CN111709579A - Ship speed optimization method and device - Google Patents

Ship speed optimization method and device Download PDF

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CN111709579A
CN111709579A CN202010557685.5A CN202010557685A CN111709579A CN 111709579 A CN111709579 A CN 111709579A CN 202010557685 A CN202010557685 A CN 202010557685A CN 111709579 A CN111709579 A CN 111709579A
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向新桃
吴振华
樊翔
程宣恺
高文
李鑫
黄建涛
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Shanghai Merchant Ship Design and Research Institute of CSSC No 604 Research Institute
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Abstract

The invention provides a ship speed optimization method and a ship speed optimization device, which relate to the technical field of ships and are used for segmenting a ship route by adopting a constant-direction line forward and backward solution algorithm to obtain a plurality of segmentation points; when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the sailing distance of the ship in the weather forecast duration; respectively calculating target distances between the starting point of the route and the plurality of segmentation points, and determining a target segmentation point which enables the target distance to be closest to the navigation distance; based on a pre-established navigational speed optimization model, solving the navigational speed of the ship by taking the target division point as an optimization terminal and the target duration as the optimized navigational time to obtain the optimal navigational speed distribution; and the optimized sailing time is less than the weather forecast time. The method and the device can improve the accuracy and reliability of the speed optimization when the weather forecast duration cannot cover the full range in the overlong airline.

Description

Ship speed optimization method and device
Technical Field
The invention relates to the technical field of ships, in particular to a ship speed optimization method and device.
Background
At present, in the field of ship speed optimization, a ship is generally optimized in a segmented speed by combining with a weather condition, wherein the weather condition can be obtained according to weather forecast, but when a ship route is too long, weather forecast information may not cover a full range, the ship cannot reach a destination within a weather forecast duration range, for example, the weather forecast duration is 5 days, and when the ship is sailed across the pacific, the ship cannot reach the destination within 5 days, so that a speed optimization result is not accurate and reliable enough.
Disclosure of Invention
The invention aims to provide a ship speed optimization method and a ship speed optimization device, which are used for solving the technical problem that a speed optimization result is not accurate and reliable enough because a ship cannot reach a destination within a weather forecast duration range due to a too long route.
In a first aspect, an embodiment of the present invention provides a ship speed optimization method, where the method includes:
segmenting the ship route by adopting a constant direction line forward and backward solution algorithm to obtain a plurality of segmentation points;
when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the sailing distance of the ship in the weather forecast duration;
respectively calculating target distances between a starting point of a flight path and the plurality of segmentation points, and determining a target segmentation point which enables the target distance to be closest to the navigation distance;
based on a pre-established navigational speed optimization model, solving the navigational speed of the ship by taking the target division point as an optimization terminal and the target duration as the optimized navigational time to obtain the optimal navigational speed distribution; wherein the optimized sailing duration is less than the weather forecast duration.
In an optional embodiment, the step of segmenting the ship route by using a constant direction line forward and backward solution algorithm to obtain a plurality of segmentation points includes:
and segmenting the flight sections between the adjacent waypoints in the plurality of waypoints of the ship by adopting a constant line forward-backward solution algorithm to obtain a plurality of segmentation points.
In an optional embodiment, the step of calculating the sailing distance of the ship within the weather forecast duration when the total expected sailing duration of the ship is greater than the weather forecast duration includes:
when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the ratio of the weather forecast duration to the expected total sailing duration;
and multiplying the ratio by the total sailing distance to obtain the sailing distance of the ship within the weather forecast duration.
In an optional embodiment, the step of solving the ship speed of the ship by using the target division point as an optimization endpoint and the target duration as an optimized sailing duration based on a pre-established speed optimization model to obtain an optimal speed distribution includes:
solving the navigational speed of the ship according to the following formula to obtain the optimal navigational speed distribution { u }opt：
Figure BDA0002544388150000021
Figure BDA0002544388150000022
Wherein the J-th division point is a target division point tiTime of arrival of ship at ith division point, ti-1The time when the ship reaches the i-1 th division point, f is a fuel consumption model, uiFor speed, Δ is displacement, w (t)i-1/2,Li-1/2) For the average environmental state expected to be experienced by the ship on the leg between every two division points, L represents a division point; siFor the distance from the starting point of the flight path to the respective division points, 0<β<1，TwThe weather forecast duration.
