Optimization Method for Ship Traffic Organization Based on Improved Multi-Objective Imperialist Competitive Algorithm

Abstract

The present invention provides a method for optimizing ship traffic organization based on an improved multi-objective imperialist competitive algorithm, which relates to the technical field of optimizing port ship traffic organization. It mainly includes: First, an initial empire is constructed according to the designed multi-objective ship sequence cost function based on the total waiting and total scheduling time of ships; Then, an adaptive ship safety time headway revolution operator is designed to perform revolution operations on colonies, simulating unexpected changes in colonies; Then, a multi-objective discrete threshold division strategy is designed to adaptively select fission objects and perform fission operations. The present invention provides a new method for solving the problem of optimizing ship traffic organization, which can solve the problem of easy premature convergence and easy local optimum in the optimization when the imperialist competitive algorithm is simply used to solve the ship traffic scheduling scheme, and has the positive effect of improving the operation efficiency of ships entering and leaving the port.

Description

Technical Field

[0001] The present invention relates to the technical field of port ship traffic organization optimization, and particularly belongs to a one-way channel ship traffic organization optimization method based on an improved multi-objective imperial competitive algorithm with a revolutionary fission operator self-adaptive evolution strategy. Background Art

[0002] With the development of the enlargement of ships and the increase in the number of ships entering and leaving the port, it has brought great pressure to the port channel. The difficulty of ship scheduling operations at the port has also increased accordingly. The scheduling process itself is also affected by various factors and requires the coordination of two departments, namely the terminal company and the vessel traffic service center (VTS). The original manual scheduling is difficult to take into account numerous considerations and meet the requirements of both safety and efficiency at the same time. There is great room for development in shortening the waiting time of ships in the port, improving the port service quality and efficiency, etc., which is crucial for the port environment and the economic benefits of the port and ships. The ship scheduling problem at the port has also received extensive attention from researchers.

[0003] The research on traditional ship scheduling optimization problems mainly focuses on the scheduling of terminal resources such as berths and quay cranes. However, the port ship operation is a continuous operation process. Maximizing the operation efficiency of the terminal may lead to an unreasonable order of ships entering and leaving the channel, reducing the overall ship entering and leaving port efficiency. Therefore, to improve the ship entering and leaving port scheduling efficiency, taking the channel as the entry point and coordinating the berth resources to form a unified ship scheduling plan. Through investigation, it is found that the port scheduling department's expectation for the scheduling result is to minimize the scheduling time and at the same time take into account the shortest waiting time of the ships. And shipping companies and berth operation companies hope that the waiting time of ships is as little as possible. Therefore, in order to meet the scheduling requirements of different departments, taking the total ship entering and leaving port scheduling time and the total ship waiting time in the port as the goals, and selecting the best among individuals based on the Pareto dominance relationship, taking into account the interests of the port side and the ship side in the port ship scheduling process. To sum up, researching efficient methods to find an information-based and intelligent solution for the ship traffic organization optimization in the port area has important practical significance and application value.

[0004] The problem of optimizing ship traffic organization in a one-way waterway belongs to discrete optimization problems and NP-Hard problems. There are numerous constraints in this problem, making it difficult to solve. With the demand for algorithm efficiency in practical problems, scholars have developed intelligent optimization algorithms such as genetic algorithms and simulated annealing algorithms to meet the different needs of decision-makers. As a new intelligent algorithm inspired by social and political behaviors, the Imperialist Competitive Algorithm (ICA) can effectively coordinate global search and local search and has begun to be gradually applied to the field of scheduling optimization. The traditional imperialist competitive algorithm mainly solves single-objective continuous optimization problems, and when solving ship scheduling schemes, it is prone to premature convergence and easy to fall into local optima. Summary of the Invention

[0005] The present invention provides a method for optimizing ship traffic organization based on an improved multi-objective imperialist competitive algorithm, which can solve the problems of premature convergence and easy falling into local optima when using only the imperialist competitive algorithm to solve ship traffic scheduling schemes. The technical means adopted by the present invention are as follows:

[0006] A method for optimizing ship traffic organization based on an improved multi-objective imperialist competitive algorithm includes the following steps:

[0007] Step S1: Obtain the constraint conditions of the multi-objective ship traffic organization optimization problem of a one-way waterway, such as flow conversion, safety time interval, berth conflict resolution, and tide riding for large ships entering and leaving the port, during the optimization process, and determine the objectives to be optimized, and establish a corresponding multi-objective optimization function;

[0008] Step S2: Use an improved multi-objective imperialist competitive algorithm based on the adaptive evolutionary strategy of the revolutionary fission operator to solve the ship scheduling scheme, including:

[0009] According to the characteristics of the problem, for multi-objective discrete optimization, construct a multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships, which is used to calculate the cost value of the ship scheduling scheme for each country.

[0010] Design an adaptive ship safety time interval revolutionary operator during the revolutionary process, introduce variable neighborhood search in the revolutionary operation, and combine it with the selection method of revolutionary objects with self-adaptability to enhance the search ability of the algorithm.

[0011] After the imperial competition operation, add a fission operation and design a multi-objective discrete threshold division strategy to alleviate the premature convergence of the algorithm;

[0012] Step S3: Perform iterative operations and output the optimized ship scheduling scheme.

