CN116720629A - Port tug scheduling method and device - Google Patents
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Abstract
The invention relates to a method and a device for port tug scheduling, wherein the method establishes a constraint condition table by acquiring all ship data and active tug data of a port, establishes an objective function according to a ship starting position, a ship target position and the active tug position for calculating the total operation time of port tug scheduling, and the objective function meets the constraint condition table and circularly optimizes a template function by using a plurality of evolution strategies under the constraint condition table in a mixed mode to obtain an optimal solution of the objective function, and the optimal solution is used as an optimal scheme for port tug scheduling. Therefore, the mixed evolution strategy is adopted, namely a plurality of evolution strategies are mixed to use the cyclic optimization objective function, global searching capability and calculation efficiency are better than those of the single evolution strategy, the situation that a local optimal solution is involved is avoided, the optimal solution of the total operation time of port tug scheduling is used as an optimal scheme of port tug scheduling, the transportation cost is reduced, and the tug scheduling efficiency is improved.
Description
Technical Field
The invention relates to the technical field of port scheduling, in particular to a port tug scheduling method and device.
Background
The traditional teaching planning and heuristic rule method has certain limitation in solving the tug dispatching problem under the complex condition, and is widely applied and accepted in the port tug dispatching field along with the rising of intelligent algorithms such as an evolution strategy algorithm, an artificial ant colony algorithm, a neural network algorithm and the like, particularly the evolution strategy algorithm has stronger global searching capability, is suitable for the high-dimensional and nonlinear problems, has good performance in treating the tug dispatching problem under the complex condition, but has the defects of slow convergence speed, easy sinking into local optimal solution and the like, so that the solution of the tug dispatching has the problems of accuracy and practicability.
Disclosure of Invention
The technical problems to be solved by the invention are as follows: the invention provides a port tug dispatching method and device, which improve the accuracy and practicability of tug dispatching.
In order to solve the technical problems, the invention adopts the following technical scheme:
in a first aspect, the present invention provides a method for port tug dispatch, comprising:
acquiring all ship data and active tug data of a port, and establishing a constraint condition table between a ship and an active tug based on the ship data and the active tug data, wherein the ship data comprises a ship starting position and a ship target position, and the active tug data comprises an active tug position;
establishing an objective function based on the ship starting position, the ship target position and the active tug position, wherein the objective function meets the constraint condition table, and circularly optimizes the objective function by adopting a mixed evolution strategy under the constraint condition table to obtain an optimal solution of the objective function, and taking the optimal solution as an optimal scheme of port tug scheduling;
the mixed evolution strategy is used in a mixed mode based on a plurality of evolution strategies, and the objective function comprises a total operation time for calculating port tug scheduling.
The method has the advantages that the mixed evolution strategy is adopted, namely a plurality of evolution strategies are mixed to use the cyclic optimization objective function, global searching capability and calculation efficiency are better than that of single evolution strategies, the situation that the local optimal solution is involved is avoided, the optimal solution of the total operation time of port tug scheduling is used as the optimal scheme of port tug scheduling, the transportation cost is reduced, and the tug scheduling efficiency is improved.
Optionally, the vessel data includes a vessel length, a vessel draft, and a maximum tug demand, the active tug data includes active tug horsepower, and establishing the constraint condition table between the vessel and the active tug based on the vessel data and the active tug data includes:
classifying the vessels based on the vessel length, the vessel draft and the maximum tug demand to obtain classified vessels;
classifying the active tugs based on the active tugs horsepower to obtain classified tugs;
a table of constraints between the vessel and the active tug is established based on the classified vessel and the classified tug.
From the above description, it is clear that the types of active tugs and the number of active tugs selectable by different types of vessels can be specified based on the constraint condition table established by the classified vessels and the classified tugs.
Optionally, the objective function is used to calculate a total job time and a total carbon emission for port tug dispatch, wherein the total carbon emission is calculated by a carbon emission formula:
+…/>
wherein S is wn Representing the total carbon emission during operation of an active tug for ship service of type w number n, Z i The method comprises the steps that an active tug i position serving a ship with a w sequence number n is given to the ship, X is a ship starting position of the ship with the w sequence number n, Y is a ship target position of the ship with the w sequence number n, CF is carbon emission of a single active tug, B is fuel consumption, CT is carbon emission coefficient, C is carbon content in fuel, and Q is a heat value released by combustion.
