LNG marine transportation path planning data processing method, device and electronic equipment

Abstract

Embodiments of the present application provide an LNG marine transportation path planning data processing method, device and electronic equipment. The method comprises: obtaining decision reference data associated with LNG marine transportation path planning, the decision reference data comprising at least annual transportation plan data, ship data, route data, and port state data; constructing a mixed integer programming model and defining a target function and a constraint function associated with LNG marine transportation path planning in the mixed integer programming model; and outputting LNG marine transportation path planning data based on the decision reference data through the mixed integer programming model. The technical solution of the embodiments of the present application can improve the accuracy of LNG marine transportation path planning data processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computers and logistics, in particular to an LNG marine transportation path planning data processing method and device, medium and electronic equipment. BACKGROUND

[0002] Liquified Natural Gas (LNG) is a clean, efficient and environmentally friendly energy source, and is increasingly valued by people. LNG marine transportation is an important link in the LNG supply chain, and the optimization of its transportation path directly affects the efficiency and safety of the entire supply chain. Existing LNG marine transportation path planning is mainly based on experience and professional knowledge, but the LNG marine transportation path planning problem involves multiple factors, such as ship navigation route, loading and unloading port selection, transportation cost, etc. Each factor is mutually constrained, and it is difficult to ensure the scientificity and accuracy of transportation path planning data processing based on experience and professional knowledge. Therefore, how to improve the accuracy of transportation path planning data processing is a technical problem to be solved. SUMMARY

[0003] Embodiments of the present application provide an LNG marine transportation path planning data processing method, device, computer program product or computer program, computer readable medium and electronic equipment, thereby at least to some extent improving the accuracy of LNG marine transportation path planning data processing.

[0004] Other characteristics and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0005] According to an aspect of an embodiment of the present application, an LNG marine transportation path planning data processing method is provided, the method comprising: obtaining decision reference data associated with LNG marine transportation path planning, the decision reference data comprising at least annual transportation plan data, ship data, route data, and port state data; constructing a mixed integer programming model and defining a target function and a constraint function associated with LNG marine transportation path planning in the mixed integer programming model; and outputting LNG marine transportation path planning data based on the decision reference data through the mixed integer programming model.

[0006] In some embodiments of the present application, based on the foregoing scheme, the following target function is defined in the mixed integer programming model:

[0007]

[0008] wherein obj represents the minimum value of the sum of full load durations allocated to virtual ships to execute transportation plans; FOB represents a set of real transportation plans. denotes a 0-1 integer variable, which takes value 1 if the transport plan s configures the virtual ship k, and 0 otherwise, k artificial denotes a virtual ship; denotes the time when the transport plan s arrives at the unloading port; denotes the unloading duration of the transport plan s; denotes the time when the transport plan s arrives at the loading port.

[0009] In some embodiments of the present application, based on the foregoing scheme, the following constraint function is defined in the mixed integer programming model:

[0010]

[0011] wherein, z s,k denotes a 0-1 integer variable, which takes value 1 if the transport plan s configures the ship k, and 0 otherwise; FOB' {s} denotes the set of real transport plans and virtual transport plans excluding the transport plan s; denotes a 0-1 integer variable, which takes value 1 if the transport plan i and the transport plan s both configure the ship k and are continuously performed, and 0 otherwise; FOB denotes the set of real transport plans; K denotes the set of self-owned ships and leased ships.

[0012] In some embodiments of the present application, based on the foregoing scheme, the following constraint function is defined in the mixed integer programming model:

[0013]

[0014] wherein, K denotes the set of self-owned ships and leased ships; q k denotes the capacity of the ship k; z s,k denotes a 0-1 integer variable, which takes value 1 if the transport plan s configures the ship k, and 0 otherwise; q s denotes the loading / unloading volume of the transport plan s; FOB denotes the set of real transport plans.