[0013] Furthermore, step S2 includes the following steps:

[0014] Step S21: Parameter initialization, including setting the number of countries \(n\) for the algorithm pop , the number of colonial countries \(n\) imp , the maximum number of iterations \(i\) max , the proportion \(\omega\) of the colony in calculating the overall imperial power, and the threshold \(K\) in the fission operation;

[0015] Step S22: Construct an initial empire according to the designed multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships, and determine the encoding and decoding methods of country individuals;

[0016] Step S23: Perform assimilation operations on the colonies, design an adaptive ship safety time interval revolution operator for the revolution operations of the colonies, simulate unexpected changes in the colonies, and after the assimilation and revolution operations, perform colonial country updates and inter-empire competition operations;

[0017] Step S24: Design a multi-objective discrete threshold division strategy to adaptively select fission objects and perform fission operations;

[0018] Step S25: Eliminate the empires without colonies, and according to the setting of the maximum number of iterations \(i\) of the algorithm in the parameters max and the setting of the remaining number of empires finally retained, judge whether the algorithm meets the iteration termination condition. If so, the algorithm terminates, and the ship scheduling plan corresponding to the remaining colonial country individuals is output, which is the ship scheduling plan that makes the total waiting time of the ship in the port and the total scheduling time of the ship entering and leaving the port relatively optimal; otherwise, go to Step S23.

[0019] Furthermore, Step S22 includes the following steps:

[0020] Step S221: Randomly generate \(n\) pop initial countries, and calculate the objective function values corresponding to each country individual, that is, the total waiting time of the ship in the port and the total scheduling time of the ship entering and leaving the port;

[0021] Step S222: Perform non-dominated sorting on the objective values corresponding to the country individuals, and calculate the corresponding non-dominated sorting order value \(R\) co,ra and crowding distance \(D\) co,cr ;

[0022] Step S223: According to the problem characteristics, for multi-objective discrete optimization, the constructed multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships is shown in formula (3), and calculate the cost value of each country according to the cost function;

[0023]

[0024] where, \(D\) co,crDenote the non-dominated sorting crowding distance of national individuals; R co,ra Denote the non-dominated sorting order value of national individuals; α and β are algorithm parameters, co represents a country, cr represents the non-dominated sorting crowding distance, and ra represents the non-dominated sorting order value;

[0025] Step S224: Select the top n imp countries with better cost values as colonial countries, and determine the number of colonies of each empire according to the proportion of the cost of colonial countries in the total cost, randomly distribute the colonies to the empires, and generate colonial countries and colonies.

[0026] Furthermore, in step S22, the national individual coding adopts the permutation coding method, that is, each national individual coding is a sequence composed of a group of ships to be scheduled; the decoding process is to convert the national individual into the in-out port sequence of the ships, and then arrange the start and end in-out port times and the times passing through each key point of the waterway for each ship according to the in-out port sequence of the ships and the ship safety time interval constraint, flow conversion constraint and berth conflict resolution constraint, so as to generate a ship scheduling plan.

[0027] Furthermore, the assimilation operation in step S23 includes the following steps:

[0028] Step S231: Generate two random positions and exchange the segments in the middle of the two positions.

[0029] Step S232: Step S231 will result in duplicate segments in the same country. The partial mapping method is used to eliminate the conflicts.

[0030] Step S233: Retain the colonies after the exchange, and keep the colonial countries unchanged, that is, do not adopt the colonial countries after the exchange.

[0031] Furthermore, the revolution operation in step S23 is specifically to simulate an unexpected change by designing an adaptive ship safety time interval revolution operator to prevent falling into a local optimum during the iteration process and realize the colony revolution operation. The adaptive ship safety time interval revolution operator includes the following steps:

[0032] Step S234: Through a selection method of revolutionary objects with self-adaptability, judge whether the colony is a revolutionary object, calculate the non-dominated sorting order value and crowding distance of national individuals in the empire. In the current iteration, if the colony satisfies the non-dominated sorting order value of 1 in the empire, that is, other national individuals in the empire cannot dominate the colony, then go to step S235; otherwise, no revolution operation is performed in this iteration, and go to step S236;

[0033] Step S235: Conduct variable neighborhood search on the colonies selected as the revolutionary objects, including using two neighborhood structures that will not generate illegal solutions, specifically including:

[0034] Neighborhood structure 1: In the national individual, randomly generate four positions, reverse the order of the corresponding ships at these four positions, and accordingly adjust the start and end times of the ships entering and leaving the port and the times passing through each key point of the waterway according to the constraints of the ship traffic organization optimization problem of one-way waterways such as ship safety time intervals and flow conversion.

[0035] Neighborhood structure 2: In the national individual, randomly generate two positions, shuffle the corresponding ship sequence between these two positions, and adjust the start and end times of the ships entering and leaving the port and the times passing through each key point of the waterway according to the constraints of the ship traffic organization optimization problem of one-way waterways such as ship safety time intervals and flow conversion.

[0036] Step S236: Conduct fast non-dominated sorting within the empire. If the cost value of the colony is better than that of the corresponding colonial country, then the colony replaces the colonial country and becomes the new colonial country within the empire; otherwise, no change occurs.