According to the description, the calculation of the objective function includes the total carbon emission of the port tug schedule, that is, the optimal solution of the total carbon emission and the total operation time of the port tug schedule is used as the optimal scheme of the port tug schedule, so that the scheduling efficiency is improved, the carbon emission is reduced, and the resource is saved.
Optionally, the establishing an objective function based on the ship starting position, the ship target position and the active tug position, the objective function meeting the constraint condition table and circularly optimizing the objective function under the constraint condition table by adopting a mixed evolution strategy comprises:
setting time sequence constraint conditions of each tug serving only one search ship at one time sequence, and adding the time sequence constraint conditions into a constraint condition table to obtain a new constraint condition table;
acquiring service ships which receive tug service in the ports under M time sequences based on the current time, and randomly generating integers as initial tug demand based on ship data of the service ships in a preset upper limit interval and a preset lower limit interval;
performing individual coding on the service ship based on the initial tug demand, and generating an initial tug schedule, wherein the initial tug schedule meets the constraint condition table;
and acquiring a ship starting position, a ship target position and an active tug position in the initial tug schedule table to establish a target function, wherein the target function meets the constraint condition table, and the target function is circularly optimized by adopting a mixed evolution strategy under the constraint condition table.
According to the description, the new constraint condition table comprises time sequence constraint conditions, namely, each tug only serves one search ship at one time sequence, so that the objective function is circularly optimized under the new constraint condition table, and the objective function is more fit with reality.
Optionally, the obtaining the ship starting position, the ship target position and the active tug position in the initial tug schedule to establish an objective function, where the objective function meets the constraint condition table and the circularly optimizing the objective function by adopting a mixed evolution strategy under the constraint condition table includes:
acquiring the actual tug demand of the service ship, and correcting the initial tug schedule based on the actual tug demand to obtain a corrected tug schedule;
and acquiring a ship starting position, a ship target position and an active tug position in the corrected tug schedule table to establish an objective function, wherein the objective function meets the constraint condition table, and the objective function is circularly optimized by adopting a mixed evolution strategy under the constraint condition table.
According to the description, the initial tug schedule is corrected according to the actual tug demand of the service ship, a more reasonable and objective starting point is provided for the follow-up cycle optimization, and the accuracy of the objective function is ensured.
Optionally, the hybrid evolution strategy circularly optimizes the objective function using a three-point crossover algorithm, a genetic algorithm, and a local search strategy in sequence.
Optionally, the circularly optimizing the objective function using a three-point cross-exchange algorithm, a genetic algorithm, and a local search strategy sequentially includes:
randomly selecting N service ships from the corrected tug schedule by adopting a three-point cross exchange algorithm, and randomly selecting 3 fields from fields of the N service ships as cross points to perform cross-interval exchange field values to obtain an exchanged tug schedule, wherein the exchanged tug schedule meets the constraint condition table;
acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule table to establish a target function, wherein the target function meets the constraint condition table and adopts a genetic algorithm to circularly optimize the target function under the constraint condition table;
randomly selecting N service ships from the interchanged tug schedules by adopting a genetic algorithm, and randomly selecting 2 field exchange field values from the fields of the N service ships to obtain a mutated tug schedule, wherein the mutated tug schedule meets the constraint condition table;
and acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule table to establish an objective function, wherein the objective function meets the constraint condition table and is circularly optimized by adopting a local search strategy under the constraint condition table.
According to the description, the three-point cross exchange algorithm, the genetic algorithm and the local search strategy are adopted in sequence to circularly optimize the objective function, so that the diversity is increased and the global search capability is improved.