In an alternative embodiment, the speed optimization model is solved according to one of the following algorithms:
particle swarm optimization algorithm, genetic algorithm, ant colony algorithm and dynamic programming algorithm.
In a second aspect, an embodiment of the present invention provides a device for optimizing a ship speed, where the device includes:
the segmentation module is used for segmenting the ship route by adopting a constant direction line forward and backward solution algorithm to obtain a plurality of segmentation points;
the calculation module is used for calculating the sailing distance of the ship in the weather forecast duration when the expected total sailing duration of the ship is greater than the weather forecast duration;
the determining module is used for respectively calculating target distances between a starting point of a route and the plurality of segmentation points and determining a target segmentation point which enables the target distance to be closest to the navigation distance;
the optimization module is used for solving the navigational speed of the ship by taking the target division point as an optimization terminal and the target duration as the optimized navigational time based on a preset navigational speed optimization model to obtain the optimal navigational speed distribution; wherein the optimized sailing duration is less than the weather forecast duration.
In an optional embodiment, the segmentation module is further configured to:
and segmenting the flight sections between the adjacent waypoints in the plurality of waypoints of the ship by adopting a constant line forward-backward solution algorithm to obtain a plurality of segmentation points.
In an optional embodiment, the computing module is further configured to:
when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the ratio of the weather forecast duration to the expected total sailing duration;
and multiplying the ratio by the total sailing distance to obtain the sailing distance of the ship within the weather forecast duration.
In a third aspect, an embodiment of the present invention provides a smart ship, including a processor and a machine-readable storage medium, where the machine-readable storage medium stores machine-executable instructions executable by the processor, and the processor executes the machine-executable instructions to implement the method described in any one of the foregoing embodiments.
In a fourth aspect, embodiments of the invention provide a machine-readable storage medium having stored thereon machine-executable instructions that, when invoked and executed by a processor, cause the processor to implement a method as in any one of the preceding embodiments.
The ship speed optimization method and the ship speed optimization device provided by the invention have the advantages that a constant-direction line forward-backward solution algorithm is adopted to divide a ship route to obtain a plurality of division points; when the expected total navigation duration of the ship is longer than the weather forecast duration, based on a pre-established speed optimization model, taking a target division point as an end point, taking the target duration as the navigation duration, solving the speed of the ship to obtain optimal speed distribution, wherein the distance between a starting point of a route and the target division point is closest to the navigation distance of the ship in the weather forecast duration, and the optimal navigation duration is shorter than the weather forecast duration. The method is characterized in that the method does not need to carry out navigation speed optimization on all the segmentation points, but carries out navigation speed optimization on the segmentation points before the target segmentation point, the segmentation points basically cover weather forecast information, and based on a surplus time strategy (the optimized navigation time is less than the weather forecast time), the navigation speed optimization is carried out under the condition that a ship arrives at a destination slightly earlier than appointed time, so that the accuracy and reliability of the navigation speed optimization can be improved when the weather forecast time in an extra-long air route cannot cover the full air route, the navigation speed optimization is more stable, the method is more suitable for the problem of the extra-long air route with higher uncertainty, and the engineering feasibility is higher.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a ship speed optimization method provided in an embodiment of the present invention;
FIG. 2 is a schematic view of a constant direction line provided by an embodiment of the present invention;
FIG. 3 is a diagram illustrating discretized effects of ship routes according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a ship speed optimization device provided by an embodiment of the invention;
fig. 5 is a schematic diagram of a smart ship according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, in the field of ship speed optimization, the ship is generally optimized in a segmented speed by combining with weather conditions, and the weather conditions can be obtained according to weather forecast, but when the air route is too long, the weather forecast information may not cover the whole air route, and the ship cannot reach a destination within the time range of the weather forecast, so that the speed optimization result is not accurate and reliable enough. Based on the above, the method and the device for optimizing the ship speed provided by the embodiment of the invention can improve the accuracy and reliability of the speed optimization when the weather forecast duration cannot cover the full range in the overlong route.
Some embodiments of the invention are described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
Fig. 1 shows a flowchart of a ship speed optimization method provided by an embodiment of the invention. Referring to fig. 1, an embodiment of the present invention provides a ship speed optimization method, including the following steps:
and S101, segmenting the ship route by adopting a constant direction line forward and backward solution algorithm to obtain a plurality of segmentation points.