[0037] Furthermore, the fission operation described in step S24 includes:

[0038] Step S241: Judge whether the empire is a fission object, select the fission object by designing a multi-objective discrete threshold division strategy, and recalculate the non-dominated sorting order value of the national individuals within the empire. In the current iteration, if there exists a colony that satisfies the condition that the difference in order value from the colonial country is less than or equal to the threshold K and the corresponding ship scheduling sequences are different, then the colonial country within the empire is denoted as imp old Go to step S242; otherwise, no fission operation is performed in this iteration, and go to step S25.

[0039] Step S242: Take the colony that meets the conditions as the colonial country of the new empire, denoted as imp new , according to imp old and imp new Determine the number of colonies assigned to the empire corresponding to the colonial country according to the cost sizes of imp

[0040] Furthermore, step S1 includes establishing a multi-objective optimization function with the minimum total waiting time of ships in port and the minimum total scheduling time of ships entering and leaving the port as the optimization objectives. The multi-objective optimization function is expressed as:

[0041]

[0042]

[0043] Among them, \(S\) is the set of ships \(S = \{1, 2, \ldots, |S|\}\), \(i, j\in S\), \(i < j\); \(T\) r,i and \(T\) le,i are respectively the start time and end time when ship \(i\) enters / leaves the port; \(T\) i is the application time when ship \(i\) enters / leaves the port.

[0044] Furthermore, the constraint conditions for the multi-objective ship traffic organization optimization problem of the one-way waterway in step \(S1\) include:

[0045] The tidal constraint for large ships entering and leaving the port is:

[0046]

[0047] The time constraint for ships to start entering / leaving the port is:

[0048]

[0049] The flow conversion constraint is:

[0050] (T r,i -T r,j -M\times q i,j -t β,i -t2)\times(D i -D j ) 2 \(\geq0\)

[0051] The time constraint for ships to pass through the waterway is:

[0052]

[0053] The safety time interval constraint is:

[0054] (T r,i -T r,j +M\times q i,j -t1-\lambda i,j t3)\times(1-(D i -D j ) 2 )\(\geq0\)

[0055] (T le,i -T le,j +M\times q i,j -t1-\lambda i,j t3)\times(1-(D / / There seems to be a repetition here which might be a mistake in the original text i -D j ) 2 )\(\geq0\)

[0056] The berth conflict resolution constraint is:

[0057] 1 - B i,m +(1 - D i)×M≥0 t=T r,i

[0058] Among them, S is the set of ships S = {1, 2,..., |S|}, i, j ∈ S, i < j; T r,i and T le,i are respectively the start time and end time for ship i to enter / leave the port; t1, t2, and t3 are respectively the safety time intervals for ships traveling in the same direction, the safety time intervals for ships traveling in opposite directions, and the additional safety time intervals required due to the berth order; t β,i and d β,i are respectively the time for ship i to reach the berth from the channel entrance in theory and the distance for ship i to reach the berth from the channel entrance in theory; v i is the average speed of ship i in theory; T i and are respectively the application time for ship i to enter / leave the port and the adjusted application time for ship i to enter / leave the port; D i = 1 indicates that ship i is an inbound ship, otherwise D i = 0; q i,j = 1 indicates that ship j enters / leaves the port later than ship i, otherwise q i,j = 0; λ i,j = 1 indicates that when ship i enters the port earlier than ship j, it docks at a relatively outer berth, otherwise λ i,j = 0; B i,m = 1 indicates that the berth m assigned to ship i is occupied, otherwise B i,m = 0; T tr,i and T td,i are respectively the start time and end time for ship i to enter / leave the port at high tide; M is the maximum value.

[0059] Compared with the prior art, the present invention has the following advantages:

[0060] 1. An optimization method for ship traffic organization based on an improved multi-objective imperial competitive algorithm provided by the present invention extends the application field of the traditional imperial competitive algorithm to the ship traffic organization optimization problem for the first time by improvement. It can solve the problems of easy premature convergence and easy entrapment in local optimum when using the imperial competitive algorithm alone to solve the ship traffic scheduling scheme, and can stably obtain a better ship scheduling scheme, having the positive effect of improving the operation efficiency of ships entering and leaving the port. In terms of algorithm improvement, according to the problem characteristics and aiming at multi-objective discrete optimization, a multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships is constructed to calculate the cost value of the ship scheduling scheme for each country. To prevent the optimization from falling into local optimum, an adaptive ship safety time headway revolution operator is designed in the revolution process, variable neighborhood search is introduced in the revolution operation, and it is combined with the selection method of revolutionary objects with self-adaptability to enhance the search ability of the algorithm; after the imperial competition operation, a fission operation is added and a multi-objective discrete threshold division strategy is designed to alleviate the situation of premature convergence of the algorithm.