[0015] In some embodiments of the present application, based on the foregoing scheme, the following constraint function is defined in the mixed integer programming model:

[0016]

[0017] wherein, K denotes the set of self-owned ships and leased ships; K artificial denotes the set of virtual ships; z s,k denotes a 0-1 integer variable, which takes value 1 if the transport plan s configures the ship k, and 0 otherwise; FOB denotes the set of real transport plans. denotes a 0-1 integer variable, which is 1 if the ship k is configured to execute the transportation plan s, and 0 otherwise; k s denotes a ship that executes the transportation plan s; s match denotes a set of transportation plans that can be matched to the ship at present.

[0018] In some embodiments of the present application, based on the foregoing scheme, the following constraint function is defined in the mixed integer programming model:

[0019]

[0020] wherein z s,k denotes a 0-1 integer variable, which is 1 if the ship k is configured to execute the transportation plan s, and 0 otherwise; FOB denotes a set of real transportation plans; denotes a set of ships that are prohibited to stop at the unloading port of the transportation plan s and the loading port of the transportation plan s.

[0021] In some embodiments of the present application, based on the foregoing scheme, the following constraint function is defined in the mixed integer programming model:

[0022]

[0023] wherein z s,k denotes a 0-1 integer variable, which is 1 if the ship k is configured to execute the transportation plan s, and 0 otherwise; denotes the distance between the unloading port of the transportation plan s and the loading port of the transportation plan s; denotes the maximum sailing speed of the ship k; denotes the time when the transportation plan s arrives at the unloading port; denotes the unloading duration of the transportation plan s; denotes the time when the transportation plan s arrives at the loading port; FOB denotes a set of real transportation plans; K denotes a set of self-owned ships and leased ships; K artificial denotes a set of virtual ships.

[0024] According to an aspect of an embodiment of the present application, there is provided a LNG marine transportation path planning data processing device, which comprises: an acquisition unit configured to acquire decision reference data associated with LNG marine transportation path planning, the decision reference data at least including annual transportation plan data, ship data, route data, and port state data; a construction unit configured to construct a mixed integer programming model and define a target function and a constraint function associated with LNG marine transportation path planning in the mixed integer programming model; and an output unit configured to output LNG marine transportation path planning data based on the decision reference data by using the mixed integer programming model.

[0025] According to an aspect of an embodiment of the present application, a computer program product or computer program including computer instructions stored in a computer readable storage medium is provided. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the method described in the above embodiments.

[0026] According to an aspect of an embodiment of the present application, a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the method described in the above embodiments is provided.

[0027] According to an aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage apparatus configured to store one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the method described in the above embodiments.

[0028] In the present application, on the one hand, the LNG marine transportation path planning data processing scheme proposed in the present application can output a ship scheduling scheme under the minimum chartering time, so as to reduce the ship chartering cost and further reduce the LNG transportation cost. On the other hand, based on the LNG marine transportation path optimization model of mixed integer programming, by comprehensively considering the annual transportation plan data, ship data, route data, port state data, and various constraint conditions and optimization objectives, a more optimized LNG marine transportation path can be obtained, which improves the accuracy of the LNG marine transportation path planning data processing and improves the transportation efficiency and safety.

[0029] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present application. BRIEF DESCRIPTION OF DRAWINGS

[0030] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application. It is clear that the accompanying drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings. In the drawings:

[0031] Figure 1 A flow chart of a LNG marine transportation path planning data processing method according to an embodiment of the present application is shown;

[0032] Figure 2 A block diagram of a LNG marine transportation path planning data processing apparatus according to an embodiment of the present application is shown;

[0033] Figure 3 A structural diagram of a computer system of an electronic device suitable for implementing embodiments of the present application is shown. DETAILED DESCRIPTION

[0034] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations may, however, be implemented in many different forms and should not be construed as limited to the examples set forth herein; rather, these implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of example implementations to those skilled in the art.

