Method for optimizing hybrid scheduling between sea ships and river ships for river-sea combined transportation of dry bulk cargos

Abstract

The invention relates to a dry bulk river-sea combined transportation seagoing ship and river-ship hybrid scheduling optimization method, which comprises the following steps: S1, constructing a river-sea combined transportation hybrid scheduling model, and defining and setting related parameters and variables; s2, constructing a target function by taking the minimum total time of ships at the port, the minimum total time of all ships waiting on the anchor ground and the minimum total operation cost of carriers as targets, and constructing a berthing position constraint, an equipment operation constraint, a river-sea combined transportation connection constraint and a time connection constraint as constraint conditions; and S3, solving the river-sea combined transportation hybrid scheduling model by adopting a heuristic genetic algorithm to obtain a scheduling scheme for scheduling. Compared with the prior art, the method has the advantages that through introduction of the anchoring ground and the storage yard, a multi-main-body collaborative scheduling optimization model among the seagoing ship, the anchoring ground, the storage yard and the river ship is constructed, an optimal collaborative scheduling mode is formed around the operating time and cost benefit elements, and cost reduction and efficiency improvement of port operation are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of transportation, in particular to a mixed scheduling optimization method for sea ships and river ships in dry bulk river-sea intermodal transport. BACKGROUND

[0002] The common modes of dry bulk intermodal transport currently include public water intermodal transport, rail-water intermodal transport, and river-sea intermodal transport. Among them, river-sea intermodal transport takes full advantage of the advantages of inland water transport, realizes seamless connection in loading and unloading and transfer links, and significantly reduces transfer cost and transport time, thus becoming a more efficient transport mode. However, in actual river-sea intermodal transport operations, the time interval of river ships arriving at the port often has great instability, and in addition to the limited nature of port resources, it is difficult for the direct barge scheduling mode of simply relying on loading and unloading of sea ships to the ships to cope with complex dynamic changes. For example, when the arrival time of river ships fluctuates greatly or the port resources are tight, it may lead to port congestion, resource waste, and prolonged waiting time of ships, etc. Therefore, under the condition of unstable arrival time of river ships, how to further optimize the allocation of port resources and improve the overall transport efficiency has become a difficult problem.

[0003] As an important area for ships to wait for berthing, anchorage plays a buffering and adjusting role in the actual scenario of dry bulk river-sea intermodal transport to realize direct barge scheduling. When the arrival time of multiple matching river ships cannot form seamless connection with sea ships, anchorage can provide temporary parking space for part of the river ships, reducing the high berthing cost of sea ships in the port. At the same time, the yard as a temporary storage area for dry bulk cargo can effectively alleviate the loading and unloading operation pressure when the matching degree of sea ships and river ships is poor, and improve the utilization rate of port resources. By introducing the coordinated optimization of anchorage and yard, not only can the uncertainty of the time interval of river ships arriving at the port be better coped with, but also the flexibility and efficiency of port operations can be further improved.

[0004] The introduction of anchorage and yard also increases the cost of anchorage and yard. How to realize the cooperation of time, cost, etc. among sea ships, anchorage, yard, and river ships has become a problem that needs to be optimized in the mixed scheduling of sea ships and river ships in river-sea intermodal transport. SUMMARY

[0005] The purpose of the present application is to provide a mixed scheduling optimization method for sea ships and river ships in dry bulk river-sea intermodal transport to solve the defects of the prior art.

[0006] The purpose of the present application can be realized by the following technical solutions:

[0007] A mixed scheduling optimization method for sea ships and river ships in dry bulk river-sea intermodal transport, comprising:

[0008] Step S1: constructing a river-sea intermodal mixed scheduling model and defining and setting relevant parameters and variables;

[0009] Step S2: constructing a target function with the least total time of the ships in the port, the least total time of all ships waiting at anchorages and the least total cost of the carrier operation as the target, and constructing berthing position constraints, equipment operation constraints, river-sea intermodal transportation connection constraints and time connection constraints as the constraint conditions;

[0010] Step S3: solving the river-sea intermodal transportation mixed scheduling model by using a heuristic genetic algorithm to obtain a scheduling scheme.

[0011] The step S1 comprises:

[0012] Step S1-1: assuming that the river-sea intermodal transportation direct barge scheduling model contains n evaluation indexes, and there are m operation modes to be evaluated, an original evaluation matrix R is established as R=[r ij ] m×n , wherein r ij is the evaluation value of the i-th evaluation index of the j-th operation mode;

[0013] Step S1-2: dividing the evaluation indexes into positive indexes and negative indexes, and the standardization processing of the positive indexes is as follows:

[0014]

[0015] The standardization processing of the negative indexes is as follows:

[0016]

[0017] , wherein s ij is the standardized evaluation index value, min(r j ) is the minimum index value of the j-th operation mode, and max(r j ) is the maximum index value of the j-th operation mode;

[0018] Step S1-3: determining the objective weight of each index based on the information amount contained by each index:

[0019]

[0020] , wherein ω j is the objective weight of the j-th index, V j is the information amount contained by the j-th index, σ j is the standard deviation of the j-th index, and p ij is the correlation coefficient between the i-th index and the j-th index;

[0021] Step S1-4: constructing a weighted standardization matrix, wherein the elements in the weighted standardization matrix are the products of the standardized evaluation index values and the objective weights of the corresponding indexes;

[0022] Step S1-5: Determine the optimal ideal solution and the worst ideal solution of the evaluation index as follows:

[0023]

[0024] Wherein: A j + is the optimal ideal solution of the evaluation index, A j - is the worst ideal solution of the evaluation index, is the maximum or minimum value of the first index in the optimal ideal solution A j + , is the maximum or minimum value of the second index in the optimal ideal solution A j + , is the maximum or minimum value of the nth index in the optimal ideal solution A j + , is the maximum or minimum value of the first index in the worst ideal solution A j - , is the maximum or minimum value of the second index in the worst ideal solution A j - , is the maximum or minimum value of the nth index in the worst ideal solution A j - ;

[0025] When the evaluation index is a positive index, the optimal ideal solution and the worst ideal solution of the evaluation index are as follows:

[0026]

[0027] When the evaluation index is a negative index, the optimal ideal solution and the worst ideal solution of the evaluation index are as follows:

[0028]

[0029] Wherein: e ij is an element in the weighted standardized matrix;

[0030] Step S1-6: Calculate the Euclidean distance of each evaluation operation mode to the optimal ideal solution and the worst ideal solution as follows:

[0031]

[0032] Wherein: is the Euclidean distance of the evaluation operation mode i to the optimal ideal solution, is the Euclidean distance of the evaluation operation mode i to the worst ideal solution.