[0061] 2. An optimization method for ship traffic organization based on an improved multi-objective imperial competitive algorithm provided by the present invention aims at the actual problems in the port production scheduling process. Under the conditions of satisfying the constraints of ship traffic organization optimization problems in one-way channels such as flow conversion, safety time interval, berth conflict resolution, and tide riding for large ships entering and leaving the port, taking into account the interests of the port side and the ship side, with the goal of minimizing the total scheduling time of ships entering and leaving the port and the total waiting time of ships in the port, the improved multi-objective imperial competitive algorithm based on the adaptive evolution strategy of the revolutionary fission operator can stably obtain a better ship scheduling scheme, having the positive effect of improving the operation efficiency of ships entering and leaving the port, providing a new method for solving the ship traffic organization optimization problem, and providing auxiliary decision-making for the ship scheduling of the port. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0063] Figure 1 It is a flowchart of the improved multi-objective imperial competitive algorithm based on the adaptive evolution strategy of the revolutionary fission operator of the present invention.

[0064] Figure 2 It is a schematic diagram of the assimilation operation in the present invention.

[0065] Figure 3Schematic diagram of the neighborhood structure for the revolutionary operation in the present invention, where (a) is the schematic diagram of the operation of neighborhood structure 1 and (b) is the schematic diagram of the operation of neighborhood structure 2.

[0066] Figure 4 Schematic diagram of the one-way channel in the comprehensive port area of Huanghua Port in the embodiment of the present invention. Detailed implementation manners

[0067] In order to enable those skilled in the art of the present technology to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0068] The traditional Imperialist Competitive Algorithm (ICA) mainly solves single-objective continuous optimization problems, and there are problems such as easy premature convergence and easy to fall into local optimum when solving scheduling problems. The multi-objective ship traffic organization optimization problem of a one-way channel belongs to a discrete optimization problem and an NP-Hard problem. According to the characteristics of the problem, the present invention improves the traditional imperialist competitive algorithm for multi-objective discrete optimization, constructs a multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships, and is used to calculate the cost value of the ship scheduling plan for each country; to prevent the optimization from falling into local optimum, an adaptive ship safety time headway revolutionary operator is designed in the revolutionary process, variable neighborhood search is introduced in the revolutionary operation, and it is combined with the selection method of revolutionary objects with self-adaptability to enhance the search ability of the algorithm; after the imperial competition operation, a fission operation is added and a multi-objective discrete threshold division strategy is designed to alleviate the situation of premature convergence of the algorithm. The method of the present invention can solve the problems of easy premature convergence and easy to fall into local optimum when using the imperialist competitive algorithm alone to solve the ship traffic scheduling plan, and can stably obtain a better ship scheduling plan, which has the positive effect of improving the operation efficiency of ships entering and leaving the port, and provides auxiliary decision-making for the ship scheduling of ports.

[0069] This embodiment provides a ship traffic scheduling method based on an improved multi-objective imperialist competitive algorithm, which specifically includes the following steps:

[0070] Step S1: Obtain the constraint conditions of the multi-objective ship traffic organization optimization problem of a one-way channel such as flow conversion, safety time interval, berth conflict resolution, and tide riding for large ships entering and leaving the port that need to be satisfied during the optimization process, determine the objectives to be optimized, and establish corresponding multi-objective optimization functions, where:

[0071] The constraints for optimizing the ship traffic organization in a one-way waterway include:

[0072] The tidal constraint for large ships entering and leaving the port is:

[0073]

[0074] The constraint on the start time of ships entering / leaving the port is:

[0075]

[0076] The flow conversion constraint is:

[0077] (T r,i -T r,j -M×q i,j -t β,i -t2)×(D i -D j ) 2 ≥0

[0078] The constraint on the time for ships to pass through the waterway is:

[0079]

[0080] The safety time interval constraint is:

[0081] (T r,i -T r,j +M×q i,j -t1-λ i,j t3)×(1-(D i -D j ) 2 )≥0

[0082] (T le,i -T le,j +M×q i,j -t1-λ i,j t3)×(1-(D i -D j ) 2 )≥0

[0083] The berth conflict resolution constraint is:

[0084] 1 - B i,m +(1 - D i )×M≥0t = T r,i

[0085] Among them, S is the set of ships S = {1, 2,..., |S|}, i, j ∈ S, i < j; T r,i and T le,iThey are the start time and end time for ship \(i\) to enter / leave the port respectively; \(t_1\), \(t_2\) and \(t_3\) are the safety time intervals for ships moving in the same direction, the safety time intervals for ships moving in opposite directions and the additional safety time intervals required due to berth order respectively; \(t\) β,i and \(d\) β,i are the time for ship \(i\) to reach the berth from the channel entrance and the distance from the channel entrance to the berth theoretically respectively; \(v\) i is the average speed of ship \(i\) theoretically; \(T\) i and are the application time for ship \(i\) to enter / leave the port and the adjusted application time for ship \(i\) to enter / leave the port respectively; \(D\) i = 1 indicates that ship \(i\) is an inbound ship, otherwise \(D\) i = 0; \(q\) i,j = 1 indicates that ship \(j\) enters / leaves the port later than ship \(i\), otherwise \(q\) i,j = 0; \(\lambda\) i,j = 1 indicates that when ship \(i\) enters the port earlier than ship \(j\), it docks at a berth farther out, otherwise \(\lambda\) i,j = 0; \(B\) i,m = 1 indicates that the berth \(m\) assigned to ship \(i\) is occupied, otherwise \(B\) i,m = 0; \(T\) tr,i and \(T\) td,i are the start time and end time for ship \(i\) to enter / leave the port at the rising tide respectively; \(M\) is the maximum value.

