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

Abstract

The application discloses a method and device for processing transportation information, a method and device for constructing a transportation model, and establishes a logistics submodel and a pipeline scheduling submodel, and the logistics submodel and the pipeline scheduling submodel are coupled by transportation connection relations and associated constraint conditions, a logistics optimization model obtained by the coupling can simultaneously consider a pipeline and a logistics path of product transportation, and transportation plan information of products to be transported is obtained by operation of the logistics optimization model, thereby providing technical support for improving product transportation efficiency.

Description

TECHNICAL FIELD

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

[0002] With the increasing demand for oil products year by year, the scale of oil product transportation is becoming larger and larger, and the cost of oil product transportation is increasing year by year. How to reasonably develop a logistics plan and save transportation costs has become an important means for oil product sales enterprises to improve their competitiveness.

[0003] The oil product pipeline network refers to a pipeline network for transporting oil products from a refinery to a gas station. According to the transportation mode, the oil product pipeline can be divided into a sequential transportation pipeline and a batch transportation pipeline. The sequential transportation pipeline refers to transporting different types of oil products in a certain order, while the batch transportation pipeline refers to transporting different types of oil products in batches. The pipeline scheduling model in the related art generally considers the calculation of a single pipeline or multiple pipelines that are not related to each other.

[0004] The scheduling plan of the oil product pipeline in the related art is small in scale, and the obtained pipeline scheduling scheme generally considers a single pipeline or multiple pipelines that are not related to each other, which is a pipeline operation method independent of each other. However, the pipeline network including the western oil product pipeline network has the characteristics of multiple pipelines, transfer depots at the connection of the pipelines, and multiple injection points in a single pipeline. How to establish a transportation pipeline that can be applied to the pipeline network including the western oil product pipeline network and develop a transportation plan to improve the transportation efficiency of oil products has become a problem to be solved. SUMMARY

[0005] The following is a summary of the subject matter of the detailed description of the present application. This summary is not intended to limit the protection 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 oil products.

[0007] The embodiments of the present disclosure provide a method for processing transportation information, which comprises:

[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 a logistics path during product transportation;

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

[0010] The logistics sub-model and the pipeline scheduling sub-model are associated and coupled according to a predetermined transportation connection relationship and associated constraint condition of the pipeline and the logistics, to obtain a logistics optimization model, and the transportation connection relationship includes a connection relationship of logistics transportation and pipeline output and pipeline receiving.

[0011] The basic information and running information of the product to be transported are calculated through the logistics optimization model to obtain transportation plan information of the product to be transported.

[0012] The pipeline for product transportation includes one or more pipelines with the following characteristics: a transfer warehouse exists at a connection of the pipeline, and / or two or more injection stations exist in a single pipeline.

[0013] In another aspect, the embodiments of the present disclosure also provide a computer storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above method for processing transportation information or the above method for constructing a transportation model.

[0014] In another aspect, the embodiments of the present disclosure also provide a terminal, which includes a memory and a processor, and the memory stores a computer program; wherein,

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

[0016] The computer program is executed by the processor to implement the above method for processing transportation information or the above method for constructing a transportation model.

[0017] In another aspect, the embodiments of the present disclosure also provide an apparatus for processing transportation information, which includes a logistics module, a pipeline scheduling module, an association module and a processing module; wherein,

[0018] The logistics module is configured to establish a logistics sub-model according to predetermined logistics information and a first constraint condition of product transportation, and the logistics sub-model is used to determine a logistics path during product transportation.

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

[0020] The association module is configured to associate and couple the logistics sub-model and the pipeline scheduling sub-model according to a predetermined transportation connection relationship and associated constraint condition of the pipeline and the logistics, to obtain a logistics optimization model, and the transportation connection relationship includes a connection relationship of logistics transportation and pipeline output and pipeline receiving.

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

[0022] The pipeline for product transportation comprises one or more pipelines with the following characteristics: a transfer station is present at the connection of the pipeline, and / or two or more injection stations are present in a single pipeline.

[0023] In yet another aspect, the embodiments of the present disclosure further provide a device for constructing a transportation model, comprising a logistics module, a pipeline scheduling module, a correlation module and a processing module, wherein,

[0024] the logistics module, the pipeline scheduling module, the correlation module and the processing module, wherein,

[0025] the logistics module is configured to establish a logistics sub-model according to pre-determined logistics information of product transportation and a first constraint condition, the logistics sub-model being used to determine a logistics path during product transportation;

[0026] the pipeline scheduling module is configured to establish a pipeline scheduling sub-model according to pre-determined pipeline information of product transportation and a second constraint condition, the pipeline scheduling sub-model being used to determine a pipeline to be called during product transportation;

[0027] the correlation module is configured to correlate and couple the logistics sub-model and the pipeline scheduling sub-model according to a pre-determined transportation correlation between the pipeline and the logistics and a correlation constraint condition, to obtain a logistics optimization model, the transportation correlation comprising a correlation between logistics transportation and pipeline output and pipeline receiving;

[0028] The pipeline for product transportation comprises a pipeline with the following characteristics: a transfer station is present at the connection of the pipeline, and / or multiple injection stations are present in a single pipeline.

[0029] Compared with the related art, the logistics sub-model and the pipeline scheduling sub-model established by the embodiments of the present disclosure are correlated and coupled through the transportation correlation and the correlation constraint condition, and the logistics optimization model obtained can simultaneously consider the pipeline and the logistics path of product transportation, and the transportation plan information of the product to be transported is obtained through the logistics optimization model, thereby providing technical support for improving the product transportation efficiency.

[0030] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the following description, or can be learned by practice of the present application. Other advantages of the present application can be realized and obtained by means of the instrumentalities and combinations pointed out in the following description. BRIEF DESCRIPTION OF DRAWINGS

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

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

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

[0034] Figure 3 A structural block diagram of an apparatus for processing transportation information by an embodiment of the present disclosure;

[0035] Figure 4 A flowchart of a method by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0036] The present application describes a number of embodiments, but the description is exemplary rather than limiting and it will be apparent to those of ordinary skill in the art that numerous more embodiments and implementations are possible within the scope of the embodiments described in the present application. Although a number of possible combinations of features have been set forth in the accompanying figures and discussed above, many other combinations will be possible. Unless specifically intended for limitation of an embodiment, any feature or element of any embodiment can be used in combination with any other feature or element of any other embodiment, or can replace any other feature or element of 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 can also be combined with any conventional features or elements to form unique inventive solutions defined by the claims. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in the present application can be implemented alone or in any appropriate combination. Accordingly, the embodiments are not to be restricted, except as by the appended claims and their equivalents. Furthermore, various modifications and changes can be made within the scope of the appended claims.

[0038] Furthermore, in describing representative embodiments, the specification can have presented the method and / or process as a particular sequence of steps. However, to the extent that the method or process depends on more than one step, the method or process should not be limited to the particular sequence of steps described. Other sequences of steps can be possible, and are within the scope of the embodiments. Therefore, the particular order in which the steps are presented in the specification is not an limitation on the embodiments. Moreover, the specification can present the steps of the method and / or process in a particular order, but the steps can be performed in any order that is practicable, as will be understood by those of ordinary skill in the art.

