i can inject batch b within the time window t. no, M represents a maximum value.

[0205] For the download operation, the judgment condition is the same as the injection judgment condition, that is, at the beginning of the time window, the tail of the batch of oil products has not passed this station, and at the end of the time window, the head of the batch of oil products has passed the station. The formula is as follows:

[0206]

[0207]

[0208]

[0209]

[0210] In this formula, z i，j , represents the station volume coordinates of the pipeline distribution station j' to which the first station i belongs, m 3 ; is a binary variable, indicating whether the pipeline distribution station j' to which the first station i belongs can download batch b within the time window t. The pipeline distribution station j' to which the first station i belongs can download batch b within the time window t. Within the time window t, the pipeline distribution station j' belonging to the first station i cannot download batch b.

[0211] The main purpose of setting the association constraint conditions in the embodiment of the present disclosure is to associate batches with oil products, so as to facilitate the calculation of inventory changes in the logistics sub-model, mainly involving the first station, namely the refinery, and the distribution depot, namely the oil depot.

[0212] In the embodiment of the present disclosure, the formula for the association constraint condition for first station association is as follows:

[0213]

[0214] In this formula, It indicates the amount of oil product o injected into the pipeline by refinery (first station) i within time window t, in m 3 ; It represents the volume of oil product o of batch b injected by the first station i within the time window t. That is, it is limited that the injection volume of the first station is consistent with the volume shipped by the refinery through the pipeline, and the time is corresponding.

[0215] The formula for the association constraint condition for associating the distribution stations of the pipeline in the embodiment of the present disclosure is as follows:

[0216]

[0217] In this formula, It represents the volume of batch b oil product o downloaded from the first station i by the distribution station j' within the time window t, in m 3 ; It indicates the amount of oil product o downloaded from refinery (first station) i by distribution station (oil depot) j′ within time window t, in units of m 3 That is, the amount downloaded from the pipeline distribution station is limited to the amount received by the oil depot through the pipeline, and the time is corresponding.

[0218] The disclosed embodiment limits the injection volume of the first station to be consistent with the shipment volume of the refinery through pipeline, and the time is corresponding, and the download volume of the pipeline distribution station is consistent with the receipt volume of the oil depot through pipeline, and the time is corresponding; the coupling association of the two calculation models is realized, and a logistics optimization model is obtained.

[0219] In the embodiment of the present disclosure, the objective function min f=f 1 +f 2 +f 3 +f 4 When the product is refined oil, f 1 is the refinery logistics cost, f 2 is the logistics fee of the transit oil depot, 3 is the inventory management fee, f 4 Penalty fee for out of stock.

[0220] In the embodiment of the present disclosure, the calculation formula of the refinery logistics cost can be:

[0221]

[0222] In this formula, It represents the amount of oil product o delivered by refinery i to oil depot j' in time window t by mode n, in m 3 ; It represents the unit freight cost of oil product o shipped by refinery i to oil depot j' via mode n, in CNY / m 3 ; It indicates the unit pipeline transportation fee for transporting oil product o from the first station (refinery) i to the distribution station (oil depot) j', the unit is CNY / m 3 ; It indicates the amount of oil product o downloaded from refinery (first station) i by distribution station (oil depot) j′ within time window t, in units of m 3 That is to say, refinery logistics costs include two aspects: one is the transportation fee incurred by the refinery when shipping to all oil depots through non-pipeline means; the other is the pipeline transportation fee incurred by the refinery when shipping to its oil depots through pipeline means.

[0223] In the embodiment of the present disclosure, the calculation formula of the transit oil depot logistics fee can be:

[0224]

[0225] In this formula, It represents the unit freight cost of oil product o shipped from oil depot j to oil depot j' by mode n, in CNY / m 3 ; It indicates the amount of oil product o sent from oil depot j (transit oil depot) to oil depot j' by mode n in time window t, in m 3 The logistics fee of the transit oil depot includes the secondary transportation costs between all oil depots. Since pipeline transportation does not require secondary transportation, the cost of pipeline transportation does not need to be considered in the logistics fee of the transit oil depot.