In the navigation of a ship, the ship usually travels along a constant line for the convenience of operation. On the earth surface, a constant direction line refers to a spherical spiral curve keeping the same angle with a meridian everywhere; after transformation to the mercator projection plane, the homeotropic lines are mapped to a straight line, as shown in fig. 2, with S being the homeotropic line. In order to accurately divide the course into a plurality of small sections, the geometric calculation of an ellipsoid needs to be carried out on a constant direction line, and the coordinates of the division points are obtained. In this step, the course of the ship is composed of several waypoints, which may be expressed as { P }1,P2...,PtotalAnd the total is the number of the waypoints, and every two adjacent waypoints navigate according to a constant direction line.
The ship route is divided into small segments by using a constant direction line forward and backward solution algorithm to obtain a plurality of division points, so that the discretization of the ship route is realized, and the ship route discretization effect is shown in fig. 3.
And S102, calculating the sailing distance of the ship in the weather forecast duration when the expected total sailing duration of the ship is greater than the weather forecast duration.
Under the current technical conditions, the weather forecast duration is limited. And (4) obtaining the total navigation distance according to the distance between the adjacent segmentation points, and further estimating the navigation distance of the ship within the weather forecast duration.
Step S103, respectively calculating the target distance between the starting point of the route and the plurality of segmentation points, and determining the segmentation point of the target which enables the target distance to be closest to the navigation distance.
Specifically, when the course is segmented by using a constant direction line forward and backward solution algorithm, the distance between adjacent segmentation points can be obtained, the target distance from the starting point of the course to each segmentation point can be calculated through distance superposition, and then the target segmentation point when the target distance is closest to the navigation distance of the ship within the weather forecast duration is calculated, so that the segmentation point before the target segmentation point basically covers the weather forecast information.
Step S104, solving the navigational speed of the ship by taking the target division point as an optimization terminal and the target duration as the optimized navigational duration based on a pre-established navigational speed optimization model to obtain the optimal navigational speed distribution; and the optimized sailing time is less than the weather forecast time.
In this step, the speed optimization model is a known model, and in this embodiment, based on the speed optimization model, the target division point is used as an optimization endpoint to optimize the speed of the divided points before the target division point, because the division points basically cover the weather forecast information, the optimized sailing time is less than the weather forecast time, surplus time is reserved, and the speed optimization is performed under the condition that the ship arrives at the destination slightly earlier than the appointed time, so that the accuracy and reliability of the speed optimization can be improved when the weather forecast time in the very long course cannot cover the full course, the speed optimization is more stable, the method is more suitable for the very long course problem with higher uncertainty, and the engineering feasibility is higher.
It should be noted that the future meteorological environment is uncertain, and if the speed optimization is performed according to "arrive at the scheduled time", the meteorological environment may not arrive at the port in time due to sudden change. Therefore, the embodiment is based on the surplus time strategy, so that the optimized navigation time length is smaller than the weather forecast time length, and the surplus time can be adjusted as required, thereby being applicable to different navigation scenes.
In some embodiments, step S101 may be implemented by:
and segmenting the flight sections between the adjacent waypoints in the plurality of waypoints of the ship by adopting a constant line forward-backward solution algorithm to obtain a plurality of segmentation points. The specific process is as follows:
1) for any two adjacentWaypoint P ofx、Px+1When x is 1 and 2 … total-1, the course angle C and course S between two points, i.e., the reverse solution process of the constant line, are obtained by the following equations (1) to (6).
The reverse solving process of the constant direction line is as follows: the latitude and longitude of the origin of a known constant direction line segment
Figure BDA0002544388150000071
End point latitude and longitude
Figure BDA0002544388150000072
And solving a course angle C and a course S of the constant direction line. For convenience of description, the index 1 is used to indicate the starting point of the leg, and the index 2 is used to indicate the ending point of the leg.
The equivalent latitude (latitude growth rate) is calculated by the following formula (1):
Figure BDA0002544388150000073
wherein,
Figure BDA0002544388150000074
representing latitude coordinates, and e representing the first eccentricity of the earth ellipsoid model.