[0033] Step S1-7: Calculate the relative closeness:

[0034]

[0035] Wherein: Z i is the relative closeness of each evaluation index under the operation mode i.

[0036] The total time of all ships in port is:

[0037]

[0038] Wherein: f1 is the total time of all ships in port, qe i is the start time of sea ship i to leave the port, q i is the arrival time of sea ship i, ke j is the start time of river ship j to leave the port, k j is the arrival time of river ship j, I is the set of sea ships, and J is the set of river ships.

[0039] The total time of all ships waiting in anchorage is:

[0040]

[0041] Wherein: f2 is the total time of all ships waiting in anchorage, qs i is the start time of sea ship i to berth, T1 is the time of sea ship from anchorage to berth, ks j is the start time of river ship j to berth, T2 is the time of river ship from anchorage to berth.

[0042] The total cost of the carrier operation is:

[0043] f3 = C1 + C2 + C3 + C4 + C5 + C6 + C7

[0044] Wherein: f3 is the total cost of the carrier operation, C1 is the sum of the ship parking fee and the environmental damage cost caused by oil pollution when the ship stays in the port, C2 is the anchorage waiting cost when the ship stays in the port, C3 is the ship unloader cost, C4 is the use cost of the stacker-reclaimer, C5 is the horizontal transportation cost of the belt conveyor, C6 is the switching cost of the loading and unloading equipment, and C7 is the stacking cost due to the ground transfer of dry bulk cargo.

[0045] The objective function is:

[0046] min f = λ1f1 + λ2f2 + λ3f3

[0047] Wherein: λ1 is the first weight coefficient, λ2 is the second weight coefficient, and λ3 is the third weight coefficient.

[0048] The step S3 comprises:

[0049] Step S3-1: uniformly coding according to the arrival time sequence of the river-sea combined transport ships;

[0050] Step S3-2: decoding the berthing position of the ship and the ship's loading and unloading machine assignment first, and then judging whether there is a direct barge condition at the moment, if yes, adopting the direct barge scheduling mode, if not, triggering the start of the yard transfer mode, and generating the berthing time decoding and anchorage waiting time decoding of the ship in the direct barge scheduling mode or the yard transfer mode;

[0051] Step S3-3: constructing an initial decoding sequence with scheduling practical significance based on the expected arrival time of the river-sea combined transport ship;

[0052] Step S3-4: selecting an adaptive function;

[0053] Step S3-5: performing genetic operator operation to obtain a scheduling scheme, and scheduling based on the scheduling scheme, wherein the genetic operator specifically includes a selection operator, a crossover operator and a mutation operator.

[0054] The process of decoding the berthing position of the ship and the ship's loading and unloading machine assignment in the step S3-2 comprises:

[0055] Step S3-2-1-1: following the principle of the shortest relative berthing distance, after determining the berth i of the sea ship, traversing the candidate berth j of the river ship, and selecting the berth combination that satisfies mind ij , wherein mind ij is the minimum value of the relative distance between the sea ship i and the river ship j berthing;

[0056] Step S3-2-1-2: following the principle of as many allocations as possible, when the berth loading and unloading machine is in an idle state, the maximum number of idle loading and unloading equipment is allocated to each ship without exceeding the upper limit constraint of single-ship equipment, thereby maximizing the equipment utilization rate;

[0057] When the scheduling mode selects the direct barge scheduling mode, the process of decoding the berthing time of the ship and the anchorage waiting time in the step S3-2 comprises:

[0058] Step S3-2-1: when the berth is available and the sea ship is ready, the berthing time is determined by the arrival time of the sea ship and the river ship,

[0059] Step S3-2-2: when the berth is not available, i.e. the last river ship is being served, the berthing time is determined by the departure time of the last river ship and the arrival time of the river ship;

[0060] When the scheduling mode is selected as the yard transshipment scheduling mode, in the process of decoding the berthing time of the ship and the anchorage waiting time in step S3-2: the berthing time of the river ship is determined by the arrival time of the river ship, and for the anchorage waiting time of all ships, if the berthing time of the ship is later than the arrival time, the anchorage waiting time is calculated according to the berthing time.

[0061] The initial solution generation process in step S3-3 includes:

[0062] Step S3-3-1: reading the expected arrival time of all ships;

[0063] Step S3-3-2: sorting the ship set in ascending order according to the arrival time;

[0064] Step S3-3-3: according to the sorting result, recording the ship number and generating the initial individual;

[0065] Step S3-3-4: taking multiple sequences formed based on the sorting disturbance as the initial population to enhance the diversity of the algorithm.

[0066] The selection operator adopts the tournament selection method, randomly samples s individuals from the population, and selects the optimal individual to enter the next generation.

[0067] The execution process of the crossover operator includes:

[0068] Step S3-5-1-1: selecting two different chromosome individuals from the population after tournament selection, denoted as parent A and parent B;

[0069] Step S3-5-1-2: randomly selecting two crossover points pos1 and pos2 in parent A, and cutting the gene segment in the interval [pos1, pos2] in parent A;

[0070] Step S3-5-1-3: copying the interval gene segment of parent A directly to the same position of the offspring, preserving its local timing characteristics; the remaining genes are filled in the original order in parent B, skipping the ship numbers already existing in the offspring, to ensure that the chromosome is a legal arrangement;

[0071] Step S3-5-1-4: verifying whether the offspring satisfies the ship uniqueness constraint, and if a conflict is generated due to the crossover, starting the repair mechanism.

[0072] The execution process of the mutation operator includes:

[0073] Step S3-5-2-1: randomly selecting a chromosome individual from the population;

[0074] Step S3-5-2-2: randomly selecting two different positions in the chromosome sequence;

[0075] Step S3-5-2-3: completely reverse the gene order between the two positions to generate a new individual.

[0076] The step S3 further comprises:

[0077] For berth space-time conflict, anchorage buffer time deficiency, and stack capacity overrun, and hierarchical repair is carried out, specifically including:

[0078] Berth conflict repair: the time axis is adjusted by α as the moving step length, and the ship berthing time sequence is adjusted to preferentially guarantee the space-time continuity of direct barge operation;

[0079] Anchorage buffer repair: when the river-ship connection time window violates the constraint, a redistribution strategy is adopted to recalculate the minimum waiting time anchorage scheduling scheme;

[0080] Stack capacity repair: for dry bulk cargo exceeding the storage limit, a near neighbor diffusion strategy is implemented to migrate the overflow cargo to the adjacent stack area and update the operation time sequence.