[0226] In the embodiment of the present disclosure, the calculation formula of the inventory management fee may be:

[0227]

[0228] In this formula, Respectively represent the unit inventory fee of oil product o by refinery i or oil depot j in each time window, in CNY / m 3 ; Represents the inventory of oil product o in refinery i at time t, in m 3 ; It represents the inventory of oil product o in oil depot j at time t, in m 3The inventory management fee includes the inventory costs of all refineries and oil depots.

[0229] In the disclosed embodiment, the calculation formula of the out-of-stock penalty fee may be:

[0230]

[0231] In this formula, It represents the unit shortage penalty fee of oil depot j for oil product o, the unit is CNY / m 3 ; Indicates the shortage of oil product o in oil depot j within time window t, in units of m 3 The shortage penalty fee includes the compensation costs of all oil depots when there is a shortage of oil.

[0232] The above formulas are used to calculate the refinery logistics fee, transit oil depot logistics fee, inventory management fee and out-of-stock penalty fee respectively, and the above fees are added together to obtain the total cost, thereby obtaining the minimum value of the total cost.

[0233] The method of the embodiment of the present disclosure can be implemented in the Southwest refined oil pipeline network, in which five pipelines (Pipeline A, Pipeline B, Pipeline C, Pipeline D and Pipeline E) are included, among which, in addition to the first station injection, Pipeline A and Pipeline B each include an intermediate injection station; therefore, the Southwest refined oil pipeline network includes a total of 5 pipelines, 42 stations, 3 transportation modes and 3 main oil products.

[0234] When formulating the refined oil transportation plan, the supply and demand plan of refined oil is first obtained. Table 1 lists the demand for corresponding oil products of some stations. Among them, the station demand is divided into three types, namely 92# gasoline, 95# gasoline, and 0# diesel; the demand for 95# gasoline in pipeline A is 0, and there is a demand for 95# gasoline in pipeline B; the demand at the injection point of each pipeline is 0.

[0235]

[0236] Table 1

[0237] Table 2 lists the supply of various oil products at some stations, among which only the first station and intermediate injection station of the pipeline have supply, pipeline A does not supply 95# gasoline, and pipeline B has supply of 3 kinds of oil products.

[0238]

[0239]

[0240] Table 2

[0241] Table 3 shows the initial states of pipeline A and part of pipeline B, where the oil head position coordinates in the pipeline are represented by oil head volume coordinates, which are the sum of the volumes of all pipelines from the oil head position to the initial position of the pipeline.

[0242]

[0243] Table 3

[0244] Table 4 lists the upper and lower limits of the download volume and the upper and lower limits of the outbound flow of each station. For the injection port, the upper and lower limits of the download volume represent the upper and lower limits of the injection flow. The upper and lower limits of the outbound flow are the maximum and minimum values ​​of the flow in the pipeline required during the design of the pipeline.

[0245]

[0246]

[0247] Table 4

[0248] Table 5 shows the initial inventory of various oil products at some stations.

[0249]

[0250] Table 5

[0251] Table 6 lists the upper and lower limits of inventory for various oil products at some stations.

[0252]

[0253]

[0254] Table 6

[0255] Table 7 lists the transportation prices and transit times for some transportation modes.

[0256]

[0257] Table 7

[0258] In Tables 1 to 7, the demand, supply, initial status of pipelines, pipeline station information, initial inventory of each station, oil depot information, transportation costs and transit time of the finished oil transportation plan are obtained respectively. Therefore, the above data are brought into the logistics optimization model to obtain the product oil transportation plan.

[0259] Table 8 is calculated by the logistics optimization model through the pipeline supply and demand plan. The table shows the transportation volume and transportation time of railway and road transportation when non-pipeline transportation is used.

