Natural gas multimodal transport scheme planning method

Abstract

The invention discloses a natural gas multimodal transport scheme planning method. The method comprises the following steps of S1, collecting transport node information according to natural gas transport requirements; s2, according to the collected transportation node information, alternative transportation modes among the nodes are decided; s3, calculating transportation costs corresponding to different alternative transportation modes among the nodes according to the different alternative transportation modes among the nodes; s4, multimodal transport scheme planning is carried out based on the transport costs corresponding to different alternative transport modes among the nodes, and an optimal natural gas multimodal transport scheme is obtained; and S5, carrying out natural gas transportation according to the transportation mode among the nodes planned in the optimal natural gas multimodal transportation scheme.

Description

Technical Field

[0001] The present invention relates to the field of natural gas transportation, and in particular to a method for planning a natural gas multimodal transport solution. Background Art

[0002] my country's natural gas transportation mainly adopts pipeline transportation, which runs diagonally across the whole of China from Xinjiang to Jiangsu and coastal areas below latitude. In order to facilitate transportation to various regions of the country, it also needs to rely on flexible transportation modes such as roads, waterways, and railways. By selecting the best transportation combination, multimodal transportation can help reduce transportation costs and improve efficiency. In addition, by combining sea transportation and pipeline transportation, it can reduce carbon emissions caused by long-distance land transportation, thereby improving the environmental friendliness of transportation.

[0003] At present, the research on multimodal transport focuses on optimization algorithms and models, focusing on data-driven path optimization, and considering the environment and sustainability. And with the development, there are also many literatures studying the optimization of multimodal transport paths under uncertain conditions, which mainly emphasizes the uncertainty of demand and mainly targets common transport objects. For special objects (such as the transportation of natural gas), the role of such research theories is not convincing enough, and it is difficult to truly achieve high comprehensive transportation efficiency. Summary of the invention

[0004] A brief summary of one or more aspects is given below to provide a basic understanding of these aspects. This summary is not an exhaustive overview of all conceived aspects, and is neither intended to identify the key or critical elements of all aspects nor to define the scope of any or all aspects. Its only purpose is to give some concepts of one or more aspects in a simplified form as a prelude to a more detailed description that will be given later.

[0005] The purpose of the present invention is to solve the above problems and provide a natural gas multimodal transport scheme planning method. For the multimodal transport route optimization under the uncertainty conditions of natural gas transportation, the transportation tools and transportation routes are selected with the help of mathematical models and improved intelligent models, so as to obtain the best natural gas multimodal transport scheme under uncertain conditions, which has important practical significance for promoting energy transformation and reducing environmental impact.

[0006] The technical solution of the present invention is:

[0007] The present invention provides a method for planning a natural gas multimodal transport solution, comprising the following steps:

[0008] Step S1: Collecting transportation node information according to natural gas transportation demand;

[0009] Step S2: Determine the alternative transportation mode between nodes based on the collected transportation node information;

[0010] Step S3: calculating the transportation costs corresponding to different alternative transportation modes between nodes according to different alternative transportation modes between nodes;

[0011] Step S4: planning a multimodal transport solution based on the transport costs corresponding to different alternative transport modes between nodes to obtain an optimal multimodal transport solution for natural gas; and

[0012] Step S5: transporting natural gas according to the transportation mode between nodes planned in the optimal natural gas multimodal transport plan.

[0013] According to an embodiment of the natural gas intermodal transportation scheme planning method of the present invention, the transportation node information includes weather information between each node and the previously used transportation mode; wherein, when the natural gas intermodal transportation scheme planning method decides the alternative transportation mode between each node, the weather information of each node in the future time period is obtained according to a preset time period, and then one or more available transportation modes are decided from the previously used transportation modes as the alternative transportation mode between each node according to the obtained weather information in the future time period between each node.

[0014] According to an embodiment of the natural gas intermodal transport scheme planning method of the present invention, weather information includes precipitation, wind level and temperature; wherein the natural gas intermodal transport scheme planning method introduces a weather decision variable when deciding the alternative transportation mode between each node according to the precipitation, wind level and temperature between each node in a future time period. Using weather decision variables of transport mode k under different weather conditions To determine whether the transportation mode k between nodes i and j can be adopted, so as to decide the alternative transportation mode between each node;

[0015] like This means that transportation mode k can be used between nodes i and j;

[0016] like Then the transportation method k between table nodes i and j cannot be used.

[0017] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, the natural gas transportation modes include pipelines, railways, waterways and roads; wherein, after obtaining the precipitation, wind level and temperature between nodes i and j, the natural gas multimodal transport scheme planning method determines whether the corresponding transportation mode can be adopted according to the following preset weather decision variables of each transportation mode under different weather conditions:

[0018] (1) Weather decision variables for the railway k=2 between nodes i and j If the precipitation between nodes i and j is ≥50mm, or the precipitation is ≥5mm, the temperature is <0 and the wind level is ≥5, then Other weather conditions

[0019] (2) Weather decision variables for waterway k=3 between nodes i and j If the precipitation between nodes i and j is ≥25mm, the temperature is ≤-10℃ and the wind level is ≥4, then Other weather conditions

[0020] (3) Weather decision variables for road k=4 between nodes i and j If the precipitation between nodes i and j is ≥40mm, or the precipitation is ≥5mm, the temperature is <0 and the wind level is ≥5, then Other weather conditions

[0021] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, after the natural gas multimodal transport scheme planning method decides on the alternative transport mode between each node, the transportation costs corresponding to the different alternative transport modes between each node are calculated based on the alternative transport modes between each node, and then the multimodal transport scheme is planned based on the transportation costs corresponding to the different alternative transport modes between each node, so as to determine the final transportation mode between each node; wherein the transportation costs corresponding to the different alternative transport modes between each node include in-transit transportation costs, node transfer costs and transportation time costs.

[0022] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, the natural gas multimodal transport scheme planning method calculates the in-transit transport cost under different transport modes between nodes by the following formula:

[0023]

[0024] in, represents the in-transit transportation cost when transport mode k is used between nodes i and j;

[0025] is an in-transit decision variable, where It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j;

[0026] represents the unit transportation cost when transport mode k is used between nodes i and j,

[0027] q ijIt represents the freight volume between nodes i and j when transport mode k is used for transportation.