[0081] Compared with the prior art, the present application has the following beneficial effects: the present application introduces anchorage and stack for river-sea intermodal transport scheduling in the direct barge scheduling mode to realize the buffering effect of river-sea intermodal transport scheduling, constructs a multi-objective river-sea intermodal transport mixed scheduling collaborative optimization model with the minimum total time of all ships in the port, the minimum anchorage waiting time, and the minimum total operating cost of the carrier, and designs a genetic algorithm based on heuristic rules to implement model solving; by using the algorithm to analyze and solve the actual data of a certain port, the river-sea intermodal transport operation plan scheduling scheme, operation time and operating cost in the scheduling period are obtained, and seamless and effective connection of sea ship unloading and river ship loading is realized. In particular, the present application introduces anchorage and stack, and forms an optimal collaborative scheduling mode between sea ships, anchorage, stack and river ships in terms of operation time and cost, which provides new technical support for existing river-sea intermodal transport. BRIEF DESCRIPTION OF DRAWINGS

[0082] Figure 1 It is a dry bulk river-sea intermodal transport mixed scheduling scenario of the present application;

[0083] Figure 2 It is a "sea ship-river ship" mixed scheduling operation time connection diagram of the present application;

[0084] Figure 3 It is a berth allocation two-dimensional space-time diagram of the present application;

[0085] Figure 4 It is an improved order crossover schematic diagram of the present application;

[0086] Figure 5 It is a reverse mutation schematic diagram of the present application;

[0087] Figure 6 This is a flowchart of the heuristic genetic algorithm solution for step S3 of this application;

[0088] Figure 7 This is an iterative convergence graph of the algorithm in the embodiments of this application;

[0089] Figure 8 This is a two-dimensional coordinate diagram of the location-time of the berth allocation for seagoing vessels in the embodiments of this application;

[0090] Figure 9 This is a two-dimensional coordinate diagram of the location-time of the riverboat berth allocation in the embodiments of this application;

[0091] Figure 10 This is a flowchart illustrating the main steps of the method described in this application. Detailed Implementation

[0092] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0093] The hybrid scheduling mode proposed in this application is a more comprehensive optimization method that incorporates yard and anchorage factors into the direct transshipment scheduling mode. The direct transshipment scheduling mode refers to the port's scheduling of terminal resources based on the sea-ship / river-ship matching plan from the dry bulk cargo river-sea intermodal transport information platform. This involves allocating berths and unloading machine resources to each sea-ship and berths and loading machine resources to the river-ships in the matching plan. When a sea-ship arrives at the terminal and berths, its matched river-ship arrives at the port. At this point, the unloading machine unloads the dry bulk cargo onto a conveyor belt and directly transports it to the corresponding river-ship berth for loading, thus realizing direct transshipment operations between sea-ships and river-ships.

[0094] In bulk cargo ports, seagoing vessels are generally large, ranging from 100,000 to 200,000 tons. River vessels, on the other hand, are typically 3,000, 5,000, or 10,000 tons. Therefore, in dry bulk river-sea intermodal transport, one seagoing vessel often needs to be matched with multiple river vessels. Bulk cargo ports have limited berth resources, and due to limitations in bulk cargo loading and unloading efficiency and vessel tonnage, in many ports that primarily serve bulk cargo vessels, seagoing vessels do not enter or leave the port frequently and generally arrive on time within the planned period. Unlike the more organized, scheduled services of container river vessels, dry bulk river vessels are often numerous and their arrival times are unpredictable.

[0095] like Figure 1 The diagram shown illustrates a scenario for the hybrid river-sea intermodal transport scheduling of dry bulk cargo, as described in this application. Its core principle is to resolve the spatiotemporal conflicts arising from the dynamic matching of seagoing and river vessels by utilizing the transshipment function of the storage yard and the buffer function of the anchorage. The specific business modules of the river-sea intermodal transport scheduling mode mainly include:

[0096] ①Sea vessel unloading operation: after the sea vessel berths, the cargo is unloaded to the belt conveyor system through the ship unloader.

[0097] ②Cargo transfer path selection: the first is the direct barge mode, that is, the cargo is directly transferred to the matching river vessel berth through the belt conveyor for loading; the second is the yard transfer scheduling mode, that is, if the matching river vessel does not arrive at the port or the direct barge operation capacity is insufficient, the cargo is temporarily stored in the yard through the belt conveyor, and then is reloaded through the stacker-reclaimer when the river vessel arrives at the port.

[0098] ③Anchorage scheduling: the river vessels that are not matched in time need to wait in the anchorage until the berth or yard resources are released, and the waiting time is constrained by the anchorage capacity and priority rules.

[0099] ④River vessel loading operation: after the river vessel berths, the loading is completed through the yard reclaimer or the direct barge operation mode, and then the river vessel departs.

[0100] In the mixed mode, the yard serves as a buffer pool to balance the operation rhythm of the sea vessels and the river vessels, and the anchorage serves as a temporary berth to relieve the pressure of the dynamic arrival of the river vessels, but at the same time, the problems of storage cost, anchorage waiting cost and multi-link resource conflict are introduced.

[0101] As shown in Figure 2 , the matching river vessel 1 arrives at the port earlier than the corresponding sea vessel, and the arrival time interval of the river vessel 2 and the river vessel 3 is too long to form the river-sea combined transport direct barge mode, so in order to reduce the operation cost of the river-sea combined transport, the direct barge scheduling and the yard transfer scheduling are combined, so that the sea vessel can be in the unloading state after berthing, that is, when there is no river vessel in the port, the sea vessel unloads the cargo of the subsequent arriving vessels to the yard for storage. Therefore, the arrival time and the combined transport volume of all sea vessels and river vessels are considered for collaborative optimization to obtain a dry bulk river-sea combined transport mixed scheduling optimization scheme, so as to reduce the cost and increase the efficiency.

[0102] As shown in Figure 3 , the model of the berth can be represented by a two-dimensional form of coordinate axis, in which the X axis represents the length of the front shore of the wharf, and the Y axis represents the time of the ship in the port, so as to construct a coordinate graph, in which there are three ships, namely ship 1, ship 2 and ship 3, and each ship is represented by a rectangle, in the coordinate axis, t1 is the berthing time of ship 1, t2 is the departure time of ship 1, and (p1, p2) is the position range of ship 1 berthing at the front shore of the wharf. Figure 3 In the model, the midpoint of the horizontal distance of the ship is used to define the berthing position of the ship on the front shore of the wharf, that is, the berthing position coordinate of ship 1 is Similarly, the berthing position coordinates of ship 2 and ship 3 can be obtained.