Optionally, the circularly optimizing the objective function under the constraint condition table by adopting a local search strategy includes:
acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule to establish an objective function, and calculating a first total carbon emission and a first total operation time of port tug scheduling of the objective function through a carbon emission formula;
inputting the first total carbon emission and the first total operation time into an evaluation index formula for evaluation calculation to obtain a first evaluation value;
circularly optimizing the objective function by adopting a local search strategy under the constraint condition table according to the first evaluation value;
wherein the circularly optimizing the objective function using a local search strategy under the constraint condition table according to the first evaluation value includes:
randomly selecting 2 field exchange field values from the exchanged tug schedule by adopting a local exchange search strategy to obtain a local exchange tug schedule, obtaining a ship starting position, a ship target position and an active tug position in the local exchange tug schedule, establishing a target function, and calculating a second total carbon emission and a second total operation time of port tug scheduling of the target function through a carbon emission formula;
inputting the second total carbon emission and the second total operation time into an evaluation index formula for evaluation calculation to obtain a second evaluation value;
if the second evaluation value is higher than the first evaluation value, circularly optimizing the objective function under the constraint condition table based on the local exchange tug schedule until reaching an exchange circulation threshold value, stopping circularly optimizing to obtain a final objective function, otherwise circularly optimizing the objective function under the constraint condition table based on the exchanged tug schedule by adopting a local exchange search strategy until reaching the exchange circulation threshold value, and stopping circularly optimizing to obtain the final objective function;
calculating a third total carbon emission and a third total operation time of final objective function port tug scheduling through a carbon emission formula, and inputting the third total carbon emission and the third total operation time into an evaluation index formula to perform evaluation calculation to obtain a third evaluation value;
simultaneously adopting a local insertion search strategy to randomly select the positions of two fields from the interchanged tug schedule, wherein one position is used as an insertion position, inserting the field value of the other position into one position after the insertion position, sequentially advancing the field value after the other position to obtain a local insertion tug schedule, acquiring a ship starting position, a ship target position and an active tug position in the local insertion tug schedule, establishing an objective function, and calculating a fourth total carbon emission and a fourth total operation time of port tug scheduling of the objective function through a carbon emission formula;
inputting the fourth total carbon emission and the fourth total operation time into an evaluation index formula to perform evaluation calculation to obtain a fourth evaluation value;
if the fourth evaluation value is higher than the first evaluation value, circularly optimizing the objective function under the constraint condition table based on the local insertion tug schedule until reaching an insertion circulation threshold value, stopping circularly optimizing to obtain a final objective function, otherwise circularly optimizing the objective function under the constraint condition table based on the interchanged tug schedule by adopting a local insertion search strategy until reaching an insertion circulation threshold value, and stopping circularly optimizing to obtain the final objective function;
calculating a fifth total carbon emission and a fifth total operation time of final objective function port tug scheduling through a carbon emission formula, and inputting the fifth total carbon emission and the fifth total operation time into an evaluation index formula to perform evaluation calculation to obtain a fifth evaluation value;
and if the fifth evaluation value is higher than the third evaluation value, acquiring an objective function corresponding to the fifth evaluation value, otherwise, acquiring the objective function corresponding to the third evaluation value.
According to the description, when the local search strategy is used for circularly optimizing the objective function, the local exchange search strategy and the local insertion search strategy are simultaneously used for circularly optimizing, the objective functions obtained finally are evaluated, and the objective function with higher evaluation value is selected from the objective functions, so that the optimal scheme of port tug dispatching is obtained, and the problem of sinking into the local optimal solution is avoided, and the accuracy of the optimal scheme is improved.
Optionally, the preset upper and lower limit interval is [1 ], the maximum tug demand in the ship data of the service ship ].
From the above description, it is known that integers are randomly generated as the initial tug demand in the upper and lower limit intervals of [1, maximum tug demand in the ship data of the service ship ], so as to ensure the reasonability of the initial tug demand.
In a second aspect, there is provided an apparatus for port tow boat dispatch comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method for port tow boat dispatch according to the first aspect when executing the computer program.
The second aspect provides a device for scheduling port tugs, and the corresponding technical effects refer to the related description of the method for scheduling port tugs provided in the first aspect.
Drawings
FIG. 1 is a flow chart of a method for port tug dispatch provided by an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for port tug dispatch according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a device for scheduling tugs at a port according to an embodiment of the present invention.
[ reference numerals description ]
1. A device for scheduling port tugs;
2. a processor;
3. a memory.
Detailed Description
In order that the above-described aspects may be better understood, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Example 1
Referring to fig. 1 to 2, the present invention provides a method for scheduling port tugs, comprising the steps of:
s1, acquiring all ship data and active tug data of a port, and establishing a constraint condition table between a ship and an active tug based on the ship data and the active tug data, wherein the ship data comprises a ship starting position and a ship target position, and the active tug data comprises an active tug position;
in this embodiment, the vessel data includes, but is not limited to, vessel length, vessel draft, and maximum tug demand, and the active tug data includes, but is not limited to, active tug horsepower.