[0028] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, the natural gas multimodal transport scheme planning method calculates the transportation time cost B of the goods by the following formula:

[0029]

[0030]

[0031] Among them, P represents the total value of goods;

[0032] β represents the monthly depreciation rate of goods;

[0033] T represents the total transportation time of the goods;

[0034] K represents the total number of transport modes;

[0035] N represents the total number of transport nodes;

[0036] represents the in-transit transportation time between nodes i and j when transportation mode k is used;

[0037] is an in-transit decision variable, where It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j;

[0038] represents the transportation distance between nodes i and j using transportation mode k;

[0039] Indicates the transport speed under each mode of transport;

[0040] represents the node transit time of changing transport mode k to transport mode l at node j;

[0041] represents a transshipment decision variable, where if It means that at node j, transport mode k is changed to transport mode l. If This means that at node j, transport mode k is not changed to transport mode l;

[0042] It represents the node transit time of changing transport mode k to transport mode l at node j.

[0043] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, when calculating the total cargo transportation time T, the natural gas multimodal transport scheme planning method determines the actual transportation distance between nodes when different transportation modes are used according to different transportation modes, and uses the following strategies to calculate the transportation distance between nodes under different transportation modes:

[0044] If there is no transportation mode k between nodes i and j, that is When

[0045] If there is a transportation mode k between nodes i and j, that is When constant.

[0046] According to an embodiment of the natural gas intermodal transport scheme planning method of the present invention, when calculating the total cargo transportation time T, the natural gas intermodal transport scheme planning method uses trapezoidal fuzzy to represent the transportation speed under each transportation mode in view of the uncertainty of the transportation speed under each transportation mode. A transport speed variable w is introduced, and the transport speed under each transport mode is established according to the transport speed variable w as shown below: Trapezoidal fuzzy membership function Used for:

[0047]

[0048] in, represents the minimum speed under transport mode k,

[0049] represents the maximum speed under transport mode k,

[0050] Indicates the maximum speed under transport mode k 1 / 4,

[0051] Indicates the maximum speed under transport mode k 3 / 4 of.

[0052] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, the natural gas multimodal transport scheme planning method further introduces a definite number a and a trapezoidal fuzzy number when calculating the transport speed containing the trapezoidal fuzzy representation. According to the determination number a and the trapezoidal fuzzy number The fuzzy credibility function shown below is established to clarify the total cargo transportation speed v:

[0053]

[0054] Among them, b1 represents the minimum value of the transportation time that can be selected.

[0055] b2 represents a lower value of transportation time which is slightly higher than b1.

[0056] b3 represents a higher value of transportation time which is slightly lower than b4.

[0057] b4 indicates that the maximum value of the transportation time can be selected.

[0058] According to an embodiment of the natural gas intermodal transport scheme planning method of the present invention, when the natural gas intermodal transport scheme planning method uses the fuzzy credibility function to clarify the total cargo transportation time T, the total cargo transportation time T containing the transportation speed represented by the trapezoidal fuzzy expression is converted into the total cargo transportation time T with clear transportation speed through the transportation time clarification strategy set as follows:

[0059] When the credibility θ∈[0, 0.5], the fuzzy credibility That is, a-b1≥2θ(b2-b1), at this time, the cargo transportation speed v can be converted to

[0060] When it is credible that θ∈[0.5,1], the fuzzy credibility That is, b4-2b3+a≥2θ(b4-b3), at this time, the cargo transportation speed v can be converted to

[0061] According to an embodiment of the natural gas intermodal transportation scheme planning method of the present invention, after the natural gas intermodal transportation scheme planning method calculates the transportation costs corresponding to different alternative transportation modes between each node, a natural gas intermodal transportation scheme planning model is used to perform multimodal transportation scheme planning to obtain the best natural gas multimodal transportation scheme; wherein, when the natural gas multimodal transportation scheme planning model performs multimodal transportation scheme planning, the comprehensive transportation cost of completing the natural gas transportation is calculated based on the transportation costs corresponding to different alternative transportation modes between each node, and the minimum comprehensive transportation cost is used as the objective function, and the objective function is used to plan the multimodal transportation scheme with the minimum comprehensive transportation cost as the best natural gas multimodal transportation scheme.

[0062] According to an embodiment of the natural gas multimodal transport solution planning method of the present invention, the objective function of the natural gas multimodal transport solution planning model is as follows:

[0063]

[0064] Among them, minF represents the minimum comprehensive transportation cost;

[0065] K represents the total number of transport modes;

[0066] N represents the total number of transport nodes;

[0067] is an in-transit decision variable, if It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j;

[0068] represents the in-transit transportation cost when transport mode k is used between nodes i and j;

[0069] represents a transshipment decision variable, where if It means that at node j, transport mode k is changed to transport mode l. If This means that at node j, transport mode k is not changed to transport mode l;

[0070] represents the node transshipment cost of changing transport mode k to transport mode l at node j;

[0071] B represents the time cost of transporting goods.

[0072] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, when the natural gas multimodal transport scheme planning model performs multimodal transport scheme planning, an improved coronavirus herd immunity optimization algorithm is used to search for the best natural gas multimodal transport scheme, thereby obtaining the best natural gas multimodal transport scheme, including the following steps:

[0073] Step C1: Initialize the parameters of the coronavirus herd immunity optimization algorithm, including the maximum number of iterations Max_itr, problem dimension n, maximum age Max_Age, population size HIS, basic reproduction rate BR r , and the upper and lower limits ub and lb of the variables;

[0074] Step C2: Initialize the population according to the initialized problem dimension and population size HIS, and randomly initialize the state of each individual to obtain the two-dimensional population matrix shown below:

[0075]

[0076] Step C3: According to the basic reproduction rate BR r Perform immune evolution on each individual in the current population to obtain an evolved population;

[0077] Step C4: Update the herd immunity individuals based on the fitness value of each individual in the evolving population;

[0078] Step C5: Determine whether the maximum number of iterations Max_itr is reached; if so, end the loop and obtain the optimal natural gas multimodal transport plan; if not, repeat steps C3 to C4 until the maximum number of iterations Max_itr is reached.