[0103] A mixed scheduling optimization method between a river-sea combined transport sea ship and a river ship is provided, as shown in the method comprises the following steps: Figure 10

[0104] A mixed scheduling optimization method between a river-sea combined transport sea ship and a river ship, comprising:

[0105] Step S1: based on CRITIC-TOPSIS method to construct river-sea combined transport mixed scheduling model, and the definition and setting of related parameters and variables;

[0106] The CRITIC-TOPSIS method is a method combining CRITIC method and TOPSIS, comprising:

[0107] Step S1-1: assuming that the river-sea combined transport direct barge scheduling model contains n evaluation indexes, and there are m operation modes to be evaluated, the original evaluation matrix is established as R=[r ij ] m×n , wherein r ij is the evaluation value of the i-th evaluation index of the j-th operation mode;

[0108] Step S1-2: the evaluation indexes are divided into positive indexes and negative indexes, and the standardization processing of the positive indexes is:

[0109]

[0110] The standardization processing of the negative indexes is:

[0111]

[0112] Wherein: s ij is the standardized evaluation index value, min(r j ) is the minimum index value of the j-th operation mode, and max(r j ) is the maximum index value of the j-th operation mode;

[0113] Step S1-3: determine the objective weight of each index based on the information amount contained in each index:

[0114]

[0115] Wherein: ω j is the objective weight of the j-th index, V j is the information amount contained in the j-th index, σ j is the standard deviation of the j-th index, and p ij is the correlation coefficient between the i-th index and the j-th index;

[0116] ​Step S1-4: constructing a weighted normalized matrix, wherein an element in the weighted normalized matrix is a product of a normalized evaluation index value and an objective weight of a corresponding index;

[0117] Step S1-5: determining the optimal ideal solution and the worst ideal solution of the evaluation index as follows:

[0118]

[0119] wherein A j + is the optimal ideal solution of the evaluation index, A j - is the worst ideal solution of the evaluation index, is a maximum or minimum value of the first index in the optimal ideal solution A j + , is a maximum or minimum value of the second index in the optimal ideal solution A j + , is a maximum or minimum value of the nth index in the optimal ideal solution A j + , is a maximum or minimum value of the first index in the worst ideal solution A j - , is a maximum or minimum value of the second index in the worst ideal solution A j - , is a maximum or minimum value of the nth index in the worst ideal solution A j - .

[0120] When the evaluation index is a positive index, the optimal ideal solution and the worst ideal solution of the evaluation index are as follows:

[0121]

[0122] When the evaluation index is a negative index, the optimal ideal solution and the worst ideal solution of the evaluation index are as follows:

[0123]

[0124] wherein e ij is an element in the weighted normalized matrix;

[0125] Step S1-6: calculating the Euclidean distances of each to-be-evaluated operation mode to the optimal ideal solution and the worst ideal solution:

[0126]

[0127]

[0128] in: To evaluate the Euclidean distance from job mode i to the optimal ideal solution. To evaluate the Euclidean distance from operation mode i to the worst ideal solution;

[0129] Step S1-7: Calculate the relative proximity:

[0130]

[0131] Where: Z i To evaluate the relative closeness of each evaluation indicator under operation mode i.

[0132] The definition and setting of relevant parameters and variables include:

[0133] (1) Set

[0134] I: represents the set of ships, i∈I, in It is the total number of all seagoing vessels arriving at the port;

[0135] J: represents the set of riverboats, j∈J, in This represents the total number of all matching riverboats;

[0136] Y: Represents the set of stockpiles, y∈Y. in The total number for all storage yards:

[0137] W: represents the set of sea-side unloading machines, w∈W in This represents the total number of ship unloaders on the sea side;

[0138] Z: Represents the set of ship loaders on the river side, z∈Z in This represents the total number of ship loaders on the river side;

[0139] R: Represents the set of stacker-reclaimers in the stockyard, r∈R in This represents the total number of stacker-reclaimers in the stockyard.

[0140] T: represents the set of discretized time periods, t∈T, t=(1,2,…,,H).

[0141] (2) Relevant parameters:

[0142] q i : Represents the arrival time of ship i, i∈I;

[0143] k j : indicates the arrival time of riverboat j, j∈J;

[0144] ql i : represents the length of sea vessel i, including the safety distance between vessels, i∈I;

[0145] kl j : represents the length of river vessel j, including the safety distance between vessels, j∈J;

[0146] represents the maximum number of stacker-reclaimers that can be allocated to each yard;

[0147] η4: represents the efficiency of the stacker-reclaimer in the yard (unit: ton / h);

[0148] T1: represents the time for sea vessel to move from anchorage to berth (unit: h);

[0149] T2: represents the time for river vessel to move from anchorage to berth (unit: h).

[0150] (3) Auxiliary variables

[0151] qs i : represents the starting berthing time of each sea vessel i, i∈I;

[0152] ks j : represents the starting berthing time of each river vessel j, j∈J;

[0153] qe i : represents the starting unberthing time of each sea vessel i, i∈I;

[0154] ke j : represents the starting unberthing time of each river vessel j, j∈J;

[0155] qb i : represents the berthing position of each sea vessel i, i∈I;

[0156] kb j : represents the berthing position of each river vessel j, j∈J;

[0157] db rt : represents the yard position of stacker-reclaimer r at time t, r∈R, t∈T;

[0158] qt iy : represents the time for unloading from sea vessel i to yard y, i∈I, y∈Y;

[0159] kt sj : represents the time for loading from yard y to river vessel j, y∈Y, j∈J.

[0160] (4) Decision variables

[0161] qxii’ is a 0-1 variable, if sea vessel i is completely on the left side of sea vessel i' in the berth-time two-dimensional coordinate graph, sea vessel i is completely on the left side of sea vessel i' from the view of the wharf, qx

[0162] = 1, otherwise 0, i∈I, i'∈I; ii’

[0163] kx jj’ is a 0-1 variable, if river vessel j is completely on the left side of river vessel j' in the berth-time two-dimensional coordinate graph, river vessel j is completely on the left side of river vessel j' from the view of the wharf, kx jj’ = 1, otherwise 0, j∈J, j'∈J;

[0164] g rti is a 0-1 variable, when the stacker-reclaimer r serves sea vessel i at time t, g

[0165] p rtj is a 0-1 variable, when the stacker-reclaimer r serves river vessel j at time t, p

[0166] Step S2: constructing a target function with the least total time of all vessels in the port, the least total time of all vessels waiting in the anchorage and the least total cost of the carrier operation as the target, and constructing the berthing position constraint, the equipment operation constraint, the river-sea intermodal transport connection constraint and the time connection constraint as the constraint conditions;

[0167] The total time of all vessels in the port is:

[0168]

[0169] wherein f1 is the total time of all vessels in the port, qe i is the departure time of sea vessel i, q i is the arrival time of sea vessel i, ke j is the departure time of river vessel j, k j is the arrival time of river vessel j, I is the set of sea vessels, and J is the set of river vessels;