[0086] With the minimum total waiting time of ships in the port and the total scheduling time of ships entering and leaving the port as the optimization objectives, the multi-objective optimization function is expressed as:

[0087]

[0088]

[0089] where \(S\) is the set of ships \(S = \{1, 2, \cdots, |S|\}\), \(i, j\in S\), \(i < j\); \(T\) r,i and \(T\) le,i are the start time and end time for ship \(i\) to enter / leave the port respectively; \(T\) i is the application time for ship \(i\) to enter / leave the port.

[0090] Step S2: Solve the ship scheduling plan by using an improved multi-objective imperial competitive algorithm based on the adaptive evolutionary strategy of the revolutionary fission operator. According to the problem characteristics, for multi-objective discrete optimization, construct a multi-objective ship sequence cost function based on the total ship waiting time and total scheduling time to calculate the cost value of the ship scheduling plan for each country; to prevent the optimization from falling into a local optimum, design an adaptive ship safety time interval revolutionary operator in the revolutionary process, introduce variable neighborhood search in the revolutionary operation, and combine it with the selection method of revolutionary objects with self-adaptability to enhance the search ability of the algorithm; after the imperial competition operation, add a fission operation and design a multi-objective discrete threshold division strategy to alleviate the situation of premature convergence of the algorithm.

[0091] Specifically, the algorithm flowchart is as Figure 1 shown, and the specific implementation process is as follows:

[0092] Step S21: Parameter initialization: Set the number of countries n of the algorithm pop , the number of colonial countries n imp , the maximum number of iterations i max , the proportion ω of the colony in calculating the power of the entire empire, and the threshold K in the fission operation;

[0093] Step S22: Construct an initial empire according to the designed multi-objective ship sequence cost function based on the total ship waiting time and total scheduling time, and determine the encoding and decoding methods of national individuals;

[0094] Specifically, step S22 specifically includes the following steps:

[0095] Step S221: Randomly generate n pop initial countries, and calculate the objective function values of each country, that is, the total ship waiting time in port and the total ship scheduling time for entering and leaving the port.

[0096] Step S222: Perform non-dominated sorting on the objective values corresponding to national individuals, and calculate the corresponding non-dominated sorting order value R co,ra and crowding distance D co,cr .

[0097] Step S223: According to the problem characteristics, for multi-objective discrete optimization, the constructed multi-objective ship sequence cost function based on the total ship waiting time and total scheduling time is shown in formula (3), and calculate the cost value of each country according to the cost function;

[0098]

[0099] Among them, D co,cr represents the non-dominated sorting crowding distance of national individuals; R co,raDenote the non - dominated sorting rank value of a national individual; α and β are algorithm parameters, co represents a country, cr represents the non - dominated sorting crowding distance, and ra represents the non - dominated sorting rank value.

[0100] Step S224: Select the top n countries with better cost values as colonial countries, and determine the number of colonies of each empire according to the proportion of the cost of colonial countries in the total cost in the empire. Randomly distribute the colonies to the empires to generate colonial countries and colonies. imp Specifically, for the encoding and decoding methods of national individuals, considering that the optimization problem of ship traffic organization in one - way channels belongs to a discrete optimization problem, according to the characteristics of the solution, the national individual adopts a permutation encoding method, that is, each national individual encoding is a sequence composed of a group of ships to be scheduled; the decoding process is to convert the national individual into the ship's arrival and departure sequence, and then according to the ship's arrival and departure sequence and the constraints of the ship traffic organization optimization problem in one - way channels such as ship safety time intervals, flow conversion, and berth conflict resolution, arrange the start and end arrival and departure times and the times passing through each key point of the channel for each ship, so as to generate a ship scheduling plan.

[0101] Specifically, for the encoding and decoding methods of national individuals, considering that the optimization problem of ship traffic organization in one - way channels belongs to a discrete optimization problem, according to the characteristics of the solution, the national individual adopts a permutation encoding method, that is, each national individual encoding is a sequence composed of a group of ships to be scheduled; the decoding process is to convert the national individual into the ship's arrival and departure sequence, and then according to the ship's arrival and departure sequence and the constraints of the ship traffic organization optimization problem in one - way channels such as ship safety time intervals, flow conversion, and berth conflict resolution, arrange the start and end arrival and departure times and the times passing through each key point of the channel for each ship, so as to generate a ship scheduling plan.

[0102] Step S23: Perform assimilation operations on the colonies, design an adaptive ship safety time - distance revolution operator to perform revolution operations on the colonies, and simulate unexpected changes in the colonies; after the assimilation and revolution operations, perform colonial country update and inter - empire competition operations. Among them:

[0103] The specific steps of the assimilation operation are as follows:

[0104] Step S231: Generate two random positions and exchange the segments between the two positions.

[0105] Step S232: Step S231 may result in duplicate segments in the same country. Use the partial mapping method to eliminate conflicts.

[0106] Step S233: Retain the exchanged colonies and keep the colonial countries unchanged, that is, do not adopt the exchanged colonial countries. Specifically as Figure 2 shown.