[0079] According to an embodiment of the natural gas intermodal transport scheme planning method of the present invention, the states of individuals in the population include susceptible state, infected state and immune state. The natural gas intermodal transport scheme planning method introduces a random number when performing immune evolution on any individual in the population. According to the random number and the basic reproduction rate BR r The contrast relationship between them is to select the corresponding state update mode for any individual, so as to perform immune evolution on the individual; wherein, the natural gas multimodal transport scheme planning method selects the state update mode according to the following expression:

[0080]

[0081] in, represents the state value of the i-th individual under dimension j at the t-th iteration,

[0082] represents the state value of the i-th individual in dimension j at the t+1th iteration,

[0083] r represents a random number in [0, 1],

[0084] represents the state value of the i-th individual after being affected by an infected person xc in dimension j at the t-th iteration,

[0085] represents the state value of the i-th individual after being affected by a susceptible person xm under dimension j at the t-th iteration,

[0086] It represents the state value of the i-th individual after being affected by an immune person xv in dimension j at the t-th iteration.

[0087] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, the natural gas multimodal transport scheme planning method calculates the state value of a group of individuals after being affected by an infected person xc by the following formula:

[0088]

[0089] in, represents the state value of the i-th individual after being affected by an infected person xc in dimension j at the t-th iteration,

[0090] represents the state value of the i-th individual under dimension j at the t-th iteration,

[0091] r represents a random number in [0, 1],

[0092] Represents the state value of the infected person xc that affects the i-th individual.

[0093] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, the natural gas multimodal transport scheme planning method calculates the state value of a group of individuals after being affected by a susceptible person xm by the following formula:

[0094]

[0095] in, represents the state value of the i-th individual after being affected by a susceptible person xm under dimension j at the t-th iteration,

[0096] represents the state value of the i-th individual under dimension j at the t-th iteration,

[0097] r represents a random number in [0, 1],

[0098] Represents the state value of the susceptible person xm that affects the i-th individual.

[0099] According to an embodiment of the natural gas multimodal transport scheme planning method of the present invention, the natural gas multimodal transport scheme planning method calculates the state value of a group of individuals after being affected by an immune person xv by the following formula:

[0100]

[0101] in, represents the state value of the i-th individual in the t-th iteration after being affected by an immune person xv in dimension j,

[0102] represents the state value of the i-th individual under dimension j at the t-th iteration,

[0103] r represents a random number in [0, 1],

[0104] Represents the state value of the immune person xv that affects the i-th individual.

[0105] According to an embodiment of the natural gas intermodal transport scheme planning method of the present invention, after completing the immune evolution of individuals in the population, the natural gas intermodal transport scheme planning method determines whether to perform immune update on individuals in the current population by comparing the fitness values ​​of the individuals before and after evolution; wherein,

[0106] If the fitness value of individual i in the t+1th iteration is less than or equal to the fitness value in the t+1th iteration, no immune update is performed on individual i;

[0107] If the fitness value of individual i in the t+1th iteration is greater than the fitness value in the t+1th iteration, individual i is immune updated, that is,

[0108] The present invention also provides a computer readable medium storing a computer program code, wherein the computer program code implements the method as described above when executed by a processor.

[0109] The present invention also provides a natural gas multimodal transport scheme planning device, comprising:

[0110] a memory for storing instructions executable by a processor; and

[0111] A processor is used to execute the instructions to implement the method as described above.

[0112] Compared with the prior art, the present invention has the following beneficial effects: the present invention aims at the planning problem of natural gas multimodal transport scheme, collects weather information between nodes and sets a weather decision variable based on the transportation mode used, determines the alternative transportation mode between nodes through the preset weather decision variable, and then plans the multimodal transport scheme according to the transportation cost corresponding to the different alternative transportation modes between nodes, thereby obtaining the natural gas multimodal transport scheme with the minimum transportation cost under feasible conditions. Compared with the prior art, the present invention comprehensively considers the suspension of natural gas multimodal transport due to extreme weather and the uncertainty of transportation speed during transportation, takes the minimum comprehensive transportation cost of the whole transportation process as the goal, establishes a natural gas multimodal transport scheme planning model with carbon emissions, number of transshipments, etc. as constraints, and adopts the coronavirus herd immunity optimization algorithm to solve it, thereby making reasonable decisions for natural gas freight companies and logistics providers, optimizing transportation resources, and providing customers with efficient and sustainable natural gas transportation services. BRIEF DESCRIPTION OF THE DRAWINGS

[0113] The above features and advantages of the present invention can be better understood after reading the detailed description of the embodiments of the present disclosure in conjunction with the following drawings. In the drawings, the components are not necessarily drawn to scale, and components with similar related properties or features may have the same or similar reference numerals.

[0114] Figure 1 It is a flow chart showing an embodiment of a method for planning a natural gas multimodal transport scheme according to the present invention.

[0115] Figure 2A flowchart showing the steps of an embodiment of a coronavirus herd immunity optimization algorithm. DETAILED DESCRIPTION

[0116] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0117] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0118] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, method and equipment known to those of ordinary skill in the relevant field may not be discussed in detail, but in appropriate cases, the technology, method and equipment should be considered as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so that once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0119] When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional views showing the device structure will not be partially enlarged according to the general scale, and the schematic views are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0120] In the description of the present application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction, and therefore cannot be understood as limiting the scope of protection of the present application; the directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.

[0121] For ease of description, spatial relationship words such as "under", "below", "below", "below", "above", "on", etc. may be used here to describe the relationship between one element or feature shown in the drawings and other elements or features. It will be understood that these spatial relationship words are intended to include other directions of the device in use or operation in addition to the direction depicted in the drawings. For example, if the device in the drawings is turned over, the direction of the element described as being "under" or "under" or "below" other elements or features will be changed to "above" the other elements or features. Thus, the exemplary words "under" and "below" can include both the up and down directions. The device may also have other orientations (rotated 90 degrees or in other orientations), so the spatial relationship descriptors used here should be interpreted accordingly. In addition, it will be understood that when a layer is referred to as being "between" two layers, it can be the only layer between the two layers, or there can be one or more layers in between.

[0122] In the context of the present application, a structure in which a first feature is described as being "on" a second feature may include embodiments in which the first and second features are formed in direct contact, and may also include embodiments in which an additional feature is formed between the first and second features, such that the first and second features may not be in direct contact.