[0039] In the related art, the scheduling model of the pipeline only considers the calculation of a single pipeline or multiple pipelines that are irrelevant to each other, and cannot make a joint scheduling scheme for the case where multiple pipelines exist in a transit station, and cannot use a system such as the western refined oil pipeline network which has multiple pipelines, multiple injection points, and multiple transportation modes.

[0040] Figure 1 A flowchart of a method for processing transportation information in the embodiments of the present disclosure is shown in FIG. 1, and includes the following steps. Figure 1

[0041] In step 101, a logistics sub-model is established according to pre-determined logistics information of product transportation and first constraint conditions, and the logistics sub-model is used to determine a logistics path during product transportation.

[0042] In step 102, a pipeline scheduling sub-model is established according to pre-determined pipeline information of product transportation and second constraint conditions, and the pipeline scheduling sub-model is used to determine a pipeline to be called during product transportation.

[0043] In an exemplary example, the logistics information and the pipeline information in the embodiments of the present disclosure can be directly obtained from a related system of product transportation according to the related art. The logistics information in the embodiments of the present disclosure can include transportation modes of product transportation and transportation routes, transportation times, and transportation product quantities corresponding to each transportation mode, which are well known to those skilled in the art. The pipeline information in the embodiments of the present disclosure can include one or more pipelines in a network of product transportation, injection stations of each pipeline, and whether a transit warehouse exists at a connection of the pipeline.

[0044] ​In an example, the embodiment of the present disclosure can establish the logistics sub-model based on logistics information and first constraint conditions, and establish the pipeline scheduling sub-model based on pipeline information and second constraint conditions, based on an operational optimization algorithm. The operational optimization algorithm is a mathematical method for finding an optimal solution or a set of optimal solutions under given constraints. It has wide applications in various fields, such as logistics scheduling, vehicle routing, facility location, network optimization, etc. The operational optimization algorithm in the related art includes: 1. Mathematical programming algorithm: including linear programming, integer programming, nonlinear programming, etc. These algorithms can solve the optimal solution through mathematical models. 2. Heuristic algorithm: including genetic algorithm, particle swarm optimization, simulated annealing algorithm, etc. These algorithms search for the optimal solution by simulating the evolution of nature, physical principles, etc. 3. Branch and bound algorithm: this algorithm decomposes the problem into several sub-problems, and then solves the sub-problems step by step to obtain the optimal solution. 4. Dynamic programming algorithm: this algorithm decomposes the problem into several sub-problems, and then solves the sub-problems step by step to obtain the optimal solution. 5. Greedy algorithm: this algorithm selects the current optimal solution at each step to obtain the global optimal solution. Through the operational optimization algorithm, the optimal solution or the set of optimal solutions can be found under various constraints.

[0045] In step 103, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled according to the predetermined transportation connection relationship and associated constraint conditions of the pipeline and the logistics, to obtain a logistics optimization model. The transportation connection relationship includes the connection relationship between logistics transportation and pipeline output and pipeline receiving.

[0046] In step 104, the basic information and operation information of the product to be transported are operated through the logistics optimization model to obtain transportation plan information of the product to be transported.

[0047] The pipeline for product transportation includes one or more pipelines with the following characteristics: a transfer warehouse exists at the connection of the pipeline, and / or two or more injection stations exist in a single pipeline.

[0048] The logistics optimization model obtained by associating and coupling the logistics sub-model and the pipeline scheduling sub-model through the transportation connection relationship and the associated constraint conditions can simultaneously consider the pipeline for product transportation and the logistics path. The transportation plan information of the product to be transported obtained by operating the logistics optimization model provides technical support for improving the efficiency of product transportation.

[0049] In an example, the product in the embodiment of the present disclosure includes refined oil, and the pipeline in the embodiment of the present disclosure can include a refined oil pipeline. The refined oil pipeline in the embodiment of the present disclosure can include the management of an existing network in the related art, such as the pipeline in the western refined oil pipeline network.

[0050] In an example, before the base 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 comprises:

[0051] The base information and operation information are acquired.

[0052] In the process of making the product transportation plan, the base information and operation information of the product to be transported are acquired; the base information is used for calculation by the logistics optimization model, and the operation information is used for making the product transportation plan by the logistics optimization model. The base information and operation information are brought into the logistics optimization model to make the product transportation plan, so as to improve the transportation efficiency of the product to be transported.

[0053] In an example, the base information in the embodiment of the present disclosure comprises the following information of the product to be transported or any combination thereof:

[0054] The product information, inventory information, pipeline station information, transportation capacity, origin name, destination name, transportation cost, and in-transit time.

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

[0056] In an example, the operation information in the embodiment of the present disclosure comprises the following information or any combination thereof:

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

[0058] The operation information in the embodiment of the present disclosure is used for making the transportation plan in the logistics optimization model. The initial state of the pipeline in the operation information can comprise the batch number and the oil head volume coordinates, etc.; the initial inventory can comprise the initial inventory of the product in each product warehouse; and the supply plan can comprise the supply amount of the inventory product at the origin and the demand amount of the product at the destination, and the supply and demand amount. By bringing the operation information into the logistics optimization model, the embodiment of the present disclosure can obtain each step in the product transportation plan.

[0059] In an example, the transportation connection relationship in the embodiment of the present disclosure comprises the following information:

[0060] a pipeline for receiving the product after the product is transported by the logistics;

[0061] a logistics for transporting the product after the product is output from the pipeline.

[0062] The embodiments of the present disclosure establish the connection between the logistics nodes of the logistics sub-model and the pipeline nodes in the pipeline scheduling sub-model through the transportation connection relationship, and realize the association and coupling of the logistics sub-model and the pipeline scheduling sub-model in combination with the association constraint condition, thereby obtaining the logistics optimization model.

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

[0064] a transportation capacity constraint, a supply-demand balance constraint, and an inventory constraint;

[0065] The transportation capacity constraint includes that the product amount sent / received by each transportation mode in a unit time is less than or equal to the upper limit of the product amount sent / received by the transportation mode; the supply-demand balance constraint includes that the sending amount of the product sent to a region in a unit time plus the shortage amount of the product is equal to the demand amount of the product in the region in the unit time; and the inventory constraint includes that the inventory of the product is within a safe inventory range.

[0066] In the embodiments of the present disclosure, the first constraint condition, the second constraint condition, and the association constraint condition are involved in the process of obtaining the logistics optimization model. The constraint condition refers to the limitation or requirement imposed on certain variables or behaviors in a certain problem or scenario.