[0107] The revolution operation is specifically to simulate a certain unexpected change through designing an adaptive ship safety time - distance revolution operator to prevent falling into local optimum during the iteration process and realize the colony revolution operation. The adaptive ship safety time - distance revolution operator includes the following steps:

[0108] Step S234: Determine whether the colony is a revolutionary object through a selection method for revolutionary objects with adaptability. To prevent the diversity of feasible solutions from being too high, it is easier to obtain better feasible solutions by selecting some relatively excellent colonies to participate in the revolutionary process in each iteration. Therefore, calculate the non-dominated sorting order value and crowding distance of the national individuals in the empire. In the current iteration, if the colony satisfies that its non-dominated sorting order value in the empire is 1, that is, no other national individuals in the empire can dominate this colony, then go to Step S235; otherwise, no revolutionary operation is performed in this iteration, and go to Step S236.

[0109] Step S235: Conduct variable neighborhood search on the colony selected as the revolutionary object to enhance the search ability of the algorithm. Two neighborhood structures that will not generate illegal solutions are adopted, specifically as follows:

[0110] Neighborhood Structure 1: In the national individual, randomly generate four positions, reverse the order of the corresponding ships at these four positions, and adjust the start and end departure and arrival times of the ships and the times passing through each key point of the waterway according to the constraints of the ship traffic organization optimization problem of one-way waterways such as ship safety time intervals and flow conversion, as Figure 3 shown in (a).

[0111] Neighborhood Structure 2: In the national individual, randomly generate two positions, shuffle the corresponding ship sequence between these two positions, and adjust the start and end departure and arrival times of the ships and the times passing through each key point of the waterway according to the constraints of the ship traffic organization optimization problem of one-way waterways such as ship safety time intervals and flow conversion, as Figure 3 shown in (b).

[0112] The update of the colonial country is specifically as follows:

[0113] Step S236: Conduct fast non-dominated sorting within the empire. If the cost value of the colony is better than that of the corresponding colonial country, then this colony replaces the colonial country to become the new colonial country within this empire; otherwise, no change occurs.

[0114] The inter-empire competition operation is specifically as follows: Calculate the total cost of all empires. The weakest empire needs to select one of its weakest colonies, and the stronger empires can compete for this colony. The stronger the empire, the greater the probability of obtaining this colony; among them, the total cost C of the empire tc,n The calculation formula is as shown in Equation (4), and the total cost of each empire is normalized as shown in Equation (5). The probability P of each empire occupying a weak colony n is calculated as shown in Equation (6):

[0115]

[0116]

[0117]

[0118] Among them, C tc,n is the total imperial cost after standardization, N nc,n is the number of colonies within the empire, C imp is the cost of the colonial country, C sh,μ is the cost of the colony, and sh represents the colony.

[0119] Step S24: Design a multi-objective discrete threshold division strategy to adaptively select fission objects and perform fission operations. Specifically, the fission operation includes:

[0120] Step S241: Determine whether the empire is a fission object. Select fission objects by designing a multi-objective discrete threshold division strategy, and recalculate the non-dominated sorting order values of the individual countries within the empire. In this iteration, if there is a colony that satisfies the condition that the difference in non-dominated sorting order values from the colonial country is less than or equal to the threshold K and the corresponding ship scheduling sequences are different, then the colonial country within this empire is denoted as imp old , go to step S242; otherwise, no fission operation is performed in this iteration, and go to step S25.

[0121] Step S242: Take the colonies that meet the conditions as the colonial countries of the new empire, denoted as imp new , and determine the number of colonies assigned to the empire corresponding to the colonial country according to the cost sizes of imp old and imp new , and randomly assign the remaining colonies to the empire.

[0122] Step S25: Eliminate the empires without colonies. According to the settings of the maximum number of iterations i max of the algorithm and the number of remaining empires finally retained, determine whether the algorithm meets the iteration termination condition. If so, the algorithm terminates, and the ship scheduling plan corresponding to the remaining colonial country individuals is output, which is the ship scheduling plan that makes the total waiting time of ships in port and the total scheduling time of ship arrivals and departures relatively optimal; otherwise, go to step S23.

[0123] Step S3: Perform iterative calculations and output the optimized ship scheduling plan.

[0124] The following is a specific embodiment to further describe and explain the present invention. In the specific embodiment of the present invention, scheduling experiments were carried out based on the ship data of the comprehensive port area of Huanghua Port, as Figure 4The figure shows the schematic diagram of the one-way channel in the comprehensive port area of Huanghua Port. The distance from No.6 anchorage to the starting point of the channel is 1.52 nautical miles, and the distance from No.8 anchorage to the starting point of the channel is 8.87 nautical miles. The length of the channel is 31.75 nautical miles, with a total of 15 berths. To connect each time period, it is necessary to consider the initial state of the ships in the channel and berths within the time range to be studied, such as whether there are ships in the channel. The berth information and busy / idle status are shown in Table 1, where the unit of distance is nmile. The information of the last ship in the previous stage and the 15 ships scheduled in this stage is shown in Table 2. The algorithm parameters are set as follows: n pop = 100, n imp = 10, i man = 300, θ = 0.5, α = 01, β = 0.5, K = 0. The computer used in the experiment: Intel i5-7200CPU, main frequency 2.50GHz, memory 12.00GB.