[0035] Moreover, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the

[0036] The block diagrams in the drawings show only the functionality of the embodiments and do not necessarily imply a physical or an architectural arrangement of the embodiments. That is, the functionality can be implemented in software, hardware, or a combination thereof. The embodiments can be implemented in one or more hardware components or integrated circuits, or in a computer system comprising one or more processors, or in a computer system comprising one or more microprocessors.

[0037] The flow diagrams depicted in the drawings show the functionality of example embodiments and do not necessarily imply a sequential order of operations, or a necessity of combinations of elements. That is, elements can occur in various orders and / or various elements can be combined or omitted.

[0038] It should be noted that reference to a "plurality" herein means two or more. The term "and / or" describes associative relationships between associated objects and means that three relationships can exist, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally means that the associated objects before and after the " / " have an "or" relationship.

[0039] It should be noted that the terms "first", "second", and the like, used in the description and the claims of the present application and the above-described drawings, are used to distinguish similar objects and are not necessarily used to describe a particular sequential or chronological order. It should be understood that the objects thus used can be interchanged, where appropriate, so that the embodiments of the present application described herein can be implemented in other than the order illustrated or described.

[0040] In order for those skilled in the art to better understand the present application, before the specific description of the present scheme, the application scenario of the LNG marine transportation path planning scheme will be simply described below.

[0041] LNG marine transportation is an important link in the LNG supply chain, and the optimization of its transportation path directly affects the efficiency and safety of the entire supply chain. In order to solve the problems existing in the traditional method, the present application models and solves the LNG marine transportation path problem based on mixed integer programming of mathematical modeling and optimization algorithm. Mixed integer programming can handle some optimization problems of discrete variables and continuous variables by combining integer programming and linear programming, and has high calculation accuracy and stability.

[0042] In the scenario of LNG marine transportation path planning, each transportation plan needs to be matched with a corresponding ship to execute the transportation plan. The transportation plan includes a real transportation plan and a virtual transportation plan. The real transportation plan refers to a transportation plan that has been determined, such as transporting liquefied natural gas from one loading port to another unloading port in a certain time interval. The virtual transportation plan is a hypothetical transportation plan. Each ship corresponds to a virtual transportation plan, which has a corresponding starting port and key port. It should be noted that the present application defines the concept of virtual transportation plan, which is for the purpose of applying mixed integer programming model, and is irrelevant to the actual business in the application scenario. In the present application, the ship includes self-owned ship, leased ship and virtual ship. The self-owned ship refers to the ship owned by the enterprise itself. The leased ship refers to the ship leased by the enterprise. The virtual ship refers to the ship that the enterprise needs but does not own or lease. It should be noted that the enterprise needs to pay a certain lease fee for leasing a ship.

[0043] Figure 1 A flowchart of a LNG marine transportation path planning data processing method according to an embodiment of the present application is shown, which can be executed by a device with computing processing function. Referring to Figure 1 The LNG marine transportation path planning data processing method at least includes steps 110 to 130, which are described in detail as follows:

[0044] In step 110, decision reference data associated with LNG marine transportation path planning is obtained, which at least includes annual transportation plan data, ship data, route data, and port state data.

[0045] In the present application, the annual transportation plan data can include what transportation plans the enterprise needs to perform in the next year, etc. The ship data can include the size of the ship, the maximum and minimum speed, and the right to sail to various countries, etc. The route data can include the routes that can be selected to perform each transportation plan, etc. The port state data can include the water depth of the loading port and the unloading port, the ship allowed to stop, etc.

[0046] With reference to the foregoing Figure 1 In step 120, a mixed integer programming model is constructed, and a target function and a constraint function associated with the LNG sea transportation path planning are defined in the mixed integer programming model.

[0047] In the present application, the mixed integer model constructed by constructing the mixed integer programming model can be expressed as z s,k And As a decision variable, wherein z s,k Indicates a 0-1 integer variable, if the transportation plan s configures the ship k, it takes the value 1, otherwise it takes the value 0; Indicates a 0-1 integer variable, if the transportation plan i and the transportation plan s both configure the ship k, and the transportation plan i and the transportation plan s are continuously performed, it takes the value 1, otherwise it takes the value 0.