[0067] The transport capacity constraint in the first constraint condition refers to the maximum transport capacity of a transport mode such as railway, water transport, highway, and pipeline within a certain time; by performing the transport capacity constraint on the logistics sub-model, the obtained transport plan information can be implemented in life, and the situation that the transport plan cannot be implemented due to exceeding the maximum transport capacity is avoided. The transport capacity constraint in the embodiment of the present disclosure includes a receiving capacity constraint and a sending capacity constraint; the receiving capacity constraint is that the product quantity received through a certain transport mode within a unit time should be less than the upper limit of the product quantity received through the transport mode; the sending capacity constraint is that the product quantity sent through a certain transport mode within a unit time should be less than the upper limit of the product quantity sent through the transport mode. The supply-demand balance constraint refers to that the supply quantity should be equal to the demand quantity; by performing the supply-demand balance constraint on the logistics sub-model, it can be limited that in the product transport plan formulated by the logistics sub-model, the sending quantity of the product to a certain region within a unit time plus the shortage quantity of the region within the unit time should be equal to the demand quantity of the region within the unit time, so as to ensure that the quantity of the product in the region is reasonable, and the situation that the product is sold out or the storage is excessive is avoided. The inventory constraint refers to the materials stored in the warehouse; by performing the inventory constraint on the logistics sub-model, it can be limited that in the product transport plan formulated by the logistics sub-model, the inventory of the product is always within the safe inventory range, and the safety problem caused by excessive inventory is avoided. The embodiment of the present disclosure performs constraints on the logistics sub-model established by the transport capacity, the supply-demand balance, and the inventory, so as to ensure that the product transport plan contained in the obtained product transport information is reasonable and can be implemented in production and operation.

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

[0069] batch constraint, flow limit constraint, and injection and distribution constraint;

[0070] The batch constraint is that for each batch, the oil head migration quantity of the batch within a unit time is consistent with the download quantity of the previous batch by the distribution station of the pipeline; the flow limit constraint is that the download quantity of the distribution station of the pipeline is within the download quantity limit range of the distribution station; the injection and distribution constraint is that the first station or the distribution station of the pipeline can perform the corresponding operation on the product of the batch only when the batch belongs to the batch that is passing through the station; the batch constraint includes batch tracking and position constraint; the batch tracking is that the oil head migration quantity of a certain batch within a unit time is consistent with the download quantity of the previous batch by the distribution station of the pipeline; the position constraint is that for each batch, the position coordinates of the batch in the pipeline at a later time are greater than or equal to the position coordinates of the batch in the pipeline at a previous time as time increases.

[0071] The batch constraint is performed on the pipeline scheduling sub-model, so that the product passing through the pipeline cannot be reduced. For a batch, the position constraint is performed to avoid the phenomenon of product backflow over time. In order to ensure the safe operation of the download product of the distribution station, when the product transportation plan is formulated by the pipeline scheduling sub-model, the effective working range of the flow meter, the regulating valve and other devices of the distribution station and the limitation condition of the oil tank to the tank inlet flow must be considered. Therefore, the flow limitation constraint is performed on the pipeline scheduling sub-model, that is, the download amount of the distribution station in the product transportation plan formulated by the pipeline scheduling sub-model cannot exceed the download amount limitation range. The injection and distribution constraint is performed on the pipeline scheduling sub-model, that is, in the product transportation plan formulated by the pipeline scheduling sub-model, the first station or the distribution station of the pipeline can perform corresponding operations 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 the distribution station can operate the batch. The batch constraint, the flow limitation constraint and the injection and distribution constraint are performed on the pipeline scheduling sub-model, so that the product transportation plan formulated by the pipeline scheduling sub-model can formulate a reasonable product transportation plan in a multi-pipeline and multi-injection point system.

[0072] In an example, the association constraint condition in the embodiment of the present disclosure includes:

[0073] The injection amount of the pipeline first station is consistent with the delivery amount of the product manufacturer output through the pipeline, and the time corresponds.

[0074] The association constraint condition is used for associating the batch in the pipeline scheduling sub-model with the product in the logistics sub-model, and the pipeline scheduling sub-model can be associated and coupled with the logistics sub-model by associating the batch in the pipeline scheduling sub-model with the product in the logistics sub-model.

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

[0076] min f=f1+f2+f3+f4;

[0077] Wherein, f is the target cost, min f represents the minimum cost, f1 is the logistics cost of the product sending place, f2 is the logistics cost of the product transfer warehouse, f3 is the inventory management cost, and f4 is the shortage penalty cost of the product receiving place.

[0078] The product shipping plan with the least cost is determined as the optimal product shipping plan, that is, the product shipping information output by the logistics optimization model. The product shipping plan obtained through the setting of the objective function of the logistics optimization model has the least cost, thereby providing technical support for saving product shipping cost.

[0079] Figure 2 A flowchart of a method for constructing a shipping model according to an embodiment of the present disclosure is shown in FIG. 2, which includes the following steps. Figure 2

[0080] In step 201, a logistics sub-model is established according to predetermined logistics information of product shipping and first constraint conditions, and the logistics sub-model is used to determine a logistics path during product shipping.

[0081] In step 202, a pipeline scheduling sub-model is established according to predetermined pipeline information of product shipping and second constraint conditions, and the pipeline scheduling sub-model is used to determine a pipeline called during product shipping.

[0082] In step 203, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled according to a shipping connection relationship and predetermined associated constraint conditions of the pipeline and the logistics, to obtain a logistics optimization model, and the shipping connection relationship includes a connection relationship between logistics shipping and pipeline output and pipeline receiving.

[0083] The pipeline of product shipping includes a pipeline having the following characteristics: a transfer warehouse exists at a connection of the pipeline, and / or multiple injection stations exist in a single pipeline.

[0084] The logistics optimization model obtained by associating and coupling the logistics sub-model and the pipeline scheduling sub-model according to the shipping connection relationship and the associated constraint conditions can simultaneously consider joint shipping of the pipeline and other logistics paths during product shipping, thereby providing technical support for improving product shipping efficiency.

[0085] It should be noted that the same part in the method for constructing a shipping model and the method for processing shipping information can use the same processing facility in the method for processing shipping information, and the present disclosure will not be repeated here.

[0086] An embodiment of the present disclosure further provides a computer storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above method for processing shipping information.

[0087] An embodiment of the present disclosure further provides a terminal, which includes a memory and a processor, and the memory stores a computer program. ​

[0088] wherein,

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

[0090] The computer program, when executed by the processor, implements the method of processing transport information as described above.

[0091] The embodiments of the present disclosure also provide a computer storage medium, which stores a computer program, and the computer program, when executed by a processor, implements the method of constructing a transport model as described above.

[0092] The embodiments of the present disclosure also provide a terminal, which comprises a memory and a processor, and the memory stores a computer program;

[0093] wherein,

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

[0095] The computer program, when executed by the processor, implements the method of constructing a transport model as described above.

[0096] Figure 3 The structural block diagram of the device for processing transport information in the embodiments of the present disclosure is shown in Figure 3 which comprises a logistics module, a pipeline scheduling module, an association module and a processing module; wherein,

[0097] The logistics module is configured to establish a logistics sub-model according to pre-determined logistics information of product transportation and first constraint conditions, and the logistics sub-model is used to determine a logistics path during product transportation;

[0098] The pipeline scheduling module is configured to establish a pipeline scheduling sub-model according to pre-determined pipeline information of product transportation and second constraint conditions, and the pipeline scheduling sub-model is used to determine a pipeline called during product transportation;

[0099] The association module is configured to associate and couple the logistics sub-model and the pipeline scheduling sub-model according to pre-determined association relationship between the pipeline and the logistics and association constraint conditions, to obtain a logistics optimization model, and the association relationship includes the association relationship between logistics transportation and pipeline output and pipeline receiving;

[0100] The processing module is configured to perform operation on the basic information and the running information of the product to be transported through the logistics optimization model, to obtain transport plan information of the product to be transported;

[0101] The pipeline of product transportation includes one or more pipelines with the following characteristics: a transfer warehouse exists at the connection of the pipeline, and / or two or more injection stations exist in a single pipeline.