The difference between the latitudes of the same magnitude at the starting point and the ending point of the line of the constant direction is calculated by the following formula (2):
Figure BDA0002544388150000075
the meridian arc length is calculated by the following formula (3):
Figure BDA0002544388150000076
wherein,
Figure BDA0002544388150000077
and (3) expressing latitude coordinates, e expressing the first eccentricity of the earth ellipsoid model, and a expressing the major semi-axis of the earth ellipsoid model.
Then the meridian arc of the origin of the constant direction lineLong and long
Figure BDA0002544388150000081
And the radial arc length of the end point of the constant direction line
Figure BDA0002544388150000082
The difference is shown in the following formula (4):
Figure BDA0002544388150000083
the course and the course angle of the constant direction are calculated by the following formulas (5) and (6):
by Dλ＝λ2-λ1Represents the difference in menstruation. After the constant direction line on the ellipsoid is transformed to the mercator projection plane, the constant direction line, the longitude line and the latitude line form a right triangle, as shown in fig. 2, then the course angle C and the course S of the constant direction line can be expressed as:
C＝arctan(Dλ/DMP) (5)
Figure BDA0002544388150000084
2) will PiAnd Pi+1The flight segment between is divided into niSmall segments, then each small segment is S/n longiThen, equations (6), (3) and (7) are sequentially called to obtain the coordinates of each division point, namely the positive solution process of the constant direction line.
The process of solving the problem positively by the constant direction line is as follows: knowing the coordinates of the starting point
Figure BDA0002544388150000085
Summing the course angle C and course S of the constant direction line, and calculating the coordinates of the end point
Figure BDA0002544388150000086
① find out
Figure BDA0002544388150000087
And DMP. Is reversely pushed by the above formula (6)
Figure BDA0002544388150000088
Then will be
Figure BDA0002544388150000089
Substituting the above formula (3) to obtain
Figure BDA00025443881500000810
The transcendental equation of (2) can be obtained by dichotomy
Figure BDA00025443881500000811
Will be provided with
Figure BDA00025443881500000812
Substituting the above formula (1) and formula (2) to obtain DMP。
② finding λ2. According to the obtained DMPFrom the mercator projection triangle, λ can be calculated2The following formula (7):
λ2＝λ1+DMPtanC (7)
3) for all waypoints { P1,P2...,PtotalAnd (3) repeating the calculation processes of 1) and 2), dividing the ship route into a plurality of small sections, and after reordering from a starting point to an end point, marking all division points as L0,L1,...,LnN +1 is the number of division points, and the distance between adjacent division points is denoted as s ═ s1,s2,...,sn]T。
In some embodiments, step S102 may include the steps of:
step 1) when the expected total sailing duration of the ship is greater than the weather forecast duration, calculating the ratio of the weather forecast duration to the expected total sailing duration;
and 2) multiplying the ratio by the total sailing distance to obtain the sailing distance of the ship within the weather forecast duration.
In particular, with TwAnd T respectively represents the weather forecast duration and the expected total duration, and the ratio α of the weather forecast duration to the expected total duration is calculated according to the following formula (8):
α＝Tw/T (8)
if α<1, indicating that the ship cannot reach the destination port within the weather forecast duration, T can be estimated from αwWithin a time length, the sailing distance S of the shipwAs shown in the following formula (9):
Figure BDA0002544388150000091
wherein S isiI is 1,2, …, n is an integer,
Figure BDA0002544388150000092
representing the total distance traveled, and n +1 is the number of split points.
In step S103, for each of the divided points, a target distance S _ L from the starting point of the route to each of the divided points is calculated according to the following equation (10)j：
Figure BDA0002544388150000093
Wherein S isiIs the distance between the adjacent dividing points.
Then, J-min, i.e., s _ L, is calculated according to the following formula (11)jAnd SwWhen the distance is closest to the target division point, the target division point is the first division point on the air route:
Figure BDA0002544388150000094
in some embodiments, the step of solving the ship speed to obtain the optimal speed distribution based on a pre-established speed optimization model by using the target division point as an optimization endpoint and the target duration as an optimization duration comprises:
solving the ship speed according to the following formula (12) to obtain the optimal speed distribution { u }opt：
Figure BDA0002544388150000101
Wherein the J-th division point is a target division point tiTime of arrival of ship at ith division point, ti-1The time when the ship reaches the i-1 th division point, f is a fuel consumption model, uiFor speed, Δ is displacement, w (t)i-1/2,Li-1/2) For the average environmental state expected to be experienced by the ship on the leg between every two division points, L represents a division point; siFor the distance from the starting point of the flight path to the respective division points, 0<β<1，TwFor weather forecast duration, it should be noted that β may be slightly less than 1.