[0170] The total time of all vessels waiting in the anchorage is:

[0171]

[0172] wherein f2 is the total time of all vessels waiting in the anchorage, qs i is the berthing time of sea vessel i, T1 is the time of sea vessel from the anchorage to the berth, ks j is the berthing time of river vessel j, and T2 is the time of river vessel from the anchorage to the berth; ​

[0173] The total cost of the carrier operation is:

[0174] f3=C1+C2+C3+C4+C5+C6+C7

[0175] Wherein f3 is the total cost of the carrier operation, C1 is the sum of the ship berth fee and the environmental damage cost caused by oil pollution when the ship stays in the port, C2 is the anchorage waiting cost when the ship stays in the port, C3 is the ship unloader cost, C4 is the use cost of the stacker-reclaimer, C5 is the horizontal transportation cost of the belt conveyor, C6 is the switching cost of the handling equipment, and C7 is the stacking cost caused by the ground transfer of the dry bulk cargo.

[0176] The objective function is:

[0177] min f = λ1f1+ λ2f2+ λ3f3

[0178] Wherein λ1 is the first weight coefficient, λ2 is the second weight coefficient, and λ3 is the third weight coefficient.

[0179] Step S3: The mixed scheduling model of the river-sea combined transportation is solved by using the heuristic genetic algorithm to obtain the scheduling scheme, including:

[0180] Step S3-1: The river-sea combined transportation ships are uniformly coded in the order of the arrival time, and the total number of the river-sea combined transportation ships is set as N. The river-sea combined transportation ships are coded as 1, 2, 3, 4, 5, … in the order of the arrival time. As shown in Table 1:

[0181] Table 1

[0182]

[0183] Step S3-2: The chromosome coding can only reflect the arrival order of the river-sea combined transportation ships, and cannot directly give the berthing time, berthing position, yard allocation, and specific allocation of the handling equipment of the ships. Therefore, a corresponding heuristic decoding process needs to be designed to construct a complete scheduling scheme according to the ship order arrangement in the chromosome.

[0184] The chromosome decoding of the mixed scheduling specifically includes: first decoding the berthing position of the ship and the ship unloader assignment, and then judging whether there is a direct barge condition at the moment, if yes, the direct barge scheduling mode is adopted, if not, the yard transfer mode is triggered to start, and the berthing time decoding of the ship in the direct barge scheduling mode or the yard transfer mode and the anchorage waiting time decoding are generated.

[0185] The process of decoding the berthing position of the ship and the ship unloader assignment in step S3-2 includes:

[0186] Step S3-2-1-1: After determining the berth of the sea vessel i, traverse the candidate berth of the river vessel j, and select the berth combination that satisfies mind ij , wherein mind ij is the minimum value of the relative distance between the sea vessel i and the river vessel j.

[0187] Step S3-2-1-2: When the berth handling machine is in an idle state, assign the maximum number of idle handling machines to each vessel without exceeding the upper limit constraint of the single vessel equipment, so as to maximize the utilization of equipment.

[0188] When the direct barge scheduling mode is selected, the process of decoding the berthing time of the vessel and the anchorage waiting time in step S3-2 includes:

[0189] Step S3-2-1: When the berth is available and the sea vessel is ready, the berthing time is determined by the arrival time of the sea vessel and the river vessel,

[0190] Step S3-2-2: When the berth is not available, i.e., the previous river vessel is being served, the berthing time is determined by the departure time of the previous river vessel and the arrival time of the river vessel.

[0191] When the yard transshipment scheduling mode is selected, in the process of decoding the berthing time of the vessel and the anchorage waiting time in step S3-2: Since the sea vessel has completely unloaded the transshipment cargo to the yard before the river vessel arrives in the transshipment mode, the berthing time of the river vessel is determined by the arrival time of the river vessel. For the anchorage waiting time of all vessels, if the berthing time of the vessel is later than the arrival time, the anchorage waiting time is calculated according to the waiting time.

[0192] Through the above process, coordinated scheduling and dynamic switching of the two operation modes are realized, the overall operation efficiency is improved, and resource conflicts are alleviated.

[0193] Step S3-3: Based on the estimated arrival time of the river-sea combined transport vessel, an initial solution sequence with practical scheduling significance is constructed, and the initial solution generation process includes:

[0194] Step S3-3-1: Read the estimated arrival time of all vessels;

[0195] Step S3-3-2: Sort the vessel set in ascending order of arrival time;

[0196] Step S3-3-3: According to the sorting result, record the vessel number and generate an initial individual;

[0197] Step S3-3-4: Form a plurality of sequences based on the sorting disturbance as the initial population to enhance the diversity of the algorithm.

[0198] Step S3-4: Selecting fitness function F c In order to reduce the number of local optimal solutions and improve the global optimal convergence probability, the improved fitness function is adopted according to the model objective function, which not only ensures the non-negative fitness value, but also effectively enhances the global search ability of the algorithm, and its expression is:

[0199]

[0200] Wherein: f c is the objective function value of the individual, and η is the parameter reflecting the problem size;

[0201] Step S3-5: performing genetic operator operation to obtain a scheduling scheme, and scheduling based on the scheduling scheme, wherein the genetic operator specifically includes a selection operator, a crossover operator and a mutation operator.

[0202] (1) Selection operator

[0203] The tournament selection method is adopted, the operation of selecting the winning individual and eliminating the inferior individual from the population is called selection, and the purpose of selection is to directly inherit the optimized individual (or solution) to the next generation or produce new individuals through pairing crossover and then inherit them to the next generation. The selection operation is based on the fitness evaluation of the individuals in the population, and the tournament selection (Tournament selection) is adopted in the algorithm. S individuals are randomly sampled from the population, and then the optimal individual is selected to enter the next generation. Only when the fitness value of the individual is better than that of the other s-1 competitors, can the individual win the tournament.

[0204] (2) Crossover operator

[0205] Its execution process includes:

[0206] Step S3-5-1-1: selecting two different chromosome individuals from the population after tournament selection, denoted as parent A and parent B;

[0207] Step S3-5-1-2: randomly selecting two crossover points pos1 and pos2 in parent A, and cutting the gene segment in the interval [pos1, pos2] in parent A;

[0208] Step S3-5-1-3: copying the interval gene segment of parent A directly to the same position of the offspring, preserving the local timing characteristics; the remaining genes are filled according to the original order in parent B, and the ship number in the existing offspring is skipped to ensure that the chromosome is a legal arrangement;

[0209] Step S3-5-1-4: verifying whether the offspring satisfies the ship uniqueness constraint, and if a conflict is generated due to the crossover, a repair mechanism (such as replacing the duplicate gene) is started.