[0102] In an example, the device further comprises an acquisition unit configured to:

[0103] acquire the basic information and the operation information.

[0104] In an example, the basic information comprises one or any combination of the following information of the product to be transported:

[0105] product information, inventory information, pipeline station information, transportation capacity, origin name, destination name, transportation cost, and in-transit time.

[0106] In an example, the operation information comprises one or any combination of the following information:

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

[0108] In an example, the transportation connection relationship comprises the following information:

[0109] pipeline for receiving the product after the product is transported by the logistics;

[0110] logistics for transporting the product after the product is output from the pipeline.

[0111] In an example, the first constraint condition comprises:

[0112] transportation capacity constraint, supply-demand balance constraint, and inventory constraint.

[0113] The transportation capacity constraint comprises: for each transportation mode, the amount of product sent / received by the current transportation mode per unit time is less than or equal to the upper limit of the amount of product sent / received by the transportation mode; the supply-demand balance constraint comprises: the amount of product sent to a region per unit time plus the amount of product shortage is equal to the demand amount of product of the region per unit time; and the inventory constraint comprises: the inventory of the product is within a safe inventory range.

[0114] In an example, the second constraint condition comprises:

[0115] batch constraint, flow restriction constraint, and injection and distribution constraint.

[0116] The batch constraint is that: for each batch, the oil head migration amount of the batch in a unit time is consistent with the download amount of the previous batch by the distribution station of the pipeline; the flow limit constraint is that: the download amount of the distribution station of the pipeline is within the download amount limit range of the distribution station; the injection and distribution constraint is that: when and only when the batch belongs to the batch passing through the station, the product of the batch can be subjected to the corresponding operation by the first station or the distribution station of the pipeline; the batch constraint includes batch tracking and position constraint; the batch tracking is that: the oil head migration amount of a certain batch in a unit time is consistent with the download amount of the previous batch by the distribution station of the pipeline; the position constraint is that: for each batch, as time increases, the position coordinates of the batch product in the pipeline at a later time are greater than or equal to the position coordinates of the batch product in the pipeline at a previous time.

[0117] In an exemplary instance, the association constraint condition in the embodiment of the present disclosure includes:

[0118] The injection amount of the pipeline first station is consistent with the delivery amount of the product generator output through the pipeline, and the time corresponds.

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

[0120] min f=f1+f2+f3+f4;

[0121] Wherein, f is the target cost, min f indicates the lowest cost, f1 is the logistics cost of the product sending place, f2 is the logistics cost of the product transit warehouse, f3 is the inventory management cost, and f4 is the shortage penalty cost of the product receiving place.

[0122] The embodiment of the present disclosure also provides a device for constructing a transportation model, comprising: a logistics module, a pipeline scheduling module, an association module and a processing module; wherein,

[0123] The logistics module, the pipeline scheduling module, the association module and the processing module; wherein,

[0124] The logistics module is configured to: establish a logistics sub-model according to the logistics information of the product transportation and the first constraint condition, and the logistics sub-model is used to determine the logistics path during the product transportation;

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

[0126] The association module is configured to: according to the transportation connection relationship and the association constraint condition of the pipeline and the logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model, and the transportation connection relationship includes: the connection relationship of the logistics transportation and the pipeline output and the pipeline receiving;

[0127] The pipeline for product transportation comprises a pipeline having the following characteristics: a transfer warehouse exists at the connection of the pipeline, and / or multiple injection stations exist in a single pipeline.

[0128] In an exemplary instance, the transportation connection relationship in the embodiments of the present disclosure comprises the following information:

[0129] A pipeline for receiving the product after the product is transported by logistics;

[0130] Logistics for transporting the product after the product is output from the pipeline.

[0131] In an exemplary instance, the first constraint condition in the embodiments of the present disclosure comprises:

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

[0133] The transportation capacity constraints comprise: for each transportation mode, the amount of product sent / received by the current transportation mode per unit time is less than or equal to the upper limit of the amount of product sent / received by the transportation mode; the supply-demand balance constraints comprise: the amount of product sent to a region per unit time plus the amount of product out of stock is equal to the amount of product demanded by the region per unit time; and the inventory constraints comprise: the inventory of the product is within a safe inventory range.

[0134] In an exemplary instance, the second constraint condition in the embodiments of the present disclosure comprises:

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

[0136] The batch constraints are: for each batch, the amount of oil head migration of the batch per unit time is consistent with the amount of download of the previous batch by the distribution station of the pipeline; the flow limit constraints are: the amount of download of the distribution station of the pipeline is within the download limit range of the distribution station; the injection and distribution constraints are: the corresponding operation on the product of the batch can be performed by the first station or the distribution station of the pipeline only when the batch belongs to a batch that is passing through the station; the batch constraints comprise batch tracking and position constraints; the batch tracking is that the amount of oil head migration of a batch per unit time is consistent with the amount of download of the previous batch by the distribution station of the pipeline; and the position constraints are: for each batch, as time increases, the position coordinates of the batch in the pipeline at a later time are greater than or equal to the position coordinates of the batch in the pipeline at an earlier time.

[0137] In an exemplary instance, the associated constraint condition in the embodiments of the present disclosure comprises:

[0138] The injection amount of the first station of the pipeline is consistent with the shipment amount of the product generation manufacturer output by the pipeline, and the times correspond.

[0139] In an exemplary instance, the objective function of the logistics optimization model in the embodiments of the present disclosure comprises:

[0140] min f=f1+f2+f3+f4;

[0141] wherein f is a target cost, min f represents the lowest cost, f1 is a logistics cost of a product sending location, f2 is a logistics cost of a product transit depot, f3 is an inventory management cost, and f4 is a shortage penalty cost of a product receiving location.

[0142] The embodiments of the present disclosure are briefly described below through application examples, and the application examples are only used to describe the embodiments of the present disclosure and do not limit the protection scope of the embodiments of the present disclosure.

[0143] Application example

[0144] The embodiments of the present disclosure are briefly described below through application examples, and the application examples are only used to describe the embodiments of the present disclosure and do not limit the protection scope of the embodiments of the present disclosure.

[0145] The first constraint condition of the logistics sub-model in the embodiments of the present disclosure is described below:

[0146] First, the set of all time points of the logistics cycle is T (for example, there are 30 days in a month, and the time span is in days, so there are 31 time points), the set of refineries (or pipeline starting stations) is I, the set of depots is J, the set of transportation modes is N, and the set of oil products is P.

[0147] The transportation capacity in the embodiments of the present disclosure includes receiving capacity and sending capacity; for the receiving capacity, the amount of oil received by the depot j' through the transportation mode n in a unit of time should be less than the upper limit of the oil receiving capacity of the mode, and the formula expression of the receiving capacity constraint is as follows:

[0148]

[0149] In the formula, represents the amount of oil product o sent by the refinery i through the mode n to the depot i' in the time window t, and the unit is cubic meters (m 3 ); represents the amount of oil product o sent by the depot j (transit depot) through the mode n to the depot j' in the time window t, and the unit is m 3 ; represents the maximum receiving capacity of the depot j' through the mode n, and the unit is m 3 ; represents the set of refineries that can send oil to the depot j'; represents the set of depots that can send oil to the depot j'.