[0260]

[0261] Table 8

[0262] Table 9 shows the partial injection volume of pipeline A when transporting by pipeline. The logistics optimization model calculates the injection situation of the first station and intermediate injection station of pipeline A according to the supply and demand plan.

[0263]

[0264]

[0265] Table 9

[0266] Table 10 lists the distribution situation of some stations in pipeline A. The logistics optimization model calculates the distribution situation of each distribution station in pipeline A based on the supply and demand plan.

[0267]

[0268] Table 10

[0269] The disclosed embodiment establishes a finished oil pipeline transportation plan formulation model, namely a logistics optimization model, combines the actual operation data of the southwest pipeline network, comprehensively considers the combined transportation mode of pipelines and railways, and formulates a corresponding operation plan that meets the on-site operation requirements.

[0270] Figure 4 is a flow chart of the method of the embodiment of the present disclosure, such as Figure 4 As shown, first input parameters, which may include refinery delivery plan, oil depot outbound plan, western oil depot transfer and oil production parameters. The above parameters are input into the logistics optimization model. The logistics sub-model in the logistics optimization model calculates the input parameters and obtains the scheme of pipeline transportation path, railway transportation path and highway transportation path respectively. The pipeline scheduling sub-model in the logistics optimization model calculates the input parameters and obtains the batch injection scheme and batch distribution scheme respectively. The oil products in the scheme obtained by the logistics sub-model are associated with the batches in the pipeline scheduling sub-model through the association constraints in the logistics optimization model, and the association coupling between the logistics sub-model and the pipeline scheduling sub-model in the logistics optimization model is realized, so that a complete pipeline transportation scheme, a complete railway transportation scheme and a complete highway transportation scheme can be obtained.

[0271] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description 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 by several physical components in cooperation. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium 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 technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

Claims

1. A method for processing transportation information, characterized in that: include: According to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported; According to the predetermined product transportation pipeline information and the second constraint condition, a pipeline scheduling sub-model is established, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported; According to the pre-determined transport connection relationship and associated constraints between pipeline and logistics, the logistics sub-model and pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transport connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception; The basic information and operation information of the products to be transported are calculated through the logistics optimization model to obtain the transportation plan information of the products to be transported; The pipeline for transporting the product includes more than one pipeline having the following characteristics: there is a transfer depot at the connection of the pipeline and / or there are more than two injection stations in a single pipeline.

2. The method according to claim 1, characterized in that Before calculating the basic information and operation information of the product to be transported through the logistics optimization model, the method further includes: The basic information and the operation information are obtained.

3. The method according to claim 2, characterized in that The basic information includes one or any combination of the following information about the product to be transported: Product information, inventory information, pipeline station information, transportation capacity, place of shipment, destination, transportation cost and transit time.

4. The method according to claim 2, characterized in that: The operation information includes one or any combination of the following information: Initial state of pipeline, initial inventory and supply plan.

5. The method according to any one of claims 1 to 4, characterized in that: The transport connection relationship includes the following information: Pipelines for receiving products after they have been transported through logistics; Logistics used to transport products after they are output from the pipeline.

6. The method according to any one of claims 1 to 4, characterized in that: The first constraint condition includes: Transportation capacity constraints, supply and demand balance constraints, and inventory constraints; Among them, the transportation capacity constraint includes: for each mode of transportation, the amount of products sent / received through the current mode of transportation per unit time is less than or equal to the upper limit of the amount of products sent / received through the mode of transportation; the supply and demand balance constraint includes: the shipment volume of products to a region per unit time plus the out-of-stock quantity of the products is equal to the demand for the products in the region per unit time; the inventory constraint includes: the inventory of the products is within the safety stock range.