At this time, the creating a constraint condition table between the ship and the active tug based on the ship data and the active tug data in step S1 includes:
s11, classifying the ships based on the ship length, the ship draft and the maximum tug demand, so as to obtain classified ships;
in this example, vessels are classified according to Table 1. A vessel classification criteria table, wherein the number of tugs refers to the maximum tug demand:
TABLE 1 Ship classification standard table
S12, classifying the active tugs based on the horsepower of the active tugs to obtain classified tugs;
in this embodiment, active tugs are classified based on their horsepower as shown in Table 2, where the number refers to the number of active tugs in the port that correspond to the tug type:
TABLE 2 classified tug Table
S13, establishing a constraint condition table between the ship and the active tug based on the classified ship and the classified tug.
In this embodiment, the constraint condition table between the ship and the active tug is established based on the classified ships of step S11 and the classified tugs of step S12 is shown in table 3, wherein tug types a, … I are numbered from low to high with respect to the active tug horsepower:
TABLE 3 constraint Condition list
S2, establishing an objective function based on the ship starting position, the ship target position and the active tug position, wherein the objective function meets the constraint condition table, and circularly optimizes the objective function by adopting a mixed evolution strategy under the constraint condition table to obtain an optimal solution of the objective function, and taking the optimal solution as an optimal scheme of port tug scheduling;
in this embodiment, establishing an objective function based on the ship starting position, the ship target position, and the active tug position in step S2, where the objective function satisfies the constraint condition table and circularly optimizing the objective function using a hybrid evolution strategy under the constraint condition table includes:
s21, setting time sequence constraint conditions of each tug serving only one search ship at one time sequence, and adding the time sequence constraint conditions into a constraint condition table to obtain a new constraint condition table;
in this embodiment, one time sequence is set to 2 hours, i.e. each tug only serves one search vessel within 2 hours.
S22, acquiring service ships which receive tug service in the ports under M time sequences based on the current time, and randomly generating integers as initial tug demand based on ship data of the service ships in a preset upper limit interval and a preset lower limit interval;
in this embodiment, a service ship receiving tug service in a port under M time sequences is acquired based on the current time, where M is set to 3, that is, the service ship receiving tug service in the port under 3 time sequences is acquired based on the current time, and M may be set according to actual requirements, where the preset upper and lower limits are [1, the maximum tug demand in the ship data of the service ship ], and if the maximum tug demand in the ship data of the service ship is 4, the integer 2 or 3 randomly generated in the interval is used as the initial tug demand.
S23, carrying out individual coding on the service ship based on the initial tug demand, and generating an initial tug schedule, wherein the initial tug schedule meets the constraint condition table;
in this embodiment, a matrix is built based on each berth of the port, and the distance between the berths is regarded as a point on the matrix, for example, a mansion port may be obtained as a port berth distribution matrix table, where P1, P2, P3, P4, P5, P6, and P7 represent each berth, and the numbers in table 4 represent the straight line distances between the berths:
TABLE 4 Port berth distribution matrix table
TABLE 5 initial tug schedule
In a specific embodiment, 6 service ships receiving tug service in ports at 3 time sequences are obtained based on the current time, the initial tug demand is 2, the corresponding tugs are tugs A and tugs B, the service ships are individually coded to generate an initial tug schedule as shown in table 5, wherein the field value of the field tug A represents the serial number of the optional tug type A, and the field value of the field tug B represents the serial number of the optional tug type B.
S24, acquiring a ship starting position, a ship target position and an active tug position in the initial tug schedule table, and establishing an objective function, wherein the objective function meets the constraint condition table, and the objective function is circularly optimized by adopting a mixed evolution strategy under the constraint condition table.
In this embodiment, the objective function is used to calculate the total operation time of port tug dispatch, and the objective function is established according to the ship starting position, the ship target position and the active tug position in the initial tug dispatch table, and the initial tug position in the active tug position corresponding table is as follows:
wherein T is an objective function,total work time scheduled for tug of service vessel of vessel type w number n, Z 1 For the initial position of tug A, Z 2 For the initial position of tug B, X is the initial position of the service vessel, Y is the target position of the service vessel, < >>For the running speed of tug A, +.>For the running speed of tug B, +.>The operating speed of the service vessel of the vessel type w number n.