[0125] Table 1 Initial busy / idle status of berths

[0126]

[0127] Table 2 Information of scheduled ships

[0128]

[0129] Table 3 Optimization scheme for ship traffic organization

[0130]

[0131] Instantiate the multi-objective optimization model for ship traffic organization based on the one-way channel, and obtain the optimal scheduling scheme for 15 ships as shown in Table 3, indicating that the method of the present invention can coordinate port resources, reasonably arrange the order and time of ships entering and leaving the port. The total waiting time of the ships corresponding to the ship scheduling scheme of this individual in the port is 61.42 hours; the total scheduling time for ships to enter and leave the port is 9.12 hours. By comparing FCFS (First Come First Served), NSGA-II (Non-dominated Sorting Genetic Algorithm), and DE (Differential Evolution), the optimization model described in the present invention uses the above method to solve 10 times respectively in the case of 10 ships, and the objective values of the obtained schemes are shown in Table 4 respectively. The results show that the method provided by the present invention makes the algorithm not easily fall into local optimum, has good optimization ability, can obtain a better ship scheduling scheme, and can shorten the total scheduling time for ships to enter and leave the port and the total waiting time of ships in the port while ensuring navigation safety, which has a positive effect of improving the operation efficiency of ships entering and leaving the port and provides auxiliary decision-making for ship scheduling in the port.

[0132] Table 4 Comparison of Results of Different Algorithms for Scheduling 10 Ships

[0133]

[0134]

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An optimization method for ship traffic organization based on an improved multi-objective imperial competitive algorithm, characterized in that, Including the following steps: Step S1: Obtain the constraints of the multi-objective ship traffic organization optimization problem for a one-way waterway, including traffic conversion, safety time interval, berth conflict resolution, and tide riding for large ships entering and leaving the port, during the optimization process, and determine the objectives to be optimized, and establish the corresponding multi-objective optimization function; Step S2: Use an improved multi-objective imperial competition algorithm based on the adaptive evolutionary strategy of the revolutionary fission operator to solve the ship scheduling plan, including: According to the problem characteristics, for multi-objective discrete optimization, construct a multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships, which is used to calculate the cost value of the ship scheduling plan for each country. Design an adaptive ship safety time interval revolutionary operator during the revolutionary process, introduce variable neighborhood search in the revolutionary operation, and combine it with the selection method of the revolutionary object with self-adaptability to enhance the search ability of the algorithm. After the imperial competition operation, add a fission operation and design a multi-objective discrete threshold division strategy to alleviate the situation of premature convergence of the algorithm; Step S2 specifically includes the following steps: Step S21: Parameter initialization, including setting the number of countries in the algorithm , the number of colonial countries , the maximum number of iterations , the proportion of colonies in calculating the power of the entire empire , the threshold in the fission operation K , Step S22: Construct an initial empire according to the designed multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships, and determine the encoding and decoding methods of national individual codes; Step S23: Perform assimilation operations on the colonies, design an adaptive ship safety time interval revolutionary operator to perform revolutionary operations on the colonies, simulate unexpected changes in the colonies. After the assimilation and revolutionary operations, perform colonial country updates and imperial competition operations; Step S24: Design a multi-objective discrete threshold division strategy to adaptively select fission objects and perform fission operations, and the fission operations include: Step S241: Determine whether the empire is a fission object. Select fission objects by designing a multi-objective discrete threshold division strategy. Recalculate the non-dominated sorting order values of the national individuals within the empire. In the current iteration, if there is a colony whose order value difference from the colonial country is less than or equal to the threshold K and the corresponding ship scheduling sequences are different, then the colonial country within the empire is recorded as Go to step S242; otherwise, no fission operation is performed in this iteration, and go to step S25 Step S242: Use the colonies that meet the conditions as the colonial countries of the new empire, denoted as , and determine the number of colonies assigned to the empire corresponding to the colonial country according to the cost sizes of and . Then randomly assign the remaining colonies to the empires. Step S25: Eliminate the empires without colonies. According to the settings of the maximum number of algorithm iterations and the number of remaining empires finally retained in the parameters, determine whether the algorithm meets the iteration termination condition. If so, terminate the algorithm and output the ship scheduling plan corresponding to the remaining colonial country individuals, which is the ship scheduling plan that makes the total waiting time of ships in the port and the total scheduling time of ships entering and leaving the port relatively optimal; otherwise, go to step S23; And the setting of the number of remaining empires finally retained, determine whether the algorithm meets the iteration termination condition. If so, terminate the algorithm and output the ship scheduling plan corresponding to the remaining colonial country individuals, which is the ship scheduling plan that makes the total waiting time of ships in the port and the total scheduling time of ships entering and leaving the port relatively optimal; otherwise, go to step S23; Step S3: Perform iterative calculations and output the optimized ship scheduling plan.