[0210] (3) Mutation operator

[0211] Its execution process includes:

[0212] Step S3-5-2-1: Randomly select an individual with a specific chromosome from the population;

[0213] Step S3-5-2-2: Randomly select two different positions in the chromosome sequence;

[0214] Step S3-5-2-3: Completely reverse the gene sequence between the two positions to generate a new individual.

[0215] In the hybrid scheduling scenario, infeasible solutions mainly manifest in three types: berth spatiotemporal conflicts, insufficient anchorage buffer time, and excessive yard capacity. Therefore, step S3 also includes:

[0216] For berth space-time conflicts, insufficient anchorage buffer time, and excessive yard capacity, a tiered repair approach will be implemented, specifically including:

[0217] Berth conflict resolution: The timeline is adjusted with a movement step of α to ensure the spatiotemporal continuity of direct transport operations.

[0218] Anchorage buffer repair: When the riverboat connection time window violates the constraints, a reallocation strategy is adopted to recalculate the anchorage scheduling scheme with the minimum waiting time;

[0219] Yard capacity restoration: Implement a neighborhood diffusion strategy for dry bulk cargo that exceeds storage limits, relocate the overflow cargo to adjacent storage areas and update the operation sequence.

[0220] The repair process employs a tabu search mechanism, recording the repair paths already attempted. If five consecutive repair attempts fail to reach the feasible region, the individual is discarded.

[0221] Multi-condition termination mechanism: This application sets the algorithm termination condition as the number of population iterations reaching the maximum number of iterations MAX_generation, and the specific value is determined based on the convergence results of the experimental data.

[0222] like Figure 6 The diagram shown is a flowchart of the heuristic genetic algorithm solution described in step S5 above.

[0223] In this application, the river-sea combined transportation production scheduling data of a bulk cargo jetty wharf in a certain sea port is taken as the specific implementation basis to build a mixed scheduling model of sea vessels and river vessels. The berth type of the port is continuous type berth, and the average water depth of the berth is more than 10 meters, which can meet the berthing demand of multiple bulk cargo vessels. Among them, the sea vessel berthing area is located in the alongshore wharf, and the length of the wharf is 500 meters, which can simultaneously accommodate 2 100,000-ton sea vessels. The matching river vessels of river-sea combined transportation are parked in the jetty wharf, which is equipped with one jetty, and the length of the jetty is 250 meters, which can simultaneously meet the operation of 2 5,000-ton river vessels on one side, and the two sides of the jetty are numbered uniformly in a linear merging manner (0-500 meters), among which 0-250 meters is the far sea vessel berth and 251-500 meters is the near sea vessel berth.

[0224] In this embodiment, it is set that the time of sea vessels from anchorage to berth is 30 minutes, and the time of river vessels from anchorage to berth is 20 minutes. The maximum number of ship unloaders used in a single sea side berth is 4, the maximum number of ship loaders used in a single river side berth is 2, and the maximum number of available stacker-reclaimers is 2. The river-sea combined transportation ship matching plan and parameters are shown in Table 2, the specific parameters of the loading and unloading equipment specifications are shown in Table 3, and other costs related to port operation are shown in Table 4, and the cargo storage cost is shown in Table 5.

[0225] The river-sea combined transportation ship matching plan and parameters of a certain sea port bulk cargo are shown in Table 2:

[0226]

[0227]

[0228] The loading and unloading equipment specifications of the river-sea combined transportation operation area of a certain sea port bulk cargo are shown in Table 3:

[0229] Table 3

[0230]

[0231]

[0232] Other costs of the river-sea combined transportation of a certain sea port bulk cargo are shown in Table 4:

[0233] Table 4

[0234] Ship type Berthing cost (Yuan / h) Environmental cost (Yuan / h) Anchorage waiting cost (Yuan / h) 30000-ton sea vessel 1100 800 900 50000-ton sea vessel 1500 1200 1300 2000-ton river vessel 320 150 250 3000-ton river vessel 450 300 380 5000-ton river vessel 600 480 540

[0235] The cargo storage cost of the river-sea combined transportation of a certain sea port bulk cargo is shown in Table 5:

[0236] Table 5

[0237] Cargo type Stacking unit cost (Yuan / ton·h) Ore 0.1 Coal 0.08

[0238] In this embodiment, the main parameters of the heuristic genetic algorithm are set as follows: the maximum number of iterations is set to 1000, the population size is 200, the crossover probability is 0.8, and the mutation probability is 0.2.

[0239] As shown in Figure 7 , in combination with the above parameters and data information, the Jianghai combined transportation direct dispatching model is run for solution, and the fitness function value change curve in the process of 1000 iterations of the algorithm is as shown in Figure 7 .

[0240] Suppose the weight coefficients of λ1, λ2, and λ3 are 0.3, 0.3, and 0.4 respectively, after the model is run, the total time of the ship in the port under the mixed dispatching mode is about 124.60 h, the anchorage waiting time is about 12.41 h, and the total operating cost of the carrier is about 332271.39 yuan.

[0241] At the same time, after the model is run, the dry bulk Jianghai combined transportation joint dispatching plan (see Table 6), the Jianghai combined transportation operation time (see Table 7), the Jianghai combined transportation yard allocation table (see Table 8 for sea ships and Table 9 for river ships), and the Jianghai combined transportation operating cost (see Table 10 for sea ships and Table 11 for river ships) are obtained.

[0242] Table 6

[0243]

[0244] As can be seen from the dry bulk Jianghai combined transportation joint dispatching plan table 6, the coordinated scheduling optimization effect of sea ships and river ships is achieved under the consideration of anchorage waiting and yard transfer factors. For example, for task P, the sea ship SV1-ore is docked at the shore wharf 130 meters at 01:15, equipped with 4 unloading machines to realize continuous unloading during docking; and the corresponding RB1 series river ships are docked at the breakwater wharf in turn, the positions are concentrated in the 340-430 meter interval, and the docking times are different from 01:15 to 20:00, and each ship is equipped with 2 loading machines. This dispatching scheme effectively balances the connection between sea ship unloading and river ship loading, ensures that the goods can be quickly transported to the river ship through the belt conveyor under the condition of no waiting of the sea ship, so as to reduce the delay caused by the untimely arrival of the river ship.

[0245] In order to more intuitively represent the docking time and position of the arriving ship, according to the dry bulk Jianghai combined transportation joint allocation plan scheme shown in Table 6, the position-time two-dimensional coordinate diagram of the sea ship and river ship berth allocation plan is drawn, as shown in Figure 8 , Figure 9 .