The oil consumption model f is the basis of the speed optimization function. When the ship sails, the fuel consumption rate y, the sailing speed u, the displacement delta, the water depth, the wind wave and other environmental parameters w ═ w1,w2,...wk]TIt is related. In the field of intelligent ships, the relationship between the fuel consumption rate y and each influence factor can be estimated through a large amount of data, and the following formula (13) is obtained:
y＝f(u,Δ,w) (13)
specifically, on the basis of a large amount of data, the parameter relationship shown in formula (13) can be obtained by methods such as generalized linear regression, decision tree, bayesian linear regression, ensemble learning, neural network, and the like.
In practical applications, the known cruise optimization model is shown as the following equation (14):
Figure BDA0002544388150000102
in this embodiment, a surplus time strategy is introduced, and an adjustable parameter β is added to obtain the formula (12).
It should be noted that if α is greater than or equal to 1, it indicates that the ship can reach the destination port within the weather forecast duration, and then the speed optimization problem is solved according to the above equation (14).
In some embodiments, the speed optimization model may be solved according to one of the following algorithms:
particle Swarm Optimization (PSO), genetic algorithm, ant colony algorithm, dynamic programming algorithm.
It should be noted that the present embodiment is not limited to the above optimization algorithm, and other optimization algorithms may be adopted.
The following describes the construction of the cruise optimization model and the cruise optimization solving process in detail by taking the PSO as an example.
The first step is as follows: calculating the total oil consumption
During a sailing mission, the displacement Δ of the ship is substantially constant. Dividing the route into n segments to obtain n +1 division points L0,L2,...,LnThe distance of each segment is s ═ s1,s2,...,sn]TThe speed of each section is u ═ u1,u2,...,un]T。
On the basis, the total sailing oil consumption can be obtained by the following method:
the time of the ship reaching each division point is obtained by s and u, and the formula (15) shows:
t0＝now，ti＝ti-1+si/ui,i＝0,1,2,...,n (15)
secondly, according to weather forecast data and water depth, calculating the expected environment experienced by the ship:
the water depth data may be represented as a discrete function of latitude and longitude (lon, lat), and the weather forecast data may be represented as a discrete function of time t and latitude and longitude (lon, lat). The environmental state w (t) expected to be experienced when the ship reaches each division point can be obtained through data interpolationi,Li) I-0, 1,2,.., n, and the average environmental state w (t) expected to be experienced by the ship over each segmenti-1/2,Li-1/2),i＝1,2,...,n。
③ mixing w (t)i-1/2,Li-1/2) I 1, 2., n is put into a fuel consumption model and integrated, and total fuel consumption can be obtained as shown in equation (16):
Figure BDA0002544388150000121
the second step is that: building optimization problems
Constructing a ship speed optimization model according to the following formula (17):
Figure BDA0002544388150000122
wherein the constraint condition is β TwThe destination is reached within time.
The third step: PSO solving optimization problem
Equation (18) shows that in solving the speed optimization problem, it is necessary to solve the speed optimization problem in an n-dimensional space { u } -, where u is equal to1,u2,...,unFind the best position in { u }optSo that the total fuel consumption F (u, Δ, w) is minimal.
PSO initialization of a set of (m) random particles
Figure BDA0002544388150000123
And then searching for an optimal solution through iterative updating. In each iteration, the particle passes close to two "extrema" { u }k,pbest，{u}gbestTo update itself. Wherein { u }k,pbestIndicating the best choice of records in each particle update process. { u }gbestIndicating the best choice of records in all particle update processes.
b. At each iteration, the particles are approximated by the following equation (18) { u }k,pbestAnd { u }gbestContinuously searching global optimum:
Figure BDA0002544388150000124
where j is the number of iterations, ω is the inertia factor, c1And c2The learning factor can be debugged manually. r is1And r2Is a random number between 0 and 1, which can increase the randomness of the search.
c. After each iteration, { u }is updatedk,pbestAnd { u }gbest. Here, { u }is selectedk,pbestAnd { u }gbestNot only is the objective function F (u, Δ, w) minimized, but solutions that do not satisfy the constraints need to be excluded.
d. After multiple iterations, if { u }gbestTends to stabilize, or the objective function F (u, Δ, w) is small enough to terminate the iteration, outputting { u }gbestAs a final result.