Wherein, step S24 includes:
s241, acquiring the actual tug demand of the service ship, and correcting the initial tug schedule based on the actual tug demand to obtain a corrected tug schedule;
in this embodiment, since the initial tug schedule is generated according to the initial tug demand, the actual tug demand of the service ship needs to be obtained, for example, if the actual tug demand is 1, the initial tug schedule needs to be modified, that is, the tug demand is changed to 1, and the initial tug schedule is narrowed, so as to obtain the modified tug schedule.
S242, acquiring a ship starting position, a ship target position and an active tug position in the corrected tug schedule table, and establishing an objective function, wherein the objective function meets the constraint condition table, and the objective function is circularly optimized by adopting a mixed evolution strategy under the constraint condition table.
In this embodiment, the hybrid evolution strategy in step S242 circularly optimizes the objective function by sequentially using a three-point cross-over algorithm, a genetic algorithm, and a local search strategy, including:
s2421, randomly selecting N service ships from the corrected tug schedule by adopting a three-point interchange algorithm, and randomly selecting 3 fields from fields of the N service ships as intersection points to perform cross-interval interchange field values to obtain an interchanged tug schedule, wherein the interchanged tug schedule meets the constraint condition table;
in this embodiment, N is an integer greater than or equal to 2, for example, when N is 2, 2 service vessels are randomly selected from the modified tug schedule, service vessel 1 and service vessel 2, and 3 fields are randomly selected from the fields of the 2 service vessels, such as: the ship type, the tug A and the initial position of the tug A are used as crossing points, so that the corrected tug schedule is divided into 4 sections, and field values are interchanged by adopting a method of interval interchange, so that the interchanged tug schedule is obtained.
S2422, acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule table, and establishing an objective function, wherein the objective function meets the constraint condition table and circularly optimizes the objective function by adopting a genetic algorithm under the constraint condition table;
s2423, randomly selecting N service ships from the interchanged tug schedules by adopting a genetic algorithm, and randomly selecting 2 field exchange field values from fields of the N service ships to obtain a mutated tug schedule, wherein the mutated tug schedule meets the constraint condition table;
in this embodiment, the ship start position, the ship target position, and the active tug position are obtained from the exchanged tug schedule obtained in step S2421, and the objective function is re-established, and a genetic algorithm is used to select N service ships, such as 3 service ships, from the N service ships, and 2 fields are randomly selected from the three service ship fields, such as: the initial position of the ship and the tug A exchange field values, so that a mutated tug schedule is obtained.
S2424, acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule table, and establishing an objective function, wherein the objective function meets the constraint condition table and is circularly optimized by adopting a local search strategy under the constraint condition table.
In this embodiment, the circularly optimizing the objective function using the local search strategy under the constraint condition table in step S2424 includes:
s24241, acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule to establish an objective function, and calculating a first total carbon emission and a first total operation time of port tug scheduling of the objective function through a carbon emission formula;
s24242, inputting the first total carbon emission and the first total operation time into an evaluation index formula for evaluation calculation to obtain a first evaluation value;
in this embodiment, the evaluation index formula is:
wherein,,=min (a×t+β×s), a+β=1, a represents a total operating time scaling factor, and β represents a total carbon emission scaling factor.
S24243, circularly optimizing the objective function by adopting a local search strategy under the constraint condition table according to the first evaluation value;
wherein, the circularly optimizing the objective function according to the first evaluation value by using the local search strategy under the constraint condition table in step S24243 includes:
s242431, randomly selecting 2 field exchange field values from the exchanged tug schedule by adopting a local exchange search strategy to obtain a local exchange tug schedule, obtaining a ship starting position, a ship target position and an active tug position in the local exchange tug schedule, establishing a target function, and calculating a second total carbon emission and a second total operation time of port tug scheduling of the target function through a carbon emission formula;
s242432, inputting the second total carbon emission and the second total operation time into an evaluation index formula for evaluation calculation to obtain a second evaluation value;
s242433, if the second evaluation value is higher than the first evaluation value, circularly optimizing the objective function under the constraint condition table based on the local exchange tug schedule until reaching an exchange circulation threshold value, stopping circularly optimizing to obtain a final objective function, otherwise circularly optimizing the objective function under the constraint condition table based on the exchanged tug schedule by adopting a local exchange search strategy until reaching the exchange circulation threshold value, and stopping circularly optimizing to obtain the final objective function;
in this embodiment, the interchange loop threshold is set to 500, i.e., loop optimization is stopped when the local interchange search strategy is used to loop optimization 500 times.