[0150] For the shipment capacity constraint, the amount of oil products shipped by the refinery or the oil depot through mode n in a unit of time should be less than the upper limit of the oil shipment capacity of the mode. Since shipment involves both the refinery and the oil depot, the refinery and the oil depot need to be limited respectively, and the formula for the shipment capacity constraint of the refinery is as follows:

[0151]

[0152] In the formula, represents the maximum shipment capacity of refinery i through mode n, with the unit of m 3 .

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

[0154]

[0155] In the formula, represents the maximum shipment capacity of oil depot j through mode n, with the unit of m 3 .

[0156] The embodiments of the present disclosure limit the amount of oil products received by the oil depot through the transportation mode in a unit of time to be less than the upper limit of the oil receiving capacity of the transportation mode, and the amount of oil products shipped by the refinery or the oil depot through the transportation mode in a unit of time to be less than the upper limit of the oil shipment capacity of the transportation mode, by performing the transportation capacity constraint in the logistics sub-model, so that the obtained refined oil transportation plan can be implemented in life, and the situation that the refined oil cannot be transported due to exceeding the upper limit of the oil receiving or shipment of the transportation mode is avoided.

[0157] The supply-demand balance constraint in the embodiments of the present disclosure is that the amount of oil shipped by the oil depot to the local market in a unit of time plus the shortage amount should be equal to the demand amount in the local market in the time span, and the formula is as follows:

[0158]

[0159] In the formula, represents the amount of oil product o shipped by oil depot j to the local market in time window t, with the unit of m 3 ; represents the shortage amount of oil product o of oil depot j in time window t, with the unit of m 3 ;D t，j，o represents the demand amount of oil product o in the local market where oil depot j is located in time window t, with the unit of m 3 . The amount of refined oil in the local market is rationalized by performing the supply-demand balance constraint on the logistics sub-model, and the situation that the refined oil is sold out or the storage amount is too large is avoided.

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

[0161]

[0162] In the formula, respectively represent the lower limit and the upper limit of the storage capacity of the oil product o in the refinery i, and the unit is m 3 . represents the inventory of the oil product o in the refinery i at time t, and the unit is m 3 .

[0163] The formula of the inventory capacity constraint of the oil depot in the embodiments of the present disclosure is as follows:

[0164]

[0165] In the formula, respectively represent the lower limit and the upper limit of the storage capacity of the oil product o in the oil depot j, and the unit is m 3 . represents the inventory of the oil product o in the oil depot j at time t, and the unit is m 3 .

[0166] Since the inventory is constantly changing in the process of product transportation, the inventory change constraint is also needed, wherein the inventory change of the refinery is related to the delivery amount (including the pipeline injection amount) to each oil depot, the production amount of itself and the initial inventory, therefore, the formula of the inventory change constraint of the refinery is as follows:

[0167]

[0168] In the formula, represents the amount of the oil product o delivered by the refinery i through the mode n to the oil depot j' in the time window t, and the unit is m 3 . represents the inventory of the refinery in the time window t+1, and the unit is m 3 . represents the inventory of the refinery in the time window t, and the unit is m 3 . represents the amount of the oil product o injected into the pipeline by the refinery (the first station) i in the time window t, and the unit is m 3 . represents the production amount of the oil product o in the refinery i in the time window t, and the unit is m 3Wherein, since the last needs to be associated with the pipeline scheduling sub-model, therefore, the pipeline injection quantity will be associated with the pipeline scheduling sub-model.

[0169] And for the inventory change of the oil depot is related to its receiving quantity (including the pipeline download quantity), delivery quantity (transit depot), initial inventory quantity, therefore, the formula of the inventory change constraint of the oil depot is as follows:

[0170]

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

[0172] The embodiments of the present disclosure avoid the situation that the safety problem is caused due to too much inventory by performing the inventory constraint on the logistics sub-model.

[0173] The embodiments of the present disclosure constrain the established logistics sub-model by the transportation capacity, supply-demand balance and inventory, and ensure that the obtained transportation plan of the refined oil is reasonable and can be implemented in the operation and production process.

[0174] The second constraint condition of the pipeline scheduling sub-model is described by taking an example as follows:

[0175] Firstly, all pipeline first stations (refineries) are collected as I, and the pipeline injection batch set corresponding to the first station i is The pipeline along the line distribution station (depot) set corresponding to the first station i is Other sets are the same as the logistics sub-model, that is, the time set is T, the 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 position constraints. For batch tracking, the pipeline scheduling sub-model is limited to the oil head movement amount of batch b in the time period t~t+1, which should be consistent with the download amount of all distribution stations to the previous batch b'<b, and the formula is as follows:

[0177]

[0178] In the formula, represents the oil head position coordinate of batch b injected by the first station i at time t+1, with the unit of m 3 ; represents the oil head position coordinate of batch b injected by the first station i at time t, with the unit of m 3 ; represents the volume of oil product o downloaded from batch b' of the first station i at the distribution station j' in the time window t, with the unit of m 3 ; In the formula, the position coordinate of the batch in the initial time is known, and the volume of the un-injected batch is determined by the pipeline scheduling sub-model, and the formula is as follows:

[0179]

[0180]

[0181] In the above formula, represents the oil head position coordinate of batch b injected by the first station i at the initial time, with the unit of m 3 ; represents the position coordinate of batch b of the pipeline to which the first station i belongs, with the unit of m 3 ; represents the volume of oil product o injected by batch b of the first station i in the time window t, with the unit of m 3 ; respectively represent the set of batches (one more than the batch number, indicating that the oil tail position of the batch is also known) and the set of newly injected batches of the pipeline to which the first station i belongs.

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

[0183]

[0184] In the formula, represents the position coordinates of the pipe storage batch b of the pipeline to which the first station i belongs in the time window t+1, in units of m 3 ; represents the position coordinates of the pipe storage batch b of the pipeline to which the first station i belongs in the time window t, in units of m 3 ; It can be seen that the position constraint limits that, for batch b, the position coordinates at a later time in the pipeline are greater than or equal to the position coordinates at a previous time in the pipeline, thereby avoiding the phenomenon that the finished oil flows backward in the pipeline. The embodiments of the present disclosure also include the following formula:

[0185]

[0186] In the formula, represents the position coordinates of the pipe storage batch b of the pipeline to which the first station i belongs in the time window t, in units of m 3 ; represents the position coordinates of the pipe storage batch b of the pipeline to which the first station i belongs in the time window t, in units of m 3 ; It can be seen that the position constraint also limits that the position coordinates of the subsequent batch are less than or equal to the position coordinates of the previous batch, so that the finished oil flows in the pipeline according to the order of the finished oil batches.