[0123] It should be understood that when a component is referred to as being "on another component," "connected to another component," "coupled to another component," or "contacting another component," it may be directly on, connected to, coupled to, or contacting the other component, or there may be intervening components. In contrast, when a component is referred to as being "directly on another component," "directly connected to," "directly coupled to," or "directly contacting" another component, there are no intervening components. Similarly, when a first component is referred to as being "electrically in contact with" or "electrically coupled to" a second component, there is an electrical path between the first component and the second component that allows current to flow. The electrical path may include capacitors, coupled inductors, and / or other components that allow current to flow, even without direct contact between conductive components.

[0124] In addition, it should be noted that the use of words such as "first" and "second" to define components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above words have no special meaning and cannot be understood as limiting the scope of protection of this application. In addition, although the terms used in this application are selected from well-known and commonly used terms, some terms mentioned in the specification of this application may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description of this article. In addition, it is required to understand this application not only by the actual terms used, but also by the meaning implied by each term.

[0125] Disclosed herein is an embodiment of a method for planning a natural gas multimodal transport solution. Figure 1 is a flow chart showing an embodiment of a method for planning a natural gas multimodal transport scheme according to the present invention. Figure 1 ,The following is a detailed description of each step of the natural gas multimodal transportation plan planning method.

[0126] Step S1: Collect transportation node information according to natural gas transportation demand.

[0127] Step S2: Determine the alternative transportation mode for each node based on the collected transportation node information.

[0128] In this embodiment, before planning the multimodal transport scheme of natural gas, considering the extreme weather during the natural gas transportation process, the transportation node information is collected according to the natural gas transportation demand, such as the cities to be passed, including the weather information between each node and the previously used transportation mode, so as to decide the alternative transportation mode between each node. Among them, when deciding the alternative transportation mode between each node, firstly, the weather information of each node in the future time period is obtained according to a preset time period, and then one or more available transportation modes are decided from the previously used transportation modes according to the obtained weather information in the future time period between each node as the alternative transportation mode between each node.

[0129] Specifically, in this embodiment, weather information includes precipitation, wind level, and temperature. When deciding the alternative transportation mode between nodes based on the precipitation, wind level, and temperature between nodes in the future time period, a weather decision variable is introduced. Using weather decision variables of transport mode k under different weather conditions To determine whether the transportation mode k between nodes i and j is available, so as to decide the alternative transportation mode between each node. This means that transportation mode k can be used between nodes i and j. Then the transportation method k between table nodes i and j cannot be used.

[0130] In one embodiment, there are four modes of natural gas transportation, namely pipeline, railway, waterway and road. After obtaining the weather information of each node in the next week by using Python tools, crawler algorithms and other means, the corresponding transportation mode is judged whether it can be adopted according to the obtained precipitation, wind level and temperature between nodes i and j, and the following preset weather decision variables of each transportation mode under different weather conditions:

[0131] (1) Weather decision variables for the railway k=2 between nodes i and j If the precipitation between nodes i and j is ≥50mm, or the precipitation is ≥5mm, the temperature is <0 and the wind level is ≥5, then Other weather conditions

[0132] (2) Weather decision variables for waterway k=3 between nodes i and j If the precipitation between nodes i and j is ≥25mm, the temperature is ≤-10℃ and the wind level is ≥4, then Other weather conditions

[0133] (3) Weather decision variables for road k=4 between nodes i and j If the precipitation between nodes i and j is ≥40mm, or the precipitation is ≥5mm, the temperature is <0 and the wind level is ≥5, then Other weather conditions

[0134] Step S3: Calculate the transportation costs corresponding to the different alternative transportation modes between the nodes according to the different alternative transportation modes between the nodes.

[0135] In this embodiment, after the alternative transportation modes between nodes are determined through the above steps, the transportation costs corresponding to the different alternative transportation modes between nodes are calculated according to the alternative transportation modes between nodes, and then the multimodal transportation plan is planned based on the transportation costs corresponding to the different alternative transportation modes between nodes, so as to determine the final transportation mode between nodes. Among them, the transportation costs corresponding to the different alternative transportation modes between nodes include in-transit transportation costs, node transfer costs and transportation time costs.

[0136] Specifically, in this embodiment, for the in-transit transportation costs under different transportation modes between nodes, the in-transit transportation costs under different transportation modes between nodes are calculated by the following formula:

[0137]

[0138] in, represents the in-transit transportation cost when transport mode k is used between nodes i and j; is an in-transit decision variable, where It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j. represents the unit transportation cost when transport mode k is used between nodes i and j, q ij It represents the freight volume between nodes i and j when transport mode k is used for transportation.

[0139] For the transportation time cost B (yuan) of goods, it is calculated based on the monthly depreciation rate of goods. The monthly depreciation rate refers to the percentage of the value of goods decreasing within a month. The longer the transportation time of goods, the more depreciation, which can be regarded as the transportation time cost of goods. Assuming that the same kind of goods are transported during the transportation process, the monthly depreciation rate of goods is constant, and each month is calculated as 30 days, the transportation time cost B (yuan) of goods is calculated by the following formula:

[0140]

[0141] Among them, P represents the total value of goods, β represents the monthly depreciation rate of goods, T represents the total transportation time of goods, K represents the total number of transportation modes, and N represents the total number of transportation nodes. It represents the in-transit time when transport mode k is used for transport between nodes i and j. is an in-transit decision variable, where It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j. represents the transportation distance between nodes i and j using transportation mode k; Indicates the transport speed under each mode of transport; It represents the node transit time of changing transport mode k to transport mode l at node j. represents a transshipment decision variable, where if It means that at node j, transport mode k is changed to transport mode l. If This means that at node j, transport mode k is not changed to transport mode l. It represents the node transit time of changing transport mode k to transport mode l at node j.

[0142] In this embodiment, for the total cargo transportation time T in the above formula, it is necessary to determine the actual transportation distance between nodes when different transportation modes are used according to different transportation modes, and the transportation distance between nodes under different transportation modes is determined by the following strategy:

[0143] (1) If there is no transportation mode k between nodes i and j, that is When

[0144] (2) If there is a transportation mode k between nodes i and j, that is When It remains unchanged and is consistent with the distance determined at the beginning.