S242434, calculating a third total carbon emission and a third total operation time of final objective function port tug scheduling through a carbon emission formula, and inputting the third total carbon emission and the third total operation time into an evaluation index formula to perform evaluation calculation to obtain a third evaluation value;
s242435, randomly selecting the positions of two fields from the interchanged tug schedule by adopting a local insertion search strategy, wherein one position is used as an insertion position, inserting the field value of the other position into one position after the insertion position, sequentially advancing the field value after the other position to obtain a local insertion tug schedule, acquiring a ship starting position, a ship target position and an active tug position in the local insertion tug schedule, establishing an objective function, and calculating a fourth total carbon emission and a fourth total operation time of port tug scheduling of the objective function through a carbon emission formula;
s242436, inputting the fourth total carbon emission and the fourth total operation time into an evaluation index formula for evaluation calculation to obtain a fourth evaluation value;
s242437, if the fourth evaluation value is higher than the first evaluation value, circularly optimizing the objective function under the constraint condition table based on the local insertion tug schedule until the insertion cycle threshold is reached, stopping circularly optimizing to obtain a final objective function, otherwise circularly optimizing the objective function under the constraint condition table based on the interchanged tug schedule by adopting a local insertion search strategy until the insertion cycle threshold is reached, stopping circularly optimizing to obtain the final objective function;
in this embodiment, the insert loop threshold is set to 500, i.e., loop optimization is stopped when the loop optimization reaches 500 times using the local insert search strategy.
S242438, calculating a final objective function port tug scheduled fifth total carbon emission and fifth total operation time through a carbon emission formula, and inputting the fifth total carbon emission and the fifth total operation time into an evaluation index formula to perform evaluation calculation to obtain a fifth evaluation value;
s242439, if the fifth evaluation value is higher than the third evaluation value, acquiring an objective function corresponding to the fifth evaluation value, otherwise, acquiring the objective function corresponding to the third evaluation value.
And S3, the hybrid evolution strategy is used in a hybrid way based on a plurality of evolution strategies, and the objective function comprises a total operation time for calculating port tug scheduling.
In this embodiment, the objective function in step S3 is used to calculate the total operating time and total carbon emission of the port tug schedule, where the total carbon emission is calculated by the carbon emission formula:
+…/>
wherein S represents the total carbon emission of port tug dispatch, S wn Representing the total carbon emission during operation of an active tug for ship service of type w number n, Z i The method comprises the steps that an active tug i position serving a ship with a w sequence number n is given to the ship, X is a ship starting position of the ship with the w sequence number n, Y is a ship target position of the ship with the w sequence number n, CF is carbon emission of a single active tug, B is fuel consumption, CT is carbon emission coefficient, C is carbon content in fuel, and Q is a heat value released by combustion.
In one embodiment, the ship type 1 number 1 ship starting position is 55, the ship target position is 555, two active tugs serving the ship are active tugs 1 and 2, respectively, the active tugs 1 position is 85, the active tugs 2 position is 95, the fuel consumption of the active tugs 1 is 180kg, the fuel consumption of the active tugs 2 is 90kg, the carbon content in the active tugs 1 fuel is 75%, the carbon content in the active tugs 2 fuel is 80%, the heat value released by the active tugs 1 combustion is 22MJ/kg, and the heat value released by the active tugs 2 combustion is 28MJ/kg, so the carbon emission coefficient of the active tugs 1 is: (44/12) × (0.75/22) =0.125, the carbon emissions of active tug 1 are: 180 x 0.125=22.5, the carbon emission coefficient of active tug 2 is: (44/12) × (0.8/28) =0.105, the carbon emissions of active tug 2 are: 90 x 0.105 = 9.45, total carbon emission S during operation of an active tug serving a vessel of type 1 number 1 11 =（|85-55|+|555-55|）*22.5+（|95-55|+|555-55|*9.45）=17028MJ。
Example two
Referring to fig. 3, an apparatus 1 for port tug dispatch includes a memory 3, a processor 2, and a computer program stored in the memory 3 and executable on the processor 2, wherein the processor 2 implements the steps of the first embodiment when executing the computer program.
Since the system/device described in the foregoing embodiments of the present invention is a system/device used for implementing the method of the foregoing embodiments of the present invention, those skilled in the art will be able to understand the specific structure and modification of the system/device based on the method of the foregoing embodiments of the present invention, and thus will not be described in detail herein. All systems/devices used in the methods of the above embodiments of the present invention are within the scope of the present invention.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the terms first, second, third, etc. are for convenience of description only and do not denote any order. These terms may be understood as part of the component name.