[0187] In pipeline transportation, flow is an important factor, so it is necessary to limit the flow of the pipeline scheduling sub-model. The flow has many cases, such as the initial injection flow, the end outflow, and the flow balance in the pipeline. Therefore, the flow limit constraint can include injection or download amount constraint, outflow (pipe section) flow constraint, and flow balance constraint. In order to ensure the safe operation of the distribution station when downloading oil products, the effective working range of the flow meter, the regulating valve and other devices of the distribution station and the restrictions of the oil tank on the tank inflow must be considered when formulating the scheduling plan. Therefore, the download amount of the distribution station cannot exceed the download amount limit range. For the injection of the first station, that is, the initial flow constraint from the refinery through the pipeline, the formula is as follows:

[0188]

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

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

[0191]

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

[0193] Since the product oil is transported in the pipeline, not only injection and download, but also outflow from the pipeline, therefore, the outbound or pipeline segment flow constraint is also needed, which should limit the flow of the pipeline segment at a certain moment to be consistent with the total download amount of the downstream distribution station, and the formula is as follows:

[0194]

[0195] In the formula, represents the upper limit of the outbound flow of the distribution station j' of the pipeline to which the first station i belongs, in m 3 / h; by the formula, the flow of the product oil in the pipeline at a certain moment is limited to be less than or equal to the total download amount of the downstream distribution station or the oil depot.

[0196] In the pipeline transportation, the flow balance also needs to be maintained, that is, the amount of the product oil entering the pipeline should be the same as the amount of the product oil downloaded, and the formula is as follows:

[0197]

[0198] In the formula, by limiting the injection flow to be equal to the download flow in the same time window, the flow balance in the pipeline is ensured.

[0199] The embodiments of the present disclosure also need to limit that the first station or the distribution 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 distribution constraints; that is, only when the batch of refined oil is located at the first station or the distribution station, the first station or the distribution station can control the batch of refined oil. For the injection constraint, the judgment condition is that at the starting time of the time window, the oil tail of the batch of oil has not passed the station, and at the end time of the time window, the oil head of the batch of oil has passed the station, and the formula is as follows:

[0200]

[0201]

[0202]

[0203]

[0204] In the formula, z i represents the volume coordinate of the first station i (usually 0), m 3 ; is a binary variable, which indicates whether the first station i can perform the injection operation on the batch b within the time window t. If the first station i can perform the injection operation on the batch b within the time window t, if not, M represents the maximum value.

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

[0206]

[0207]

[0208]

[0209]

[0210] In the formula, z i，j represents the station volume coordinate of the pipeline distribution station j' to which the first station i belongs, m 3 ; is a binary variable, which indicates whether the pipeline distribution station j' to which the first station i belongs can perform the download operation on the batch b within the time window t. If the pipeline distribution station j' to which the first station i belongs can perform the download operation on the batch b within the time window t, if not,

[0211] The main purpose of the association constraint condition 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, and mainly involves the first station, i.e., a refinery, and a distribution depot, i.e., an oil depot.

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

[0213]

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

[0215] In the embodiment of the present disclosure, the formula of the association constraint condition for the association of the distribution station of the pipeline is as follows:

[0216]

[0217] In the formula, represents the volume of oil product o in the batch b downloaded from the first station i by the distribution station j' in the time window t, and the unit is m 3 ; represents the amount of oil product o downloaded from the refinery (the first station) i by the distribution station (the oil depot) j' in the time window t, and the unit is m 3 . That is, it is limited that the download amount of the pipeline distribution station is consistent with the receipt amount of the oil depot through the pipeline mode, and the time corresponds.

[0218] In the embodiment of the present disclosure, by limiting that the injection amount of the first station is consistent with the delivery amount of the refinery through the pipeline mode, and the time corresponds, and the download amount of the pipeline distribution station is consistent with the receipt amount of the oil depot through the pipeline mode, and the time corresponds, the coupling association of the two calculation models is realized, and the logistics optimization model is obtained.

[0219] In the embodiment of the present disclosure, in the objective function min f = f1 + f2 + f3 + f4, when the product is a finished oil product, f1 is the logistics cost of the refinery, f2 is the logistics cost of the transit oil depot, f3 is the inventory management cost, and f4 is the shortage penalty cost.

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

[0221]

[0222] In the formula, represents the amount of oil product o delivered by the refinery i through the mode n to the oil depot j' in the time window t, and the unit is m 3 ; represents the unit freight of oil product o from refinery i to oil depot j' by mode n, with the unit of CNY / m 3 ; represents the unit pipeline transportation fee of oil product o from the first station (refinery) i to the distribution station (oil depot) j', with the unit of CNY / m 3 ; represents the amount of oil product o downloaded from refinery (first station) i by oil depot (distribution station) j' in time window t, with the unit of m 3 . That is, the refinery logistics fee includes two aspects: one is the transportation fee generated by the refinery sending goods to all oil depots by non-pipeline mode; the other is the pipeline transportation fee generated by the refinery sending goods to the affiliated oil depots by pipeline mode.

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

[0224]

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

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

[0227]

[0228] In the formula, respectively represent the unit inventory fee of oil product o in each time window for refinery i or oil depot j, with the unit of CNY / m 3 ; represents the inventory amount of oil product o in refinery i at time t, with the unit of m 3 ; represents the inventory amount of oil product o in oil depot j at time t, with the unit of m 3 . The inventory management fee includes the inventory cost of all refineries and oil depots.

[0229] In the embodiment of the present disclosure, the calculation formula of the shortage penalty fee can be:

[0230]

[0231] In the formula, represents the unit shortage penalty cost of the oil depot j to the oil product o, and the unit is CNY / m 3 ; represents the shortage quantity of the oil product o of the oil depot j in the time window t, and the unit is m 3 The shortage penalty cost includes all compensation fees of the oil depots when the shortage occurs.

[0232] The refinery logistics cost, the transit oil depot logistics cost, the inventory management cost, and the shortage penalty cost are calculated respectively through the above formulas, the total cost is obtained by adding the above costs, and then the minimum value of the total cost is obtained.

[0233] The method of the embodiment of the present disclosure can be implemented in the southwest product oil pipeline network, which includes five pipelines (A pipeline, B pipeline, C pipeline, D pipeline, and E pipeline), wherein the A pipeline and the B pipeline each include an intermediate injection station in addition to the first station injection. Therefore, the southwest product oil pipeline network includes 5 pipelines, 42 stations, 3 transportation modes, and 3 main oil products.

[0234] When the product oil transportation plan is formulated, the supply and demand plan of the product oil is first obtained, and Table 1 lists the demand quantity of the corresponding oil product of some stations, wherein the station demand is divided into three kinds, which are 92# gasoline, 95# gasoline, and 0# diesel oil; the demand quantity of 95# gasoline of the A pipeline is 0, and the B pipeline has a demand for 95# gasoline; the demand quantity of the injection point of each pipeline is 0.

[0235]

[0236] Table 1

[0237] Table 2 lists the supply quantity of various oil products of some stations, wherein only the first station and the intermediate injection station of the pipeline have the supply quantity, the A pipeline has no supply of 95# gasoline, and the B pipeline has the supply quantity of three kinds of oil products.

[0238]

[0239]

[0240] Table 2

[0241] Table 3 shows the initial state of the A pipeline and part of the B pipeline, wherein the oil head position coordinates in the pipeline are represented by the oil head volume coordinates, and the oil head volume coordinates are the total volume of all pipelines from the position of the oil head to the initial position of the pipeline.