[0048] In an embodiment of the present application, the full load time (such as the number of days) of the chartered ship is minimized under the premise of meeting all transportation plans, that is, the sum of the full load time of the transportation task assigned to the virtual ship is minimized, and the target function is as follows formula (1):

[0049] Wherein, obj represents the minimum value of the sum of the full load time of the transportation task assigned to the virtual ship; FOB represents the set of real transportation plans; Indicates a 0-1 integer variable, if the transportation plan s configures the virtual ship k, it takes the value 1, otherwise it takes the value 0, k artificial Indicates the virtual ship number; Indicates the time when the transportation plan s arrives at the unloading port; Indicates the unloading time of the transportation plan s; Indicates the time when the transportation plan s arrives at the loading port.

[0050] In the present application, under the premise of ensuring the completion of all loading and unloading tasks, by minimizing the full load days of the chartered ship as the target, an integer programming model is constructed by using operational research knowledge to reasonably schedule and plan the transportation path of the enterprise's own ship. The advantage is that it can reduce the leasing cost of the ship, thereby reducing the entire transportation cost and improving the economic benefit of the enterprise.

[0051] In an embodiment of the present application, constraints can be imposed on the coupling of decision variables, for the decision variables of matching ships to execute transport plans, and the decision variables of ship continuity to execute transport plans, the constraint functions are as follows formula (2):

[0052]

[0053] Wherein, z s,k represents a 0-1 integer variable, if the transport plan s configures the ship k, it takes the value of 1, otherwise it takes the value of 0; FOB' {s} represents the set of real transport plans and virtual transport plans excluding the transport plan s; represents a 0-1 integer variable, if the transport plan i and the transport plan s both configure the ship k, and the transport plan i and the transport plan s are executed continuously, it takes the value of 1, otherwise it takes the value of 0; FOB represents the set of real transport plans; K represents the set of self-owned ships and leased ships.

[0054] In an embodiment of the present application, constraints can also be imposed on the ship cargo, that is, the loading / unloading capacity of the ship when executing the transport plan is less than the capacity of the ship, the constraint function is as follows formula (3):

[0055]

[0056] Wherein, K represents the set of self-owned ships and leased ships; q k represents the capacity of the ship k; z s,k represents a 0-1 integer variable, if the transport plan s configures the ship k, it takes the value of 1, otherwise it takes the value of 0; q s represents the loading / unloading capacity of the transport plan s; FOB represents the set of real transport plans.

[0057] In an embodiment of the present application, constraints can also be imposed on the number of ships and matching, that is, each transport plan s is executed by one ship, the constraint function is as follows formula (4):

[0058]

[0059] Wherein, K represents the set of self-owned ships and leased ships; K artificial represents the set of virtual ships; z s,k represents a 0-1 integer variable, if the transport plan s configures the ship k, it takes the value of 1, otherwise it takes the value of 0; FOB represents the set of real transport plans.

[0060] For the transport plan s that has matched the ship, set its ship as unchangeable, the constraint function is as follows formula (5):

[0061]

[0062] wherein, denotes a 0-1 integer variable, which takes the value of 1 if the ship k is configured to execute the transportation plan s, otherwise takes the value of 0; k s denotes the ship that executes the transportation plan s; s match denotes the set of transportation plans that can be matched to the ship at the current time.

[0063] In an embodiment of the present application, the 4. port ship matching constraint

[0064] For some reasons, some ports have a set of forbidden ships, and the constraint function is as follows formula (6):

[0065]

[0066] wherein, z s,k denotes a 0-1 integer variable, which takes the value of 1 if the ship k is configured to execute the transportation plan s, otherwise takes the value of 0; FOB denotes the set of real transportation plans; denotes the set of ships forbidden to stop at the unloading port of the transportation plan s and the loading port of the transportation plan s.