Furthermore, it should be noted that in the description of the present specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with the embodiment or example being included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art upon learning the basic inventive concepts. Therefore, the appended claims should be construed to include preferred embodiments and all such variations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, the present invention should also include such modifications and variations provided that they come within the scope of the following claims and their equivalents.
Claims (10)
1. A method for port tug dispatch comprising:
acquiring all ship data and active tug data of a port, and establishing a constraint condition table between a ship and an active tug based on the ship data and the active tug data, wherein the ship data comprises a ship starting position and a ship target position, and the active tug data comprises an active tug position;
establishing an objective function based on the ship starting position, the ship target position and the active tug position, wherein the objective function meets the constraint condition table, and circularly optimizes the objective function by adopting a mixed evolution strategy under the constraint condition table to obtain an optimal solution of the objective function, and taking the optimal solution as an optimal scheme of port tug scheduling;
the mixed evolution strategy is used in a mixed mode based on a plurality of evolution strategies, and the objective function comprises a total operation time for calculating port tug scheduling.
2. The method of port tug dispatch of claim 1, wherein the vessel data includes vessel length, vessel draft and maximum tug demand, the active tug data includes active tug horsepower, and establishing a constraint table between a vessel and an active tug based on the vessel data and the active tug data includes:
classifying the vessels based on the vessel length, the vessel draft and the maximum tug demand to obtain classified vessels;
classifying the active tugs based on the active tugs horsepower to obtain classified tugs;
a table of constraints between the vessel and the active tug is established based on the classified vessel and the classified tug.
3. The method of port tow boat dispatch of claim 1 wherein said objective function is used to calculate a total operating time and a total carbon emissions for port tow boat dispatch, wherein said total carbon emissions are calculated by a carbon emissions formula:
+…/>
wherein S is wn Representing the total carbon emission during operation of an active tug for ship service of type w number n, Z i The method comprises the steps that an active tug i position serving a ship with a w sequence number n is given to the ship, X is a ship starting position of the ship with the w sequence number n, Y is a ship target position of the ship with the w sequence number n, CF is carbon emission of a single active tug, B is fuel consumption, CT is carbon emission coefficient, C is carbon content in fuel, and Q is a heat value released by combustion.
4. The method of port tug dispatch of claim 1, wherein the establishing an objective function based on the vessel start position, vessel target position, and active tug position, the objective function satisfying the constraint table and circularly optimizing the objective function using a hybrid evolution strategy under the constraint table comprises:
setting time sequence constraint conditions of each tug serving only one search ship at one time sequence, and adding the time sequence constraint conditions into a constraint condition table to obtain a new constraint condition table;
acquiring service ships which receive tug service in the ports under M time sequences based on the current time, and randomly generating integers as initial tug demand based on ship data of the service ships in a preset upper limit interval and a preset lower limit interval;
performing individual coding on the service ship based on the initial tug demand, and generating an initial tug schedule, wherein the initial tug schedule meets the constraint condition table;
and acquiring a ship starting position, a ship target position and an active tug position in the initial tug schedule table to establish a target function, wherein the target function meets the constraint condition table, and the target function is circularly optimized by adopting a mixed evolution strategy under the constraint condition table.
5. The method of port tug dispatch of claim 4, wherein said obtaining a vessel start position, a vessel target position, an active tug position in said initial tug dispatch table establishes an objective function that satisfies said constraint condition table and that is circularly optimized using a hybrid evolution strategy under said constraint condition table comprises:
acquiring the actual tug demand of the service ship, and correcting the initial tug schedule based on the actual tug demand to obtain a corrected tug schedule;
and acquiring a ship starting position, a ship target position and an active tug position in the corrected tug schedule table to establish an objective function, wherein the objective function meets the constraint condition table, and the objective function is circularly optimized by adopting a mixed evolution strategy under the constraint condition table.
6. The method of port tug dispatch of claim 4, wherein the hybrid evolution strategy is to circularly optimize the objective function using a three-point crossover algorithm, a genetic algorithm, and a local search strategy in sequence.