[0145] In addition, in this embodiment, when calculating the total transportation time T of the goods, trapezoidal fuzzy is used to represent the transportation speed under each transportation mode in view of the uncertainty of the transportation speed under each transportation mode. A transport speed variable w is introduced, and the transport speed under each transport mode is established according to the transport speed variable w as shown below: Trapezoidal fuzzy membership function It helps quantify fuzziness so that fuzzy sets can accurately represent various possibilities under fuzzy or uncertain conditions, thereby supporting the application of fuzzy reasoning and decision-making processes. The expression is as follows:

[0146]

[0147] in, represents the minimum speed under transport mode k, represents the maximum speed under transport mode k, Indicates the maximum speed under transport mode k 1 / 4, Indicates the maximum speed under transport mode k 3 / 4 of.

[0148] At the same time, since the total cargo transportation time T contains the transportation speed expressed by trapezoidal fuzzy, the core idea of ​​chance-constrained programming theory is used to clarify the fuzzy variables and transform the model into a definite mathematical expression. Specifically, a definite number a and a trapezoidal fuzzy number are introduced. According to the determination number a and the trapezoidal fuzzy number The fuzzy credibility function shown below is established to clarify the total cargo transportation time T:

[0149]

[0150] Among them, b1 represents the minimum value that can be selected as the transportation time, usually the shortest possible time. b2 represents a lower but typical value as the transportation time, usually slightly higher than b1, indicating a faster possibility. b3 represents a higher but typical value as the transportation time, usually slightly lower than b4, indicating a slower possibility; b4 represents the maximum value that can be selected as the transportation time, usually the longest possible time.

[0151] In this embodiment, when the fuzzy credibility function is used to clarify the cargo transportation speed v, the following transportation speed clarification strategy is also required to convert the transportation speed with trapezoidal fuzzy representation into the cargo transportation speed v with clear transportation speed:

[0152] When the credibility θ∈[0, 0.5], the fuzzy credibility That is, a-b1≥2θ(b2-b1), at this time, the cargo transportation speed v can be converted to

[0153] When the credibility is θ∈[0.5, 1], the fuzzy credibility That is, b4-2b3+a≥2θ(b4-b3), at this time, the cargo transportation speed v can be converted to

[0154] Step S4: planning a multimodal transport solution based on the transport costs corresponding to different alternative transport modes between nodes to obtain the best multimodal transport solution for natural gas.

[0155] In this embodiment, after calculating the transportation costs corresponding to different alternative transportation modes between nodes through the above steps, a natural gas multimodal transportation plan planning model is used to plan the multimodal transportation plan to obtain the best natural gas multimodal transportation plan. Among them, when the natural gas multimodal transportation plan planning model plans the multimodal transportation plan, the comprehensive transportation cost of natural gas transportation is calculated based on the transportation costs corresponding to different alternative transportation modes between nodes, and the minimum comprehensive transportation cost is used as the objective function. The objective function is used to plan the multimodal transportation plan with the minimum comprehensive transportation cost as the best natural gas multimodal transportation plan.

[0156] Specifically, in this embodiment, the natural gas multimodal transport plan planning model uses the minimum comprehensive transportation cost as the objective function, and the expression is as follows:

[0157]

[0158] Among them, minF represents the minimum comprehensive transportation cost; K represents the total number of transportation modes and N represents the total number of transportation nodes. is an in-transit decision variable, if It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j. It represents the in-transit transportation cost when transport mode k is used between nodes i and j. represents a transshipment decision variable, where if It means that at node j, transport mode k is changed to transport mode l. If This means that at node j, transport mode k is not changed to transport mode l. represents the node transshipment cost of changing transport mode k to transport mode l at node j. B represents the transportation time cost of the goods. Among them, for the in-transit transportation cost Node transfer cost The specific calculation method of the transportation time cost B is shown above and will not be repeated here. When solving the natural gas multimodal transport planning model, in addition to considering the setting of in-transit decision variables and transshipment decision variables for the actual needs of natural gas transportation, the following constraints must also be followed:

[0159] (1) Carbon emission constraints:

[0160] (2) Continuity constraints for node transportation mode changes:

[0161] (3) There is only one mode of transportation between nodes:

[0162] (4) Only one transfer between nodes:

[0163] In one embodiment, an improved coronavirus herd immunity optimization algorithm is used to search for the best natural gas multimodal transport solution. Figure 2 For a flowchart showing an embodiment of the coronavirus herd immunity optimization algorithm, please refer to Figure 2 ,The following is a detailed description of each step of the coronavirus herd immunity optimization algorithm.

[0164] Step C1: Initialize the parameters of the coronavirus herd immunity optimization algorithm, including the maximum number of iterations Max_itr, problem dimension n, maximum age Max_Age, population size HIS, basic reproduction rate BR r , and the upper limit ub and lower limit lb of the variable.

[0165] Step C2: Initialize the population according to the initialized problem dimension and population size HIS, and randomly initialize the state of each individual to obtain the two-dimensional population matrix shown below:

[0166]

[0167] In this embodiment, each individual in the two-dimensional population matrix is ​​a multimodal transport plan for natural gas from the departure point to the destination. When initializing the population, the ant colony algorithm is used to determine the next visited city according to the pheromone concentration on the connection path of each node, and select the node path one by one to initialize the population. The individuals in the ant lion population refer to the order of passing cities in the transportation of goods.

[0168] Specifically, in the ant lion algorithm, its parameters include parameters: ant k (k = 1, 2, ..., HIS), pheromone concentration T τj (t), heuristic function η ij (t) = 1 / d ij α is the pheromone importance factor. The larger its value, the greater the role of pheromone concentration in migration. β is the heuristic function importance factor. The larger its value, the greater the role of heuristic function in migration, that is, ants will migrate to cities with a shorter distance with a greater probability. allow k (k=1,2,..,HIS) represents the set of cities to be visited by ant k. Definition represents the probability of ant k transferring from node i to node j at time t, then the probability formula for selecting the next city is:

[0169]

[0170] In addition, when performing path selection, two large loops are used to determine the path selection of each ant and each node. Among them, the outer loop is a loop of each ant (number of loops: HIS), and the inner loop is a loop of path selection of each city (number of loops: m). Therefore, after two loops, an initial matrix n×HIS is obtained, which represents HIS individuals traversing n nodes, that is, the complete path plan between the individuals in the population from the departure point to the destination.