[0242]

[0243] Table 3

[0244] Table 4 lists the upper and lower limits of the download amount and the upper limit of the outbound flow of each station, and the upper limit of the injection flow for the injection port download upper and lower limits. The upper and lower limits of the outbound flow are the maximum and minimum values of the flow in the pipeline required by the pipeline at the design time.

[0245]

[0246]

[0247] Table 4

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

[0249]

[0250] Table 5

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

[0252]

[0253]

[0254] Table 6

[0255] Table 7 lists the transportation prices and in-transit times of some transportation modes.

[0256]

[0257] Table 7

[0258] In Tables 1 to 7, the demand, supply, pipeline initial state, pipeline station information, initial inventory of each station, oil depot information, and transportation cost and in-transit time of product oil transportation plan are obtained respectively. Therefore, the above data is brought into the logistics optimization model, so as to obtain the product oil transportation plan.

[0259] Table 8 is the calculation of the supply and demand plan by the logistics optimization model through the pipeline, and the table shows the transportation amount and transportation time of the railway and highway transportation modes when using non-pipeline transportation.

[0260]

[0261] Table 8

[0262] Table 9 is the injection amount of A pipeline when using pipeline transportation, and the injection of the first station and the intermediate injection station of A pipeline is obtained by the logistics optimization model according to the supply and demand plan.

[0263]

[0264]

[0265] Table 9

[0266] Table 10 lists the A pipeline section station distribution situation, and the logistics optimization model is calculated according to the supply and demand plan to obtain the distribution situation of each distribution station of the A pipeline.

[0267]

[0268] Table 10

[0269] The embodiments of the present disclosure establish a product oil pipeline transportation planning model, i.e., a logistics optimization model, combine the actual operation data of the southwest pipeline network, comprehensively consider the joint transportation mode of the pipeline and the railway, formulate a corresponding operation plan, and meet the operation requirements on the site.

[0270] Figure 4 For the method flowchart of the embodiments of the present disclosure, as shown in Figure 4 the input parameters can include refinery delivery plans, oil depot delivery plans, western oil depot external adjustment, and petroleum production parameters. The above parameters are input into the logistics optimization model, the logistics sub-model part of the logistics optimization model calculates the input parameters to obtain a pipeline transportation path scheme, a railway transportation path scheme, and a highway transportation path scheme, the pipeline scheduling sub-model part of the logistics optimization model calculates the input parameters to obtain a batch injection scheme and a batch distribution scheme; the oil products in the schemes obtained by the logistics sub-model are associated with the batches in the pipeline scheduling sub-model through the associated constraint conditions in the logistics optimization model, the association and coupling of the logistics sub-model and the pipeline scheduling sub-model in the logistics optimization model are realized, and complete pipeline transportation schemes, complete railway transportation schemes, and complete highway transportation schemes can be obtained.

[0271] Those of ordinary skill in the art will realize and understand that all or some of the steps in the methods disclosed above and the functional modules / units in the systems and devices can be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component can have multiple functions, or one function or step can be performed by several physical components in cooperation. Some or all of the components can be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on computer-readable media, which can include computer storage media (or non-transitory media) and communication media (or transitory media). As is well known to those of ordinary skill 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 storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is 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 which can be used to store the desired information and which can be accessed by a computer. Furthermore, it is common and well understood by those of ordinary skill in the art that communication media typically embodies 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 can include any information delivery media.

Claims

1. A method of processing shipping information, characterized by, The method comprises the following steps: establishing a logistics sub-model according to predetermined logistics information of product transportation and first constraint conditions, the logistics sub-model being used to determine a logistics path during product transportation; establishing a pipeline scheduling sub-model according to predetermined pipeline information of product transportation and second constraint conditions, the pipeline scheduling sub-model being used to determine a pipeline called during product transportation; associating and coupling the logistics sub-model and the pipeline scheduling sub-model according to a predetermined transportation connection relationship of the pipeline and the logistics and associated constraint conditions, to obtain a logistics optimization model, the transportation connection relationship comprising a connection relationship between logistics transportation and pipeline output and pipeline receiving; operating basic information and running information of the product to be transported through the logistics optimization model to obtain transportation plan information of the product to be transported; wherein the pipeline of the product transportation comprises one or more pipelines with the following characteristics: a transfer warehouse exists at a connection of the pipeline and / or two or more injection stations exist in a single pipeline; the first constraint conditions comprise transportation capacity constraints, supply-demand balance constraints and inventory constraints; the transportation capacity constraints comprise, for each transportation mode, a product amount sent / received through a current transportation mode in a unit time being less than or equal to an upper limit of the product amount sent / received through the transportation mode; the supply-demand balance constraints comprise a product sending amount to a region in a unit time plus a shortage amount of the product being equal to a demand amount of the product in the region in the unit time; the inventory constraints comprise the product inventory being within a safe inventory range; the second constraint conditions comprise batch constraints, flow limitation constraints and injection and distribution constraints; the batch constraints are that, for each batch, an oil head migration amount of the batch in a unit time is consistent with a download amount of a previous batch by a distribution station of the pipeline; the flow limitation constraints are that a download amount of the distribution station of the pipeline is within a download amount limitation range of the distribution station; the injection and distribution constraints are that the first station or the distribution station of the pipeline can perform corresponding operations on a product of the batch only when the batch belongs to a batch passing through the station; the batch constraints comprise batch tracking and position constraints; the batch tracking is that an oil head migration amount of a certain batch in a unit time is consistent with a download amount of a previous batch by a distribution station of the pipeline; the position constraints are that, for each batch, a position coordinate of the batch in the pipeline at a later time is greater than or equal to a position coordinate of the batch in the pipeline at an earlier time.

2. The method of claim 1, wherein, Before the basic information and the running information of the product to be transported are operated through the logistics optimization model, the method further comprises: obtaining the basic information and the running information.

3. The method of claim 2, wherein, The basic information comprises one or any combination of the following information of the product to be transported: product information, inventory information, pipeline station information, transportation capacity, sending location name, destination name, transportation cost and in-transit time.

4. The method of claim 2, wherein, The running information comprises one or any combination of the following information: initial state, initial inventory and supply plan of the pipeline.

5. The method according to any one of claims 1 to 4, characterized in that, The transportation connection relationship comprises the following information: a pipeline used to receive a product after the product is transported by logistics. The product is output from the pipeline, and logistics for transporting the product.

6. The method according to any one of claims 1 to 4, characterized in that, The association constraint condition comprises: The injection amount of the first station of the pipeline is consistent with the shipment amount output by the product manufacturer through the pipeline, and the time corresponds.

7. The method according to any one of claims 1 to 4, characterized in that, The objective function of the logistics optimization model comprises: wherein, is a target cost, represents a cost minimization, is a logistics cost of a product origin, is a logistics cost of a product transit warehouse, is a stock management cost, is a shortage penalty cost of a product receiving location.