[0246] Table 7

[0247]

[0248]

[0249] From Table 7, it can be seen that the sea ships have no anchorage waiting time, indicating that the sea ships are quickly berthed at the scheduled time and start unloading operations at the shore-type wharf; while the river ships have different degrees of anchorage waiting when berthing at the spur-type wharf, and the waiting time varies from 0 to 1.67. Taking task P as an example, the loading and unloading time of sea ship SV1-ore is 14.93, while the loading and unloading time of RB1 series river ships is between 1.88 and 4.86, and the longer waiting time of some river ships (such as RB1-4 and RB1-5) shows that due to the unevenness of the arrival time of river ships, some ships need to wait for a short time in the anchorage before completing the berthing.

[0250] The mixed scheduling mode uses the anchorage and the yard as a buffer, so that the sea ships can continue unloading without interruption due to the delay of river ships, and the river ships can wait in the anchorage to obtain suitable berthing conditions, thereby realizing the effective connection of sea ship unloading and river ship loading. Although the waiting time of some river ships is increased, this scheduling strategy shows strong adaptability in balancing the efficiency of ship operation and resource utilization, and provides certain support for reducing operating costs and improving joint transport efficiency.

[0251] Table 8

[0252]

[0253] Table 9

[0254]

[0255]

[0256] Tables 8 and 9 reveal the space-time coordination characteristics of dry bulk storage and transfer under the mixed scheduling mode. Taking task P as an example, sea ship SV1-ore is unloaded in two batches to S1-1 stack and S1-2 stack, with an interval of only 23 minutes, which reflects the segmented unloading strategy of uneven arrival of river ships. The river ships mainly present the characteristics of concentrated period and dispersed stacking: the ore river ships arriving later than the sea ship departure time concentrate in 19:00-20:00 to call S1-1 stack and S1-2 stack, which reflects the dynamic allocation of yard resources. The configuration of the stacker-reclaimer forms a 1:1 linkage with the ship unloader and the ship loader. This scheme effectively alleviates the influence of uneven arrival of river ships on joint transport direct barge operation through the mechanism of dynamic unloading and concentrated loading.

[0257] Table 10

[0258]

[0259] Table 11

[0260]

[0261]

[0262] Tables 10 and 11 disclose the operating costs of sea vessels and river vessels in the mixed scheduling mode, in which the effects of the yard storage and the anchorage waiting are considered. For example, in the SV1-ore total cost, the equipment cost accounts for 47.87%, and the storage cost accounts for only 5.46%, which indicates that the direct barge operation is highly efficient.

[0263] The river vessel costs are significantly differentiated. For example, RB1-3 and RB2-7 and RB2-8 have the highest total costs due to the high anchorage waiting and loading and unloading times. The zero anchorage waiting costs of RB1-2, RB1-8, RB1-9, RB2-9, RB2-10, RB2-11, RB2-12 and RB2-14 verify the optimization of the storage strategy on the time coordination, which reflects that the port flexibly regulates the anchorage waiting and the yard transfer through the mixed scheduling strategy when facing the coexistence of the dispersed and concentrated river vessel arrival times, thereby reducing the overall operating cost while ensuring the efficient use of resources. The results verify the effectiveness of the model in dealing with the dynamic arrival of ships and the uncertainty of resource scheduling, and provide a quantitative basis for the cost trade-off among equipment investment, yard construction and ship scheduling.

[0264] In the embodiment, a multi-objective river-sea combined transportation mixed scheduling optimization model of the total time of all ships in port, the total anchorage waiting time of all ships and the total operating cost of the carrier is constructed, and a heuristic genetic algorithm is designed to solve the model. Then, the algorithm is used to solve the actual port data, and the river-sea combined transportation scheduling scheme, operation time and operating cost in the scheduling period are obtained. The seamless connection of continuous unloading of sea vessels and effective loading of river vessels is realized, which provides an optimal scheduling method for the mixed scheduling mode between sea vessels and river vessels in river-sea combined transportation, and maximizes the cost reduction and efficiency improvement.

[0265] If the above functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts that essentially contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

Claims

1. A method for optimizing the mixed scheduling of seagoing vessels and river vessels in dry bulk river-sea intermodal transport, characterized in that, include: Step S1: Construct a river-sea intermodal transport hybrid scheduling model and define and set relevant parameters and variables; Step S2: Construct an objective function with the goals of minimizing the total time of ships in port, minimizing the total waiting time of all ships at anchorages, and minimizing the total operating cost of the carrier. Construct berthing position constraints, equipment operation constraints, river-sea intermodal transport connection constraints, and time connection constraints as constraints. Step S3: Use a heuristic genetic algorithm to solve the river-sea intermodal transport hybrid scheduling model to obtain a scheduling scheme for scheduling.

2. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 1, characterized in that, Step S1 includes: Step S1-1: Assume the river-sea intermodal direct transport scheduling model contains n evaluation indicators and a total of m operational modes to be evaluated. Establish the original evaluation matrix as R = [r ij ] m×n , where r ij Let be the evaluation value of the i-th evaluation indicator for the j-th work mode; Step S1-2: Divide the evaluation indicators into positive and negative indicators. The standardization process for positive indicators is as follows: The standardization process for negative indicators is as follows: Where: s ij The standardized evaluation index value is min(r). j ) represents the minimum index value for the j-th operation mode, max(r) j ) represents the maximum index value for the j-th operation mode; Step S1-3: Determine the objective weight of each indicator based on the amount of information contained in each indicator: Where: ω j V represents the objective weight of the j-th indicator. j Let σ be the amount of information contained in the j-th indicator. j p is the standard deviation of the j-th indicator. ij To evaluate the correlation coefficient between the i-th and j-th indicators; Step S1-4: Construct a weighted standardization matrix, where each element in the weighted standardization matrix is ​​the product of the standardized evaluation index value and the objective weight of the corresponding index. Step S1-5: Determine the optimal and worst ideal solutions for the evaluation index as follows: Among them: A j + For the optimal ideal solution of the evaluation index, A j - The worst-case ideal solution for the evaluation index. For the first index in the optimal ideal solution A j + The maximum or minimum value in, For the second index in the optimal ideal solution A j + The maximum or minimum value in, For the nth index in the optimal ideal solution A j + The maximum or minimum value in, For the first index in the worst ideal solution A j - The maximum or minimum value in, For the second index in the worst ideal solution A j - The maximum or minimum value in, For the nth index in the worst ideal solution A j - The maximum or minimum value in; When the evaluation index is a positive index, the optimal and worst ideal solutions for the evaluation index are: When the evaluation index is negative, the optimal and worst ideal solutions for the evaluation index are: Where: e ij These are the elements in the weighted standardized matrix; Step S1-6: Calculate the Euclidean distance from each job mode to be evaluated to the optimal and worst ideal solutions: in: To evaluate the Euclidean distance from job mode i to the optimal ideal solution. To evaluate the Euclidean distance from operation mode i to the worst ideal solution; Step S1-7: Calculate the relative proximity: Where: Z i To evaluate the relative closeness of each evaluation indicator under operation mode i.

3. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 2, characterized in that, The total time all vessels spent in port is: Where: f1 is the total time all vessels spend in port, qe i Let q be the time when ship i begins to depart from its berth. i For the arrival time of seagoing vessel i, ke j k is the starting departure time of riverboat j. j Let I be the arrival time of riverboat j, I be the assembly time of ocean-going vessels, and J be the assembly time of riverboats. The total waiting time for all ships at anchor is: Where: f2 is the total waiting time of all ships at anchor, qs i Let T1 be the start time of berthing for seagoing vessel i, T1 be the time it takes for the seagoing vessel to travel from the anchorage to the berth, and ks be the start time of berthing for seagoing vessel i. j T1 represents the start time of berthing of riverboat j, and T2 represents the time it takes for the riverboat to travel from the anchorage to the berth. The carrier's total operating costs are: f3 = C1 + C2 + C3 + C4 + C5 + C6 + C7 Where: f3 is the carrier's total operating cost, C1 is the sum of ship berthing fees and environmental damage costs caused by oil spills incurred when the ship stays in port, C2 is the anchorage waiting cost when the ship stays in port, C3 is the cost of ship loading and unloading machinery, C4 is the cost of stacker-reclaimer operation, C5 is the cost of belt conveyor horizontal transport, C6 is the switching cost of loading and unloading equipment, and C7 is the storage cost incurred due to the transshipment of dry bulk cargo. The objective function is: minf = λ1f1 + λ2f2 + λ3f3 Where: λ1 is the first weight coefficient, λ2 is the second weight coefficient, and λ3 is the third weight coefficient.

4. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 2, characterized in that, Step S3 includes: Step S3-1: Serialize the vessels according to their arrival time sequence in the river-sea intermodal transport; Step S3-2: First, decode the ship's berthing position and the ship's loading and unloading machine assignment, and then determine whether the ship's direct docking conditions are available. If so, adopt the direct docking scheduling mode. If not, trigger the start of the yard transfer mode and generate the decoding of the ship's berthing time and anchorage waiting time in the direct docking scheduling mode or the yard transfer mode. Step S3-3: Based on the estimated arrival time of the river-sea intermodal vessels, construct an initial solution sequence with practical scheduling significance; Step S3-4: Select the fitness function; Step S3-5: Perform genetic operator operations to obtain a scheduling scheme, and perform scheduling based on the scheduling scheme. The genetic operators specifically include selection operators, crossover operators, and mutation operators.

5. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 4, characterized in that, The process of decoding the ship's berthing position and the ship's loading / unloading machine assignment in step S3-2 includes: Step S3-2-1-1: Following the principle of minimizing relative berthing distance, after determining the berth for seagoing vessel i, iterate through the candidate berths for riverboat j and select the one that satisfies the minimum requirement. ij The berth combination, in which, mind ij This refers to the minimum relative distance between seagoing vessel i and riverboat j when they are moored. Step S3-2-1-2: Following the principle of allocating as many as possible, when the berth loading and unloading machines are idle, allocate the maximum number of idle loading and unloading machines to each ship without exceeding the upper limit of equipment per ship, thereby maximizing equipment utilization. When the direct-delivery dispatch mode is selected, the process of decoding the berthing time and anchorage waiting time in step S3-2 includes: Step S3-2-1: When the berth is available and the seagoing vessel is ready, the berthing time is determined by the arrival times of the seagoing vessel and the river vessel. Step S3-2-2: When the berth is unavailable, i.e., the previous river vessel is being served, the berthing time is determined by the departure time of the previous river vessel and the arrival time of this river vessel. When the yard transshipment scheduling mode is selected, in step S3-2, during the decoding of the berthing time and the anchorage waiting time of the vessel: the berthing time of the river vessel is determined by the arrival time of the river vessel. For the anchorage waiting time of all vessels, if the berthing time of the vessel is later than the arrival time, the anchorage waiting time is calculated based on the berthing time.

6. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 4, characterized in that, The initial solution generation process in step S3-3 includes: Step S3-3-1: Read the estimated arrival times of all vessels; Step S3-3-2: Sort the vessel group in ascending order of arrival time; Step S3-3-3: Based on the sorting results, record the ship number and generate the initial individual; Step S3-3-4: Use multiple sequences formed based on sorting perturbation as the initial population to enhance the diversity of the algorithm.

7. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 4, characterized in that, The selection operator uses a tournament selection method, randomly sampling s individuals from the population and selecting the best individual to enter the next generation.

8. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 4, characterized in that, The execution process of the crossover operator includes: Step S3-5-1-1: Select two individuals with different chromosomes from the population selected through the tournament, denoted as parent A and parent B; Step S3-5-1-2: Randomly select two intersection points pos1 and pos2 in parent generation A, and extract the gene segment in parent generation A located in the interval [pos1,pos2]. Step S3-5-1-3: Copy the gene segment of parent A directly to the same position in the offspring, preserving its local temporal characteristics; fill in the remaining genes according to the original order in parent B, skipping the ship numbers already present in the offspring, to ensure that the chromosomes are legally arranged; Step S3-5-1-4: Verify whether the offspring meets the ship uniqueness constraint. If a conflict arises due to crossover, initiate the repair mechanism.

9. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 4, characterized in that, The execution process of the mutation operator includes: Step S3-5-2-1: Randomly select an individual with a specific chromosome from the population; Step S3-5-2-2: Randomly select two different positions in the chromosome sequence; Step S3-5-2-3: Completely reverse the gene sequence between the two positions to generate a new individual.

10. The method for optimizing the mixed scheduling of seagoing and river vessels in dry bulk cargo river-sea intermodal transport according to claim 4, characterized in that, Step S3 further includes: For berth space-time conflicts, insufficient anchorage buffer time, and excessive yard capacity, a tiered repair approach will be implemented, specifically including: Berth conflict resolution: The timeline is adjusted with a movement step of α to ensure the spatiotemporal continuity of direct transport operations. Anchorage buffer repair: When the riverboat connection time window violates the constraints, a reallocation strategy is adopted to recalculate the anchorage scheduling scheme with the minimum waiting time; Yard capacity restoration: Implement a neighborhood diffusion strategy for dry bulk cargo that exceeds storage limits, relocate the overflow cargo to adjacent storage areas and update the operation sequence.

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