On the basis of the above embodiments, an embodiment of the present invention further provides a ship speed optimization device, as shown in fig. 4, the device includes:
the segmentation module 41 is configured to segment the ship route by using a constant direction line forward-backward solution algorithm to obtain a plurality of segmentation points;
the calculation module 42 is used for calculating the sailing distance of the ship within the weather forecast duration when the expected total sailing duration of the ship is greater than the weather forecast duration;
a determining module 43, configured to calculate target distances between the starting point of the route and the multiple segmentation points, and determine a target segmentation point at which the target distance is closest to the travel distance;
the optimization module 44 is configured to solve the ship speed based on a pre-established speed optimization model by using the target division point as an optimization endpoint and the target duration as an optimization navigation duration to obtain optimal speed distribution; and the optimized sailing time is less than the weather forecast time.
In some embodiments, the segmentation module 41 is further configured to:
and segmenting the flight sections between the adjacent waypoints in the plurality of waypoints of the ship by adopting a constant line forward-backward solution algorithm to obtain a plurality of segmentation points.
In some embodiments, the calculation module 42 is further configured to:
when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the ratio of the weather forecast duration to the expected total sailing duration;
and multiplying the ratio by the total sailing distance to obtain the sailing distance of the ship within the weather forecast duration.
In some embodiments, optimization module 44 is further configured to:
solving the ship speed according to the formula (12) of the embodiment to obtain the optimal speed distribution { u }opt：
Figure BDA0002544388150000141
Figure BDA0002544388150000142
Wherein the J-th division point is a target division point tiTime of arrival of ship at ith division point, ti-1The time when the ship reaches the i-1 th division point, f is a fuel consumption model, uiFor speed, Δ is displacement, w (t)i-1/2,Li-1/2) For the average environmental state expected to be experienced by the ship on the leg between every two division points, L represents a division point; siFor the distance from the starting point of the flight path to the respective division points, 0<β<1，TwThe weather forecast duration.
In some embodiments, the speed optimization model is solved according to one of the following algorithms:
particle swarm optimization algorithm, genetic algorithm, ant colony algorithm and dynamic programming algorithm.
According to the ship speed optimization method and device provided by the embodiment of the invention, the ship route is divided by adopting a constant-direction line forward-backward solution algorithm to obtain a plurality of division points; when the expected total navigation duration of the ship is longer than the weather forecast duration, based on a pre-established speed optimization model, taking a target division point as an end point, taking the target duration as the navigation duration, solving the speed of the ship to obtain optimal speed distribution, wherein the distance between a starting point of a route and the target division point is closest to the navigation distance of the ship in the weather forecast duration, and the optimal navigation duration is shorter than the weather forecast duration. The method is characterized in that the method does not need to optimize the speed of the ship aiming at all the division points, but optimizes the speed of the ship aiming at the division points before the target division point, the division points basically cover weather forecast information, and based on a rich time strategy (the optimized navigation time is less than the weather forecast time), the speed of the ship is optimized under the condition that the ship arrives at the destination slightly earlier than the appointed time, so that the accuracy and the reliability of the speed optimization can be improved when the weather forecast time in the overlong route cannot cover the full range, the speed optimization is more stable, the method is more suitable for the problem of the overlong route with higher uncertainty, and the engineering feasibility is higher.
The ship speed optimization device provided by the embodiment of the invention can be specific hardware on equipment or software or firmware installed on the equipment. The device provided by the embodiment of the present invention has the same implementation principle and technical effect as the method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the method embodiments without reference to the device embodiments.
Referring to fig. 5, an embodiment of the present invention further provides a smart ship 500, including: the system comprises a processor 501, a memory 502, a bus 503 and a communication interface 504, wherein the processor 501, the communication interface 504 and the memory 502 are connected through the bus 503; the memory 502 is used to store programs; the processor 501 is used for calling the program stored in the memory 502 through the bus 503 to execute the ship speed optimization method of the above embodiment.
The Memory 502 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 504 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
Bus 503 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 5, but this does not indicate only one bus or one type of bus.