7. The method according to any one of claims 1 to 4, characterized in that: The second constraint condition includes: Batch constraints, flow limit constraints, and injection and distribution constraints; Among them, the batch constraint is: for each batch, the oil head movement of the batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the flow limit constraint is: the download amount of the pipeline distribution station is within the download amount limit range of the distribution station; the injection and distribution constraints are: if and only if the batch belongs to a batch that is passing through the station, the first station or distribution station of the pipeline can perform corresponding operations on the products of the batch; the batch constraint includes batch tracking and position constraints; the batch tracking is that the oil head movement of a batch per unit time is consistent with the download amount of the previous batch by the pipeline distribution station; the position constraint is: for each batch, as time increases, the position coordinates of the batch products in the pipeline at the next moment are greater than or equal to their position coordinates in the pipeline at the previous moment.

8. The method according to any one of claims 1 to 4, characterized in that: The association constraints include: The injection volume at the first station of the pipeline is consistent with the shipment volume output by the product manufacturer through the pipeline, and the time corresponds.

9. The method according to any one of claims 1 to 4, characterized in that: The objective function of the logistics optimization model includes: minf=f1+f2+f3+f4; Among them, f is the target cost, minf means the lowest cost, f1 is the logistics fee at the product shipment location, f2 is the logistics fee at the product transit warehouse, f3 is the inventory management fee, and f4 is the out-of-stock penalty fee at the product receiving location.

10. A method for constructing a transportation model, characterized in that: include: According to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported; According to the predetermined product transportation pipeline information and the second constraint condition, a pipeline scheduling sub-model is established, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported; According to the transport connection relationship between pipeline and logistics and the pre-determined associated constraints between pipeline and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model, wherein the transport connection relationship includes the connection relationship between logistics transportation and pipeline output and pipeline reception; The pipeline for transporting the product includes a pipeline having the following characteristics: there is a transfer warehouse at the connection point of the pipeline, and / or there are multiple injection stations in a single pipeline.

11. A computer storage medium storing a computer program, wherein the computer storage medium stores a computer program, and when the computer program is executed by a processor, the method for processing transportation information according to any one of claims 1 to 9, or the method for constructing a transportation model according to claim 10 is implemented.

12. A terminal, comprising: A memory and a processor, wherein the memory stores a computer program; wherein, The processor is configured to execute the computer program in the memory; When the computer program is executed by the processor, the method for processing transportation information according to any one of claims 1 to 9 or the method for constructing a transportation model according to claim 10 is implemented.

13. A device for processing transportation information, characterized in that: include: Logistics module, pipeline scheduling module, association module and processing module; among them, The logistics module is set up as follows: according to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported; The pipeline scheduling module is configured to: establish a pipeline scheduling sub-model according to the predetermined pipeline information of the product transportation and the second constraint condition, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported; The association module is set as follows: according to the predetermined transportation connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transportation connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception; The processing module is configured to: calculate the basic information and operation information of the product to be transported through a logistics optimization model to obtain the transportation plan information of the product to be transported; The pipeline for transporting the product includes more than one pipeline having the following characteristics: there is a transfer depot at the connection of the pipeline and / or there are more than two injection stations in a single pipeline.

14. A device for constructing a transportation model, characterized in that: include: Logistics module, pipeline scheduling module, association module and processing module; among them, Logistics module, pipeline scheduling module, association module and processing module; among them, The logistics module is set up as follows: according to the predetermined logistics information of product transportation and the first constraint condition, a logistics sub-model is established, and the logistics sub-model is used to determine the logistics path when the product is transported; The pipeline scheduling module is configured to: establish a pipeline scheduling sub-model according to the predetermined pipeline information of the product transportation and the second constraint condition, and the pipeline scheduling sub-model is used to determine the pipeline to be called when the product is transported; The association module is set as follows: according to the predetermined transportation connection relationship and associated constraints between pipelines and logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model. The transportation connection relationship includes: the connection relationship between logistics transportation and pipeline output and pipeline reception; The pipeline for transporting the product includes a pipeline having the following characteristics: there is a transfer warehouse at the connection point of the pipeline, and / or there are multiple injection stations in a single pipeline.

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