[0171] Step C3: According to the basic reproduction rate BR r Perform immune evolution on each individual in the current population to obtain the evolved population.

[0172] In this embodiment, the state of each individual in the population is divided into susceptible state, infected state and immune state. When performing immune evolution on any individual in the population, a random number is introduced. According to the random number and the basic reproduction rate BR r The contrast relationship between them is used to select the corresponding state update method for any individual through the following expression, so as to perform immune evolution on the individual:

[0173]

[0174] in, represents the state value of the i-th individual under dimension j at the t-th iteration, represents the state value of the i-th individual in dimension j at the t+1th iteration, r represents a random number in [0, 1], Indicates the state value of the i-th individual in the t-th iteration after being affected by an infected person xc in dimension j represents the state value of the i-th individual after being affected by a susceptible person xm under dimension j at the t-th iteration, It represents the state value of the i-th individual after being affected by an immune person xv in dimension j at the t-th iteration.

[0175] Specifically, from the above expression, we can know that when the generated random number r≥BR r When , the state value of the individual in the next iteration t+1 is unchanged, the state value of the individual in the previous iteration t Consistent.

[0176] When the random number generated When the individual is in an infected state, the state value of the individual in the next iteration t+1 is affected by an infected person xc, and its state value for The calculation formula is as follows:

[0177]

[0178] in, represents the state value of the i-th individual after being affected by an infected person xc in dimension j at the t-th iteration, represents the state value of the i-th individual in dimension j at the t-th iteration, r represents a random number in [0, 1], Represents the state value of the infected person xc that affects the i-th individual.

[0179] When the random number generated When the individual is in a susceptible state, the state value of the individual in the next iteration t+1 is affected by a susceptible person xm, and its state value for The calculation formula is as follows:

[0180]

[0181] in, represents the state value of the i-th individual after being affected by a susceptible person xm under dimension j at the t-th iteration, represents the state value of the i-th individual in dimension j at the t-th iteration, r represents a random number in [0, 1], Represents the state value of the susceptible person xm that affects the i-th individual.

[0182] When the generated random number r <BR r When the individual is in an immune state, the state value of the individual in the next iteration t+1 is affected by an immune person xv, and its state value for The calculation formula is as follows:

[0183]

[0184] in, represents the state value of the i-th individual in the t-th iteration after being affected by an immune person xv in dimension j,

[0185] represents the state value of the i-th individual under dimension j at the t-th iteration,

[0186] r represents a random number in [0, 1],

[0187] Represents the state value of the immune person xv that affects the i-th individual.

[0188] Step C4: Update the herd immunity individuals based on the fitness value of each individual in the evolving population.

[0189] In this embodiment, after completing the immune evolution of the individuals in the population through the above steps, it is necessary to determine whether to perform immune update on the individuals in the current population by comparing the fitness values ​​of the individuals before and after evolution. If the fitness value of the individual in the t+1th iteration is less than or equal to the fitness value in the tth iteration, that is, Then the individual's immune system is updated, x j (t) = x' j (t+1). If the fitness value of individual i in the t+1 iteration is greater than the fitness value in the t iteration, that is No immune update is performed on the individual.

[0190] In addition, in this embodiment, in order to enhance the ability of individuals to explore the solution space, some modifications are made to the population individuals. By modifying the formula X ~ U (- 1 , 1 ) to control the individual to approach or move away from the selected individual (same state, that is, the same S), the formula is as follows:

[0191] x' i，j =x i，j +X~U(-1,1)×(x i，j -x selected,j )

[0192] At the same time, in order to prevent the coronavirus herd immunity optimization algorithm from falling into a local optimum, this embodiment also uses the Meteopolis criterion in the simulated annealing algorithm to determine the acceptance of the new solution and adjust the age of the individual. Assuming x is the current solution, x' is the new solution, T0 is the initial temperature, and q is the cooling rate, then the change of T is as follows:

[0193] T=T0·q t

[0194] At this time, the probability of accepting the new solution in the Meteopolis criterion is:

[0195]

[0196] Where f(x) represents the fitness function, i.e., the objective function in the problem model. In the case of f(x′)≥f(x), a probability r=X~U(0,1) is randomly generated. If If yes, then the new solution is accepted; otherwise, then the new solution is not accepted.

[0197] Step C5: Determine whether the maximum number of iterations Max_itr is reached; if so, end the loop and obtain the optimal natural gas multimodal transport plan; if not, repeat steps C3 to C4 until the maximum number of iterations Max_itr is reached.

[0198] Step S5: transporting natural gas according to the transportation mode between nodes planned in the optimal natural gas multimodal transport plan.

[0199] In this embodiment, the optimal natural gas multimodal transport plan is obtained through the above steps, and natural gas is transported according to the transportation mode of each node determined by the optimal natural gas multimodal transport plan, so that multimodal transport is carried out according to the plan with the lowest transportation cost when the weather permits.

[0200] This specification also provides a computer-readable medium storing a computer program code, which, when executed by a processor, implements the natural gas multimodal transport plan planning method as described above.

[0201] This specification also provides a natural gas multimodal transport scheme planning device, including an instruction memory for storing instructions executable by a processor, and a processor for executing instructions in the instruction memory to implement the natural gas multimodal transport scheme planning method as described above.

[0202] The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein, but should be granted the widest scope consistent with the principles and novel features disclosed herein.

[0203] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or a combination of the two. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. The technician may implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention.

[0204] The various illustrative logic blocks, modules, and circuits described in conjunction with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in cooperation with a DSP core, or any other such configuration.

[0205] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, a storage medium may be integrated into a processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside in a user terminal as discrete components.