The memory 502 is used for storing a program, the processor 501 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 501, or implemented by the processor 501.
The processor 501 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 501. The Processor 501 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 502, and the processor 501 reads the information in the memory 502 and completes the steps of the method in combination with the hardware.
Embodiments of the present invention also provide a machine-readable storage medium, in which machine-executable instructions are stored, and when the machine-executable instructions are called and executed by a processor, the machine-executable instructions cause the processor to implement the above method for optimizing ship speed.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for optimizing the speed of a ship, the method comprising:
segmenting the ship route by adopting a constant direction line forward and backward solution algorithm to obtain a plurality of segmentation points;
when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the sailing distance of the ship in the weather forecast duration;
respectively calculating target distances between a starting point of a flight path and the plurality of segmentation points, and determining a target segmentation point which enables the target distance to be closest to the navigation distance;
based on a pre-established navigational speed optimization model, solving the navigational speed of the ship by taking the target division point as an optimization terminal and the target duration as the optimized navigational time to obtain the optimal navigational speed distribution; wherein the optimized sailing duration is less than the weather forecast duration.
2. The method of claim 1, wherein the step of segmenting the ship route by using a constant direction line forward and backward solution algorithm to obtain a plurality of segmentation points comprises:
and segmenting the flight sections between the adjacent waypoints in the plurality of waypoints of the ship by adopting a constant line forward-backward solution algorithm to obtain a plurality of segmentation points.
3. The method of claim 1, wherein said step of calculating the vessel's voyage distance within the weather forecast duration when the total expected voyage duration for the vessel is greater than the weather forecast duration comprises:
when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the ratio of the weather forecast duration to the expected total sailing duration;
and multiplying the ratio by the total sailing distance to obtain the sailing distance of the ship within the weather forecast duration.
4. The method according to claim 1, wherein the step of solving the ship's speed based on the pre-established speed optimization model with the target division point as the optimization endpoint and the target duration as the optimization duration to obtain the optimal speed distribution comprises:
solving the navigational speed of the ship according to the following formula to obtain the optimal navigational speed distribution { u }opt：
Figure FDA0002544388140000021
Figure FDA0002544388140000022
Wherein the J-th division point is a target division point tiTime of arrival of ship at ith division point, ti-1The time when the ship reaches the i-1 th division point, f is a fuel consumption model, uiFor speed, Δ is displacement, w (t)i-1/2,Li-1/2) For the average environmental state expected to be experienced by the ship on the leg between every two division points, L represents a division point; siFor the distance from the starting point of the flight path to the respective division points, 0<β<1，TwThe weather forecast duration.
5. The method of claim 1 or 4, wherein the speed optimization model is solved according to one of the following algorithms:
particle swarm optimization algorithm, genetic algorithm, ant colony algorithm and dynamic programming algorithm.
6. A device for optimizing the speed of a ship, said device comprising:
the segmentation module is used for segmenting the ship route by adopting a constant direction line forward and backward solution algorithm to obtain a plurality of segmentation points;
the calculation module is used for calculating the sailing distance of the ship in the weather forecast duration when the expected total sailing duration of the ship is greater than the weather forecast duration;
the determining module is used for respectively calculating target distances between a starting point of a route and the plurality of segmentation points and determining a target segmentation point which enables the target distance to be closest to the navigation distance;
the optimization module is used for solving the navigational speed of the ship by taking the target division point as an optimization terminal and the target duration as the optimized navigational time based on a preset navigational speed optimization model to obtain the optimal navigational speed distribution; wherein the optimized sailing duration is less than the weather forecast duration.
7. The apparatus of claim 6, wherein the segmentation module is further configured to:
and segmenting the flight sections between the adjacent waypoints in the plurality of waypoints of the ship by adopting a constant line forward-backward solution algorithm to obtain a plurality of segmentation points.
8. The apparatus of claim 6, wherein the computing module is further configured to:
when the expected total sailing duration of the ship is longer than the weather forecast duration, calculating the ratio of the weather forecast duration to the expected total sailing duration;
and multiplying the ratio by the total sailing distance to obtain the sailing distance of the ship within the weather forecast duration.
9. A smart vessel comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor executing the machine-executable instructions to implement the method of any one of claims 1-5.
10. A machine-readable storage medium having stored thereon machine-executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of any of claims 1-5.
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