2. The optimization method for ship traffic organization based on an improved multi-objective imperialist competitive algorithm according to claim 1, characterized in that Step S22 includes the following steps: Step S221: Randomly generate initial countries, and calculate the objective function values corresponding to each country individual, that is, the total waiting time of ships in port and the total scheduling time of ships entering and leaving the port; Step S222: Perform non-dominated sorting on the objective values corresponding to the national individuals, and calculate the corresponding non-dominated sorting order values and crowding distance ; Step S223: According to the problem characteristics, for multi-objective discrete optimization, the constructed multi-objective ship sequence cost function based on the total waiting time and total scheduling time of ships is shown in formula (3), and calculate the cost value of each country according to the cost function; (3) Among them, represents the non-dominated sorting crowding distance of the national individual; represents the non-dominated sorting ordinal value of the national individual; , is the algorithm parameter, represents the country, represents the non-dominated sorting crowding distance, represents the non-dominated sorting ordinal value; Step S224: Select the top countries with relatively better cost values as colonial countries, and determine the number of colonies for each empire according to the proportion of the cost of colonial countries in the total cost within the empire. Randomly distribute the colonies to the empires to generate colonial countries and colonies.

3. A method for optimizing ship traffic organization based on an improved multi-objective imperial competitive algorithm according to claim 1, characterized in that In step S22, the national individual code adopts the permutation coding method, that is, each national individual code is a sequence composed of a group of ships to be scheduled; the decoding process is to convert the national individual into the ship's arrival and departure sequence, and then arrange the start and end arrival and departure times and the times passing through each key point of the waterway for each ship according to the ship's arrival and departure sequence and the ship safety time interval constraint, traffic conversion constraint, and berth conflict resolution constraint, so as to generate a ship scheduling plan.

4. A ship traffic organization optimization method based on an improved multi-objective imperialist competitive algorithm according to claim 1, characterized in that, The assimilation operation in step S23 includes the following steps: Step S231: Generate two random positions and exchange the segments between the two positions; Step S232: Step S231 will result in duplicate segments in the same country, and use the partial mapping method to eliminate conflicts; Step S233: Retain the exchanged colonies and keep the colonial countries unchanged, that is, do not adopt the exchanged colonial countries.

5. An optimization method for ship traffic organization based on an improved multi-objective imperialist competitive algorithm according to claim 4, characterized in that, The revolutionary operation described in step S23 is specifically to simulate a certain unexpected change by designing an adaptive ship safety time - distance revolutionary operator to prevent falling into local optimum during the iterative process and achieve the colonial revolutionary operation. The adaptive ship safety time - distance revolutionary operator includes the following steps: Step S234: By means of a selection method for revolutionary objects with self - adaptability, determine whether the colony is a revolutionary object, calculate the non - dominated sorting order value and crowding distance of the national individuals within the empire. In the current iteration, if the colony satisfies the condition that its non - dominated sorting order value within the empire is 1, that is, no other national individuals within the empire can dominate this colony, then go to step S235; otherwise, no revolutionary operation is performed in this iteration and go to step S236; Step S235: Conduct variable neighborhood search on the colony selected as the revolutionary object, including using two neighborhood structures that will not generate illegal solutions, specifically including: Neighborhood structure 1: In the national individual, randomly generate four positions, reverse the order of the corresponding ships at these four positions, and according to the constraints of the ship traffic organization optimization problem of one - way waterways such as ship safety time interval and flow conversion, adjust the start and end times of ship entry / exit and the times passing through each key point of the waterway accordingly. Neighborhood structure 2: In the national individual, randomly generate two positions, scramble the corresponding ship sequence between these two positions, and according to the constraints of the ship traffic organization optimization problem of one - way waterways such as ship safety time interval and flow conversion, adjust the start and end times of ship entry / exit and the times passing through each key point of the waterway. Step S236: Conduct fast non - dominated sorting within the empire. If the cost value of the colony is better than that of the corresponding colonial country, then this colony replaces the colonial country to become the new colonial country within the empire; otherwise, no change occurs.

6. The optimization method for ship traffic organization based on an improved multi-objective imperialist competitive algorithm according to claim 1, characterized in that Step S1 includes establishing a multi - objective optimization function with the minimum total waiting time of ships in port and the total scheduling time of ship entry / exit as the optimization objectives. The multi - objective optimization function is expressed as: (1) (2) Among them, is a set of ships ; and are respectively the start time and end time of a ship entering / leaving the port; is the application time of a ship entering / leaving the port.

7. An optimization method for ship traffic organization based on an improved multi-objective imperialist competitive algorithm according to claim 1, characterized in that The constraint conditions for the multi - objective ship traffic organization optimization problem of one - way waterways in step S1 include: The tidal - riding constraint for large ships entering / leaving the port is: The constraint for the start time of ship entry / exit is: The flow conversion constraint is: The constraint for the time of ships passing through the waterway is: The safety time interval constraint is: The berth conflict resolution constraint is: Among them, is the set of ships ; and are respectively the start time and end time for a ship to enter / leave the port; , and are respectively the safety time interval for ships going in the same direction, the safety time interval for ships going in opposite directions, and the additional safety time interval required due to the berth order; and are respectively the time for a ship to reach the berth from the entrance of the waterway in theory and the distance from the entrance of the waterway to the berth for a ship in theory; is the average speed of a ship in theory; and are respectively the application time for a ship to enter / leave the port and the adjusted application time for entering / leaving the port; indicates that the ship is an inbound ship, otherwise it is ; indicates that the ship enters / leaves the port later than the ship , otherwise ; indicates that when the ship enters the port earlier than the ship , it docks at a more outer berth, otherwise ; indicates that the berth assigned to the ship is occupied, otherwise ; and are respectively the start time and end time for a ship to enter / leave the port with the rising tide; is the maximum value.

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