[0206] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, each function may be stored on or transmitted by a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one place to another. Storage media may be any available medium that can be accessed by a computer. As an example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, a server, or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. Disk and disc as used herein include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wherein disk often reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

Claims

1. A method for planning a natural gas multimodal transport solution, characterized in that: The following steps are involved: Step S1: Collecting transportation node information according to natural gas transportation demand; Step S2: Determine the alternative transportation mode between nodes based on the collected transportation node information; Step S3: calculating the transportation costs corresponding to different alternative transportation modes between nodes according to different alternative transportation modes between nodes; Step S4: planning a multimodal transport solution based on the transport costs corresponding to different alternative transport modes between nodes to obtain the best multimodal transport solution for natural gas; as well as Step S5: transporting natural gas according to the transportation mode between nodes planned in the optimal natural gas multimodal transport plan.

2. The method for planning a natural gas multimodal transport solution according to claim 1, characterized in that: The transportation node information includes weather information between each node and previously used transportation methods; wherein, when the natural gas multimodal transport scheme planning method decides on alternative transportation methods between each node, weather information of each node in a future time period is obtained according to a preset time period, and then one or more available transportation methods are decided from previously used transportation methods based on the obtained weather information in the future time period between each node as alternative transportation methods between each node.

3. The method for planning a natural gas multimodal transport solution according to claim 2, characterized in that: Weather information includes precipitation, wind level and temperature; wherein, the natural gas multimodal transport plan planning method introduces a weather decision variable when deciding the alternative transportation mode between each node according to the precipitation, wind level and temperature between each node in a future time period. Using weather decision variables of transport mode k under different weather conditions To determine whether the transportation mode k between nodes i and j can be adopted, so as to decide the alternative transportation mode between each node; like This means that transportation mode k can be used between nodes i and j; like Then the transportation method k between table nodes i and j cannot be used.

4. The method for planning a natural gas multimodal transport solution according to claim 3, characterized in that: The transportation modes of natural gas include pipelines, railways, waterways and roads; wherein, after obtaining the precipitation, wind level and temperature between nodes i and j, the natural gas multimodal transport scheme planning method determines whether the corresponding transportation mode can be adopted according to the following preset weather decision variables of each transportation mode under different weather conditions: (1) Weather decision variables for the railway k=2 between nodes i and j If the precipitation between nodes i and j is ≥50mm, or the precipitation is ≥5mm, the temperature is <0 and the wind level is ≥5, then Other weather conditions (2) Weather decision variables for waterway k=3 between nodes i and j If the precipitation between nodes i and j is ≥ 25 mm, the temperature is ≤ -10°C and the wind level is ≥ 4, then Other weather conditions (3) Weather decision variables for road k=4 between nodes i and j If the precipitation between nodes i and j is ≥40mm, or the precipitation is ≥5mm, the temperature is <0 and the wind level is ≥5, then Other weather conditions 5. The method for planning a natural gas multimodal transport solution according to claim 1, characterized in that: After deciding on the alternative transportation modes between nodes, the natural gas multimodal transport scheme planning method calculates the transportation costs corresponding to different alternative transportation modes between nodes according to the alternative transportation modes between nodes, and then plans the multimodal transport scheme based on the transportation costs corresponding to different alternative transportation modes between nodes, so as to determine the final transportation mode between nodes; among which, the transportation costs corresponding to different alternative transportation modes between nodes include in-transit transportation costs, node transshipment costs and transportation time costs.

6. The method for planning a natural gas multimodal transport solution according to claim 5, characterized in that: The natural gas multimodal transport plan planning method calculates the in-transit transportation cost under different transportation modes between nodes through the following formula: in, represents the in-transit transportation cost when transport mode k is used between nodes i and j; is an in-transit decision variable, where It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j; represents the unit transportation cost when transport mode k is used between nodes i and j, q ij It represents the freight volume between nodes i and j when transport mode k is used for transportation.

7. The method for planning a natural gas multimodal transport solution according to claim 5, characterized in that: The natural gas multimodal transport plan planning method calculates the transportation time cost B of the goods by the following formula: Among them, P represents the total value of goods; β represents the monthly depreciation rate of goods; T represents the total transportation time of the goods; K represents the total number of transport modes; N represents the total number of transport nodes; represents the in-transit transportation time between nodes i and j when transportation mode k is used; is an in-transit decision variable, where It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j; represents the transportation distance between nodes i and j using transportation mode k; Indicates the transport speed under each mode of transport; represents the node transit time of changing transport mode k to transport mode l at node j; represents a transshipment decision variable, where if It means that at node j, transport mode k is changed to transport mode l. If This means that at node j, transport mode k is not changed to transport mode l; It represents the node transit time of changing transport mode k to transport mode l at node j.

8. The method for planning a natural gas multimodal transport solution according to claim 7, characterized in that: When calculating the total cargo transportation time T, the natural gas multimodal transport plan planning method determines the actual transportation distance between nodes when different transportation modes are used according to different transportation modes, and uses the following strategies to calculate the transportation distance between nodes under different transportation modes: If there is no transportation mode k between nodes i and j, that is When If there is a transportation mode k between nodes i and j, that is When constant.

9. The method for planning a natural gas multimodal transport solution according to claim 7, characterized in that: When calculating the total cargo transportation time T, the natural gas multimodal transport planning method adopts trapezoidal fuzzy to represent the transportation speed under each transportation mode in view of the uncertainty of the transportation speed under each transportation mode. A transport speed variable w is introduced, and the transport speed under each transport mode is established according to the transport speed variable w as shown below: Trapezoidal fuzzy membership function Used for: in, represents the minimum speed under transport mode k, represents the maximum speed under transport mode k, Indicates the maximum speed under transport mode k 1 / 4, Indicates the maximum speed under transport mode k 3 / 4 of.

10. The method for planning a natural gas multimodal transport solution according to claim 7, characterized in that: The natural gas multimodal transport planning method also introduces a definite number a and a trapezoidal fuzzy number when calculating the transport speed with trapezoidal fuzzy representation. According to the determination number a and the trapezoidal fuzzy number The fuzzy credibility function shown below is established to clarify the total cargo transportation speed v: Among them, b1 represents the minimum value of the transportation time that can be selected. b2 represents a lower value of transportation time which is slightly higher than b1. b3 represents a higher value of transportation time which is slightly lower than b4. b4 indicates that the maximum value of the transportation time can be selected.