[0067] In an embodiment of the present application, the speed range of the ship can also be constrained, that is, the full load sailing time of the ship that executes the transportation plan s has upper and lower limit constraints, and the constraint function is as follows formula (7):

[0068]

[0069] wherein, z s,k denotes a 0-1 integer variable, which takes the value of 1 if the ship k is configured to execute the transportation plan s, otherwise takes the value of 0; denotes the distance between the unloading port and the loading port of the transportation plan s;

[0070] denotes the maximum sailing speed of the ship k; denotes the time when the transportation plan s arrives at the unloading port;

[0071] denotes the unloading time of the transportation plan s; denotes the time when the transportation plan s arrives at the loading port;

[0072] FOB denotes the set of real transportation plans; K denotes the set of self-owned ships and leased ships;

[0073] K artificial denotes the set of virtual ships.

[0074] In one embodiment of the present application, the continuity of the real transportation plan can also be constrained, i.e. for the plan s assigned to the ship k, it is guaranteed that it is continuous with its previous and next plans, and its constraint function is as follows formula (8):

[0075]

[0076] wherein FOB' represents the set of real transportation plans and virtual transportation plans; k represents the set of real transportation plans and virtual transportation plans; represents a 0-1 integer variable, which is 1 if the transportation plan i and the transportation plan s are both assigned to the ship k and are continuous, otherwise it is 0; FOB' represents the set of real transportation plans and virtual transportation plans; k { s} represents the set of real transportation plans and virtual transportation plans except the transportation plan s; represents a 0-1 integer variable, which is 1 if the transportation plan s and the transportation plan j are both assigned to the ship k and are continuous, otherwise it is 0; K represents the set of self-owned ships and leased ships.

[0077] The ship k can be idle without being assigned a task, and the out-degree of its virtual plan is limited to be less than or equal to 1, and its constraint function is as follows formula (9):

[0078]

[0079] wherein FOB represents the set of real transportation plans; represents a 0-1 integer variable, which is 1 if the virtual transportation plan s executed by the ship k and the transportation plan j are both assigned to the ship k and are continuous, otherwise it is 0; K represents the set of self-owned ships and leased ships; the virtual plan executed by the ship k has a starting point at the initial starting point of the ship k.

[0080] In one embodiment of the present application, the time continuity of the real transportation plan can also be constrained, i.e. the unloading port of the transportation plan i is not one of the optional upstream ports of the transportation plan j, then the transportation plan i and the transportation plan j cannot be continuously executed, and its constraint function is as follows formula (10):

[0081]

[0082] wherein, represents a 0-1 integer variable, which is 1 if the transportation plan i and the transportation plan j are both assigned to the ship k and are continuous, otherwise it is 0; K represents the set of self-owned ships and leased ships; FOB represents the set of real transportation plans; FOB\{i} represents the set of real transportation plans except the transportation plan i; iIP denotes the unloading port of the transportation plan i; denotes the set of optional upstream ports of the transportation plan j.

[0083] denotes the lower bound of the connection time between the completion of the transportation plan i and the start of the execution of the transportation plan j, and its constraint function is as follows formula (11):

[0084]

[0085] wherein, denotes a 0-1 integer variable, and takes the value of 1 if the transportation plan i and the transportation plan j are both configured with the ship k and are continuously executed between the transportation plan i and the transportation plan j, otherwise takes the value of 0; denotes the time when the transportation plan j arrives at the loading port; denotes the time when the transportation plan i arrives at the unloading port; denotes the unloading time of the transportation plan i; K denotes the set of self-owned ships and leased ships; FOB denotes the set of real transportation plans; FOB\{i} denotes the set of real transportation plans excluding the transportation plan i.

[0086] denotes the sailing time according to the maximum speed of the ship k, and its calculation formula (12) is as follows:

[0087]

[0088] wherein, denotes the distance between the unloading port of the transportation plan i and the loading port of the transportation plan j; denotes the maximum sailing speed of the ship k; denotes the virtual plan s executed by the ship k, and the starting points are all at the initial starting point of the ship k; denotes the distance between the initial position and the loading port of the transportation plan j.