8. A method of constructing a transportation model, characterized by, Comprise: 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 during product transportation. According to the predetermined pipeline information of product transportation and the second constraint condition, a pipeline scheduling sub-model is established, and the pipeline scheduling sub-model is used to determine the pipeline called during product transportation. According to the transportation connection relationship between the pipeline and the logistics and the predetermined association constraint condition between the pipeline and the logistics, the logistics sub-model and the pipeline scheduling sub-model are associated and coupled to obtain a logistics optimization model, and the transportation connection relationship comprises the connection relationship between logistics transportation and pipeline output and pipeline receiving. The pipeline of the product transportation comprises a pipeline with the following characteristics: a transfer warehouse exists at the connection of the pipeline, and / or multiple injection stations exist in a single pipeline; the first constraint condition comprises: transportation capacity constraint, supply-demand balance constraint and inventory constraint; wherein the transportation capacity constraint comprises: for each transportation mode, the amount of product sent / received through the current transportation mode per unit time is less than or equal to the upper limit of the amount of product sent / received through the transportation mode; the supply-demand balance constraint comprises: the shipment amount of product sent to a region per unit time plus the shortage amount of the product equals the demand amount of the product in the region per unit time; the inventory constraint comprises: the inventory of the product is within the safe inventory range; the second constraint condition comprises: batch constraint, flow limitation constraint and injection and distribution constraint; wherein the batch constraint is that for each batch, the oil head migration amount per unit time of the batch is consistent with the download amount of the previous batch at the distribution station of the pipeline; the flow limitation constraint is that the download amount of the distribution station of the pipeline is within the download amount limitation range of the distribution station; the injection and distribution constraint is that the first station or the distribution station of the pipeline can perform corresponding operations on the product of the batch only when the batch belongs to the batch that is passing through the station; the batch constraint comprises batch tracking and position constraint; the batch tracking is that the oil head migration amount per unit time of a certain batch is consistent with the download amount of the previous batch at the distribution station of the pipeline; the position constraint is that for each batch, the position coordinates of the batch in the pipeline at a later time are greater than or equal to the position coordinates of the batch in the pipeline at an earlier time. 9.A computer storage medium, the computer storage medium storing a computer program, the computer program being executed by a processor to implement the method for processing transportation information according to any one of claims 1 to 7, or the method for constructing a transportation model according to claim 8.

10. A terminal comprising: A memory and a processor, the memory storing a computer program; wherein The processor is configured to execute the computer program in the memory. The computer program is executed by the processor to implement the method for processing transportation information according to any one of claims 1 to 7, or the method for constructing a transportation model according to claim 8.

11. An apparatus for processing shipping information, characterized by Comprise: The logistics module, the pipeline scheduling module, the association module and the processing module; wherein, The logistics module is configured to establish a logistics sub-model according to predetermined logistics information of product transportation and a first constraint condition, and the logistics sub-model is used to determine a logistics path during product transportation; The pipeline scheduling module is configured to establish a pipeline scheduling sub-model according to predetermined pipeline information of product transportation and a second constraint condition, and the pipeline scheduling sub-model is used to determine a pipeline called during product transportation; The association module is configured to associate and couple the logistics sub-model and the pipeline scheduling sub-model according to a predetermined transportation connection relationship of the pipeline and the logistics and an association constraint condition, to obtain a logistics optimization model, and the transportation connection relationship comprises a connection relationship of logistics transportation, pipeline output and pipeline receiving; The processing module is configured to perform calculation on basic information and running information of a product to be transported through the logistics optimization model, to obtain transportation plan information of the product to be transported; Wherein, the pipeline of product transportation comprises one or more pipelines with the following characteristics: a transfer warehouse exists at the connection of the pipeline, and / or two or more injection stations exist in a single pipeline; the first constraint condition comprises a transportation capacity constraint, a supply-demand balance constraint and an inventory constraint; wherein, the transportation capacity constraint comprises that the amount of products sent / received through a current transportation mode per unit time is less than or equal to the upper limit of the amount of products sent / received through the transportation mode; the supply-demand balance constraint comprises that the amount of products sent to a region per unit time plus the shortage amount of the products equals the demand amount of the products in the region per unit time; the inventory constraint comprises that the inventory of the products is within a safe inventory range; the second constraint condition comprises a batch constraint, a flow limitation constraint and an injection and distribution constraint; wherein, the batch constraint is that the oil head migration amount of each batch per unit time is consistent with the download amount of the previous batch at the distribution station of the pipeline; the flow limitation constraint is that the download amount of the distribution station of the pipeline is within the download amount limitation range of the distribution station; the injection and distribution constraint is that the first station or the distribution station of the pipeline can perform corresponding operations on the products of the batch only when the batch belongs to a batch passing through the station; the batch constraint comprises batch tracking and position constraint; the batch tracking is that the oil head migration amount of a batch per unit time is consistent with the download amount of the previous batch at the distribution station of the pipeline; the position constraint is that for each batch, the position coordinates of the batch in the pipeline at a later time are greater than or equal to the position coordinates of the batch in the pipeline at an earlier time.

12. An apparatus for constructing a transportation model, the apparatus comprising: Comprise: The logistics module, the pipeline scheduling module, the association module and the processing module; wherein, The logistics module, the pipeline scheduling module, the association module and the processing module; wherein, The logistics module, the pipeline scheduling module, the association module and the processing module; wherein, The logistics module is configured to establish a logistics sub-model according to predetermined logistics information of product transportation and a first constraint condition, the logistics sub-model being used to determine a logistics path during product transportation; The pipeline scheduling module is configured to establish a pipeline scheduling sub-model according to predetermined pipeline information of product transportation and a second constraint condition, the pipeline scheduling sub-model being used to determine a pipeline called during product transportation; The association module is configured to associate and couple the logistics sub-model and the pipeline scheduling sub-model according to a predetermined transportation connection relationship of the pipeline and the logistics and an association constraint condition, to obtain a logistics optimization model, the transportation connection relationship including a connection relationship of logistics transportation and pipeline output and pipeline receiving; The pipeline of the product transportation includes a pipeline having the following characteristics: a transfer warehouse exists at a connection of the pipeline, and / or multiple injection stations exist in a single pipeline; the first constraint condition includes a transportation capacity constraint, a supply-demand balance constraint and an inventory constraint; the transportation capacity constraint includes that a product amount sent / received through a current transportation mode per unit time is less than or equal to an upper limit of a product amount sent / received through the transportation mode; the supply-demand balance constraint includes that a sending amount of a product sent to a region per unit time plus a shortage amount of the product is equal to a demand amount of the product in the region per unit time; the inventory constraint includes that an inventory of the product is within a safe inventory range; the second constraint condition includes a batch constraint, a flow limitation constraint and an injection and distribution constraint; the batch constraint is that, for each batch, an oil head migration amount of the batch per unit time is consistent with a download amount of a previous batch by a distribution station of the pipeline; the flow limitation constraint is that a download amount of the distribution station of the pipeline is within a download amount limitation range of the distribution station; the injection and distribution constraint is that, when and only when a batch belongs to a batch passing through a station, a first station or a distribution station of the pipeline can perform a corresponding operation on the batch; the batch constraint includes batch tracking and position constraint; the batch tracking is that an oil head migration amount of a certain batch per unit time is consistent with a download amount of a previous batch by a distribution station of the pipeline; the position constraint is that, for each batch, a position coordinate of the batch in the pipeline at a later time is greater than or equal to a position coordinate of the batch in the pipeline at an earlier time.

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