7. The method of port tow boat dispatch of claim 6 wherein said sequentially using three-point crossover algorithm, genetic algorithm and local search strategy to cyclically optimize said objective function comprises:
randomly selecting N service ships from the corrected tug schedule by adopting a three-point cross exchange algorithm, and randomly selecting 3 fields from fields of the N service ships as cross points to perform cross-interval exchange field values to obtain an exchanged tug schedule, wherein the exchanged tug schedule meets the constraint condition table;
acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule table to establish a target function, wherein the target function meets the constraint condition table and adopts a genetic algorithm to circularly optimize the target function under the constraint condition table;
randomly selecting N service ships from the interchanged tug schedules by adopting a genetic algorithm, and randomly selecting 2 field exchange field values from the fields of the N service ships to obtain a mutated tug schedule, wherein the mutated tug schedule meets the constraint condition table;
and acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule table to establish an objective function, wherein the objective function meets the constraint condition table and is circularly optimized by adopting a local search strategy under the constraint condition table.
8. The method of port tow boat scheduling of claim 7 wherein said employing a local search strategy loop under said constraint table to optimize said objective function comprises:
acquiring a ship starting position, a ship target position and an active tug position in the interchanged tug schedule to establish an objective function, and calculating a first total carbon emission and a first total operation time of port tug scheduling of the objective function through a carbon emission formula;
inputting the first total carbon emission and the first total operation time into an evaluation index formula for evaluation calculation to obtain a first evaluation value;
circularly optimizing the objective function by adopting a local search strategy under the constraint condition table according to the first evaluation value;
wherein the circularly optimizing the objective function using a local search strategy under the constraint condition table according to the first evaluation value includes:
randomly selecting 2 field exchange field values from the exchanged tug schedule by adopting a local exchange search strategy to obtain a local exchange tug schedule, obtaining a ship starting position, a ship target position and an active tug position in the local exchange tug schedule, establishing a target function, and calculating a second total carbon emission and a second total operation time of port tug scheduling of the target function through a carbon emission formula;
inputting the second total carbon emission and the second total operation time into an evaluation index formula for evaluation calculation to obtain a second evaluation value;
if the second evaluation value is higher than the first evaluation value, circularly optimizing the objective function under the constraint condition table based on the local exchange tug schedule until reaching an exchange circulation threshold value, stopping circularly optimizing to obtain a final objective function, otherwise circularly optimizing the objective function under the constraint condition table based on the exchanged tug schedule by adopting a local exchange search strategy until reaching the exchange circulation threshold value, and stopping circularly optimizing to obtain the final objective function;
calculating a third total carbon emission and a third total operation time of final objective function port tug scheduling through a carbon emission formula, and inputting the third total carbon emission and the third total operation time into an evaluation index formula to perform evaluation calculation to obtain a third evaluation value;
simultaneously adopting a local insertion search strategy to randomly select the positions of two fields from the interchanged tug schedule, wherein one position is used as an insertion position, inserting the field value of the other position into one position after the insertion position, sequentially advancing the field value after the other position to obtain a local insertion tug schedule, acquiring a ship starting position, a ship target position and an active tug position in the local insertion tug schedule, establishing an objective function, and calculating a fourth total carbon emission and a fourth total operation time of port tug scheduling of the objective function through a carbon emission formula;
inputting the fourth total carbon emission and the fourth total operation time into an evaluation index formula to perform evaluation calculation to obtain a fourth evaluation value;
if the fourth evaluation value is higher than the first evaluation value, circularly optimizing the objective function under the constraint condition table based on the local insertion tug schedule until reaching an insertion circulation threshold value, stopping circularly optimizing to obtain a final objective function, otherwise circularly optimizing the objective function under the constraint condition table based on the interchanged tug schedule by adopting a local insertion search strategy until reaching an insertion circulation threshold value, and stopping circularly optimizing to obtain the final objective function;
calculating a fifth total carbon emission and a fifth total operation time of final objective function port tug scheduling through a carbon emission formula, and inputting the fifth total carbon emission and the fifth total operation time into an evaluation index formula to perform evaluation calculation to obtain a fifth evaluation value;
and if the fifth evaluation value is higher than the third evaluation value, acquiring an objective function corresponding to the fifth evaluation value, otherwise, acquiring the objective function corresponding to the third evaluation value.
9. The method for port tug dispatch of claim 4, wherein the preset upper and lower limit interval is [1 ], the maximum tug demand in the ship data of the service ship ].
10. An apparatus for port tug scheduling comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 9 when executing the computer program.
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