[0089] In an embodiment of the present application, the use time of the self-owned ship can also be constrained, that is, for the last transportation plan executed by the self-owned ship k, the end time is limited to be less than the latest available time, and its constraint function is as follows formula (13):

[0090]

[0091] wherein, denotes a 0-1 integer variable, and takes the value of 1 if the transportation plan s and the virtual transportation plan s executed by the ship k are both configured with the ship k and are continuously executed between the transportation plan s and the virtual transportation plan s executed by the ship k, otherwise takes the value of 0; the latest available time of the available time interval of the ship k; the arrival time of the transportation plan s at the unloading port; the unloading duration of the transportation plan s; FOB represents the set of real transportation plans; K owned the set of self-owned ships;

[0092] In an embodiment of the present application, the use time of the leased ship can also be constrained, that is, if the return location of the leased ship contains a domestic port, the end time of the last task is less than the last day of the lease period, and the constraint function is as follows formula (14):

[0093]

[0094] wherein, is a 0-1 integer variable, which is 1 if the transportation plan s and the virtual transportation plan s performed by the ship k are both configured with the ship k, and the transportation plan s and the virtual transportation plan s performed by the ship k are continuously performed, otherwise 0; the latest available time of the available time interval of the ship k; the arrival time of the transportation plan s at the unloading port; the unloading duration of the transportation plan s; FOB represents the set of real transportation plans; K charter the set of leased ships.

[0095] Otherwise, the end time of the last transportation task plus the time of the ship from the last unloading port to the return location is less than the last day of the lease period, and the constraint function is as follows formula (15):

[0096]

[0097] wherein, is a 0-1 integer variable, which is 1 if the transportation plan s and the virtual transportation plan s performed by the ship k are both configured with the ship k, and the transportation plan s and the virtual transportation plan s performed by the ship k are continuously performed, otherwise 0; the latest available time of the available time interval of the ship k; the arrival time of the transportation plan s at the unloading port; the unloading duration of the transportation plan s; FOB represents the set of real transportation plans; K charter the set of leased ships. the return voyage time of the ship k of the last executed transportation plan, taking the minimum value of the distance between the unloading port of the last transportation plan and the return location, taking the minimum sailing speed of the ship k, the return voyage time is calculated as follows formula (16):

[0098]

[0099] wherein, denotes the distance between the unloading port of the last transportation plan and the ship return location; denotes the set of ports for ship k to return; denotes the minimum sailing speed of ship k.

[0100] In an embodiment of the present application, the ship return location of the leased ship can also be constrained, that is, if the ship return location of the leased ship does not contain a domestic port, there is no constraint, and if it contains a domestic port, the unloading port of the last transportation task allocated to the leased ship k is constrained to be one of the ship return locations, and the constraint function is as follows formula (17):

[0101]

[0102] wherein, denotes a 0-1 integer variable, which takes the value of 1 if both the transportation plan s and the virtual transportation plan s performed by ship k are configured for ship k and are continuously performed between the transportation plan s and the virtual transportation plan s performed by ship k, and takes the value of 0 otherwise; FOB denotes the set of real transportation plans; K charter denotes the set of leased ships; S IP denotes the unloading port of the transportation plan s; denotes the set of ports for ship k to return.

[0103] Continuing to refer to Figure 1 In step 130, based on the decision reference data, LNG marine transportation path planning data is output by the mixed integer programming model.

[0104] In the present application, the LNG marine transportation path planning data output by the mixed integer programming model can be which ship matches which transportation plan, which route and at what time to execute the transportation plan.

[0105] In the present application, on the one hand, through the LNG marine transportation path planning data processing scheme proposed in the present application, a ship scheduling scheme under the minimum chartering time can be output, thereby reducing the ship chartering cost and further reducing the LNG transportation cost. On the other hand, based on the LNG marine transportation path optimization model of mixed integer programming, by comprehensively considering the annual transportation plan data, ship data, route data, port state data, and various constraint conditions and optimization objectives, a more optimized LNG marine transportation path can be obtained, which improves the accuracy of LNG marine transportation path planning data processing, and improves the transportation efficiency and safety.