11. The method for planning a natural gas multimodal transport solution according to claim 7, characterized in that: When the natural gas multimodal transport scheme planning method uses the fuzzy credibility function to clarify the total cargo transportation time T, the total cargo transportation time T with the transportation speed represented by the trapezoidal fuzzy expression is converted into the total cargo transportation time T with a clear transportation speed through the transportation time clarification strategy set as follows: When the credibility θ∈[0,0.5], the fuzzy credibility That is, a-b1≥2θ(b2-b1), at this time, the cargo transportation speed v can be converted to When it is credible that θ∈[0.5,1], the fuzzy credibility That is, b4-2b3+a≥2θ(b4-b3), at this time, the cargo transportation speed v can be converted to 12. The method for planning a natural gas multimodal transport solution according to claim 5, characterized in that: The natural gas intermodal transport scheme planning method calculates the transportation costs corresponding to different alternative transport modes between nodes, and then uses a natural gas intermodal transport scheme planning model to plan the multimodal transport scheme to obtain the optimal natural gas intermodal transport scheme; wherein, when the natural gas intermodal transport scheme planning model plans the multimodal transport scheme, the comprehensive transportation cost of completing the natural gas transportation is calculated based on the transportation costs corresponding to different alternative transport modes between nodes, and the minimum comprehensive transportation cost is used as the objective function, and the objective function is used to plan the multimodal transport scheme with the minimum comprehensive transportation cost as the optimal natural gas intermodal transport scheme.

13. The method for planning a natural gas multimodal transport solution according to claim 12, characterized in that: The objective function of the natural gas multimodal transport solution planning model is as follows: Among them, minF represents the minimum comprehensive transportation cost; K represents the total number of transport modes; N represents the total number of transport nodes; is an in-transit decision variable, if It means that the transportation between nodes i and j is carried out by transportation mode k. This means that transport mode k is not used for transportation between nodes i and j; represents the in-transit transportation cost when transport mode k is used between nodes i and j; represents a transshipment decision variable, where if It means that at node j, transport mode k is changed to transport mode l. If This means that at node j, transport mode k is not changed to transport mode l; represents the node transshipment cost of changing transport mode k to transport mode l at node j; B represents the time cost of transporting goods.

14. The method for planning a natural gas multimodal transport solution according to claim 12, characterized in that: When planning a multimodal transport plan, an improved coronavirus herd immunity optimization algorithm is used to find the best natural gas multimodal transport plan, which includes the following steps: Step C1: Initialize the parameters of the coronavirus herd immunity optimization algorithm, including the maximum number of iterations Max_itr, problem dimension n, maximum age Max_Age, population size HIS, basic reproduction rate BR r , and the upper and lower limits ub and lb of the variables; Step C2: Initialize the population according to the initialized problem dimension and population size HIS, and randomly initialize the state of each individual to obtain the two-dimensional population matrix shown below: Step C3: According to the basic reproduction rate BR r Perform immune evolution on each individual in the current population to obtain an evolved population; Step C4: Update the herd immunity individuals based on the fitness value of each individual in the evolving population; Step C5: Determine whether the maximum number of iterations Max_itr is reached; if so, end the loop and obtain the optimal natural gas multimodal transport plan; if not, repeat steps C3 to C4 until the maximum number of iterations Max_itr is reached.

15. The method for planning a natural gas multimodal transport solution according to claim 14, characterized in that: The states of individuals in the population include susceptible state, infected state and immune state. The natural gas multimodal transport plan planning method introduces a random number when performing immune evolution on any individual in the population. According to the random number and the basic reproduction rate BR r The contrast relationship between them is to select the corresponding state update mode for any individual, so as to perform immune evolution on the individual; wherein, the natural gas multimodal transport scheme planning method selects the state update mode according to the following expression: in, represents the state value of the i-th individual under dimension j at the t-th iteration, represents the state value of the i-th individual in dimension j at the t+1th iteration, r represents a random number in [0,1], represents the state value of the i-th individual after being affected by an infected person xc in dimension j at the t-th iteration, represents the state value of the i-th individual after being affected by a susceptible person xm under dimension j at the t-th iteration, It represents the state value of the i-th individual after being affected by an immune person xv in dimension j at the t-th iteration.

16. The method for planning a natural gas multimodal transport solution according to claim 15, characterized in that: The natural gas multimodal transport scheme planning method calculates the state value of a group of individuals after being affected by an infected person xc by the following formula: in, represents the state value of the i-th individual after being affected by an infected person xc in dimension j at the t-th iteration, represents the state value of the i-th individual under dimension j at the t-th iteration, r represents a random number in [0,1], Represents the state value of the infected person xc that affects the i-th individual.

17. The method for planning a natural gas multimodal transport solution according to claim 15, characterized in that: The natural gas multimodal transport scheme planning method calculates the state value of a group of individuals after being affected by a susceptible person xm by the following formula: in, represents the state value of the i-th individual after being affected by a susceptible person xm under dimension j at the t-th iteration, represents the state value of the i-th individual under dimension j at the t-th iteration, r represents a random number in [0,1], Represents the state value of the susceptible person xm that affects the i-th individual.

18. The method for planning a natural gas multimodal transport solution according to claim 15, characterized in that: The method for planning a multimodal natural gas transport solution calculates the state value of a group of individuals after being affected by an immune person xv by the following formula: in, represents the state value of the i-th individual in the t-th iteration after being affected by an immune person xv in dimension j, represents the state value of the i-th individual under dimension j at the t-th iteration, r represents a random number in [0,1], Represents the state value of the immune person xv that affects the i-th individual.

19. The method for planning a natural gas multimodal transport solution according to claim 14, characterized in that: After the natural gas multimodal transport scheme planning method completes the immune evolution of the individuals in the population, it determines whether to perform immune update on the individuals in the current population by comparing the fitness values ​​of the individuals before and after the evolution; wherein, If the fitness value of individual i in the t+1th iteration is less than or equal to the fitness value in the t+1th iteration, no immune update is performed on individual i; If the fitness value of individual i in the t+1th iteration is greater than the fitness value in the t+1th iteration, individual i is immune updated, that is, 20. A computer readable medium storing computer program code, characterized in that: The computer program code implements the method according to any one of claims 1 to 19 when executed by a processor.

21. A natural gas multimodal transport plan planning device, characterized in that: include: a memory for storing instructions executable by a processor; as well as A processor, configured to execute the instructions to implement the method according to any one of claims 1 to 19.

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