[0106] In this application, it is emphasized that the innovations of this application are as follows:

[0107] (1) Transformation of mathematical model: The traditional LNG marine transportation path problem usually uses heuristic algorithm or empirical method for solution, while the invention transforms it into a mixed integer programming problem, which can obtain more accurate and optimized results.

[0108] (2) Comprehensive consideration of multiple factors: The invention considers multiple factors, including ship navigation route and loading and unloading port selection, which can obtain a more comprehensive and optimized path scheme.

[0109] (3) Practicality and economy: The invention can provide effective decision support for enterprises to optimize LNG marine transportation path and ship cost, with the advantages of practicality and economy.

[0110] The following describes an embodiment of the device of the present application, which can be used to execute the LNG marine transportation path planning data processing method in the above-mentioned embodiments of the present application. For details not disclosed in the device embodiment of the present application, please refer to the above-mentioned embodiments of the LNG marine transportation path planning data processing method.

[0111] Figure 2 A block diagram of the LNG marine transportation path planning data processing device according to an embodiment of the present application is shown.

[0112] Referring to Figure 2 The LNG marine transportation path planning data processing device 200 according to an embodiment of the present application is shown, which includes an acquisition unit 201, a construction unit 202 and an output unit 203.

[0113] The acquisition unit 201 is configured to acquire decision reference data associated with LNG marine transportation path planning, the decision reference data at least including annual transportation plan data, ship data, route data and port state data; the construction unit 202 is configured to construct a mixed integer programming model and define a target function and a constraint function associated with LNG marine transportation path planning in the mixed integer programming model; and the output unit 203 is configured to output LNG marine transportation path planning data processing based on the decision reference data through the mixed integer programming model.

[0114] Figure 3 A structural schematic diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application is shown.

[0115] It should be noted that, Figure 3 The computer system 300 of the electronic device shown is only an example and should not limit the functions and use range of the embodiments of the present application.

[0116] like Figure 3 As shown, the computer system 300 includes a Central Processing Unit (CPU) 301, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 302 or programs loaded from storage portion 308 into Random Access Memory (RAM) 303, such as performing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An Input / Output (I / O) interface 305 is also connected to the bus 304.

[0117] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0118] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs various functions defined in the system of this application.

[0119] It should be noted that the computer-readable medium in the embodiments of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination thereof. The computer-readable storage medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination thereof. More specific examples of the computer-readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer-readable signal medium can include a data signal carrying a computer-readable program code in a baseband or as a part of a carrier wave. Such a propagated data signal can take various forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, which can send, transmit, propagate or transport a program for use by or in conjunction with an instruction execution system, device or apparatus. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, or the like, or any suitable combination thereof.

[0120] The flowcharts and block diagrams in the drawings illustrate the possible implementation architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In the flowcharts or block diagrams, each block can represent a module, a program segment or a part of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different orders than that shown in the drawings. For example, two blocks that are shown in succession can actually be executed substantially in parallel, and sometimes in reverse order, depending on the involved functions. It should also be noted that each block in the block diagrams or flowcharts, and the combination of blocks in the block diagrams or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0121] The units described in the embodiments of the present application can be implemented by software, or by hardware, or by a combination of software and hardware. The units described can also be located in a processor. In some cases, the names of the units do not constitute a limitation on the units themselves.

[0122] As another aspect, the present application also provides a computer program product or computer program, which includes computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method described in the above embodiments.

[0123] As another aspect, the present application also provides a computer readable medium, which can be included in the electronic device described in the above embodiments, or can exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the method described in the above embodiments.

[0124] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, the division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into several modules or units.

[0125] From the above description of the embodiments, those skilled in the art will readily appreciate that the example embodiments described herein can be implemented by software and / or by hardware coupled with software. Accordingly, the technical solutions of the embodiments of the present application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, U disk, mobile hard disk, etc.) or network, and includes several instructions to make a computing device (which can be a personal computer, server, touch terminal, or network device, etc.) execute the methods according to the embodiments of the present application.

[0126] Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the application following the general principles thereof and including such departures from the present disclosure as come within known use or custom in the art.

[0127] It is to be understood that the application is not limited to the precise construction already described above and shown in the drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application should only be limited by the claims appended hereto.

Claims

1. A data processing method for LNG maritime transport route planning, characterized in that, The method includes: Obtain decision reference data associated with LNG maritime transport route planning, wherein the decision reference data includes at least annual transport plan data, vessel data, route data, and port status data; A mixed-integer programming model is constructed, and an objective function and constraint functions associated with LNG maritime transport route planning are defined in the mixed-integer programming model, wherein the objective function is: in, This represents the minimum sum of full-load durations allocated to virtual ships to execute transportation plans; A collection representing actual transportation plans; This represents a 0-1 integer variable. If the transportation plan s is configured with virtual ship k, the value is 1; otherwise, the value is 0. Represents a virtual ship; Indicates the time when transport plan s arrives at the port of discharge; This indicates the unloading time for transportation plan s; Indicates the time when transport plan s arrives at the loading port; Based on the decision reference data, the mixed integer programming model outputs LNG maritime transport route planning data.

2. The method according to claim 1, characterized in that, The following constraint functions are defined in the mixed-integer programming model: in, This represents a 0-1 integer variable. If the transportation plan s is configured with ship k, the value is 1; otherwise, the value is 0. This represents the set of real and virtual transportation plans excluding transportation plan s; This represents an integer variable between 0 and 1. If both transportation plan i and transportation plan s are configured with ship k, and transportation plan i and transportation plan s are executed consecutively, the value is 1; otherwise, the value is 0. A collection representing actual transportation plans; This refers to a collection of owned and leased vessels.

3. The method according to claim 1, characterized in that, The following constraint functions are defined in the mixed-integer programming model: in, This refers to a collection of owned and leased vessels; This represents the capacity of ship k; This represents a 0-1 integer variable. If the transportation plan s is configured with ship k, the value is 1; otherwise, it is 0. This indicates the loading / unloading volume of transportation plan s; This represents a collection of actual transportation plans.

4. The method according to claim 1, characterized in that, The following constraint functions are defined in the mixed-integer programming model: in, This refers to a collection of owned and leased vessels; Represents a collection of virtual ships; This represents a 0-1 integer variable. If the transportation plan s is configured with ship k, the value is 1; otherwise, the value is 0. A collection representing actual transportation plans; This represents an integer variable between 0 and 1. If the transportation plan s is configured to execute the ships in the transportation plan s, the value is 1; otherwise, the value is 0. Indicates the vessel executing transport plan s; This represents the set of shipping plans that can currently be matched with ships.

5. The method according to claim 1, characterized in that, The following constraint functions are defined in the mixed-integer programming model: in, This represents a 0-1 integer variable. If the transportation plan s is configured with ship k, the value is 1; otherwise, the value is 0. A collection representing actual transportation plans; This indicates the collection of vessels prohibited from berthing at the unloading port and loading port of transport plan s.

6. The method according to claim 1, characterized in that, The following constraint functions are defined in the mixed-integer programming model: in, This represents a 0-1 integer variable. If the transportation plan s is configured with ship k, the value is 1; otherwise, the value is 0. This indicates the distance between the unloading port and the loading port of transport plan s; This represents the maximum speed of ship k. Indicates the time when transport plan s arrives at the port of discharge; This indicates the unloading time for transportation plan s; Indicates the time when transport plan s arrives at the loading port; A collection representing actual transportation plans; This refers to a collection of owned and leased vessels; This represents a collection of virtual ships.

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