A containerized loading method for a special pulp ship

Abstract

The present invention proposes a containerized loading method for a special pulp ship, which comprises: pre-configuring loading constraints and loading preferences according to artificial experience, and formulating a task sorting strategy according to the loading preferences; adapting an intelligent loading algorithm to loading ship attributes and cargo loading attributes based on loading tasks, and setting an optimization target and a corresponding weight of the loading task; respectively adopting a packing algorithm, a container turnover optimization algorithm, and an unpacked quantity optimization algorithm to cyclically solve loading schemes of multiple loading tasks, and updating and recording a target loading scheme; generating a special ship loading diagram according to the target loading scheme, and outputting a loading file in JSON format through the loading diagram for calling.

Description

Technical Field

[0001] The present invention relates to the technical field of special ship stowage, and in particular to a containerized stowage method for a special pulp ship. Background Art

[0002] The ship stowage plan is mainly composed of the pre-stowage plan and the actual stowage plan. The container ship assembly problem in the field of special ship assembly is a combined optimization problem with multiple objectives, multiple constraints and multiple task strategies. The quality of the stowage plan will affect the loading and unloading efficiency of the container ship and the versatility and efficiency of the subsequent special ship stowage.

[0003] With the introduction of the concept of intelligent stowage, the manual stowage mode based mainly on the stowage staff's experience has become a major bottleneck in the existing container stowage operations. Currently, more and more container ships are beginning to adopt intelligent stowage. Intelligent stowage refers to the decision-making process of simulating the ideas and methods of container stowers by artificial intelligence algorithms, comprehensively considering factors such as equipment conditions, task distribution, storage status, and automatically stowing containers scheduled for export onto the target special ship's container positions based on pre-stowage ship plans, ship seaworthiness requirements, and terminal operation requirements.

[0004] However, the current research on intelligent stowage of special ship containers has the following shortcomings:

[0005] (1) There are few cases in which special constraints and loading preferences are considered in the loading problem of special ship containers, which cannot fully meet the flexibility and versatility of special ship container loading;

[0006] (2) In the actual assembly process of special-purpose ship containers, the impact of factors such as container turning and operational conflicts on loading was not considered, and the overall balanced loading of special-purpose ships was not fully considered;

[0007] (3) When simulating the stowage process through artificial intelligence algorithms, the solutions for different types of special ships are not fully adapted. At the same time, the process of converting manual experience into artificial intelligence algorithms lacks the embedding of the overall algorithm framework, which cannot guarantee the universality and efficiency of the intelligent algorithm, and has a great impact on the output of high-quality stowage plans.

[0008] Therefore, there is an urgent need for a containerized loading method for pulp special ships to solve the above-mentioned deficiencies in the research based on intelligent loading of special ship containers, and further study the optimization problem of special ship container loading. Summary of the invention

[0009] In view of the deficiencies of the prior art, the present invention proposes a containerized loading method for a special pulp ship.

[0010] The first aspect of the present invention discloses a containerized loading method for a special pulp ship, comprising:

[0011] S1: pre-configure the loading constraints and loading preferences according to manual experience, and formulate the task sorting strategy according to the loading preferences;

[0012] S2: Adapt the intelligent loading algorithm to the ship type attributes and the cargo loading attributes based on the loading task, and convert the ship data and task data into a unified format for independent packaging to provide to the intelligent loading algorithm for data identification and reading. The intelligent loading algorithm includes a packing algorithm, a box turnover optimization algorithm, an unpacked box optimization algorithm, and a box type identification optimization algorithm;

[0013] S3: Setting the optimization objectives and corresponding weights of the stowage task, wherein the optimization objectives include: ① ensuring that the number of unpacked containers is minimized; ② ensuring that the weighted mean of the number of overturned containers in the port of origin and the port of destination is minimized; ③ ensuring that the number of mixed layers of containers in different ports of destination is minimized;

[0014] S4: the packing algorithm is used to cyclically solve the loading schemes of multiple loading tasks. If a loading scheme feasible solution that meets the optimization target of the container turnover quantity exists in multiple cyclic solving processes, the feasible solution is recorded and the optimization target ③ is cyclically optimized based on the feasible solution by the packing algorithm. The target loading scheme is updated and recorded, and the process is skipped to step S7. If a loading scheme feasible solution cannot be generated under the condition of meeting the optimization target of the container turnover quantity in multiple cyclic solving processes, the process is skipped to step S5.

[0015] S5: the loading schemes of multiple loading tasks are solved cyclically by using the container turnover optimization algorithm. If a loading scheme feasible solution that satisfies all loading tasks exists in multiple cyclic solution processes, the feasible solution is recorded and the optimization target ② and the optimization target ③ are weightedly optimized on the basis of the feasible solution by using the container turnover optimization algorithm. The target loading scheme is updated and recorded, and the process is skipped to step S7. If the multiple cyclic solution processes cannot satisfy the loading scheme feasible solution that is not optimized for the container turnover quantity under the condition of satisfying the container turnover optimization target, the process is skipped to step S6.

[0016] S6: using the unloaded quantity optimization algorithm to cyclically solve the loading schemes of multiple loading tasks, recording the current solution, sequentially weightedly optimizing the optimization target ①, the optimization target ② and the optimization target ③ through the unloaded quantity optimization algorithm, and updating and recording the target loading scheme;

[0017] S7: Generate a special ship stowage diagram according to the target stowage plan, and call the stowage file in JSON format output by the stowage diagram, wherein the stowage information of all containers of the target stowage plan is recorded in the stowage file.

[0018] In an optional embodiment, the loading constraints preconfigured according to manual experience include primary loading constraints and secondary loading constraints, the primary loading constraints include: stack height limit, weight limit, same width of containers in the same stack, same height of containers in the same layer, bay capacity limit, container location priority constraint, container same-slot matching constraint; the secondary loading constraints include: standard containers are not mixed with extra-wide containers, frame containers are loaded in the cabin, new energy containers are loaded outside the warehouse, standard containers are loaded on the upper cover of the frame containers, and special frame container loading constraints.

[0019] In an optional embodiment, the loading preferences preconfigured based on manual experience include: ① containers with the same destination port are loaded on the same layer; ② non-mixed loading preference in the same cabin; ③ the destination port of the upper container is closer than the destination port of the lower container; ④ preference for ship loading volume; ⑤ manual loading preference;

[0020] The task sorting strategy formulated according to the loading preference includes: ① sorting the initial assembly tasks in the order of departure ports from near to far and destination ports from far to near; ② sorting the initial assembly tasks in the order of destination ports from far to near and departure ports from near to far; ③ giving priority to special frame containers, and sorting the initial assembly tasks in the order of departure ports from near to far and destination ports from far to near; ④ giving priority to special frame containers, and sorting the initial assembly tasks in the order of destination ports from far to near and departure ports from near to far.

[0021] In an optional embodiment, adapting the intelligent loading algorithm to the ship type attributes includes:

[0022] S21: Divide the ship into multiple compartments horizontally and vertically into deck positions and cabin positions, and number the deck positions and cabin positions;

[0023] S22: dividing the container slots into primary container slots, secondary container slots and tertiary container slots by using the primary size, secondary size and tertiary size container reference units, matching the primary container slots with the secondary container slots and the tertiary container slots, and distinguishing the container slots of standard containers and extra-wide containers;

[0024] S23: All slots are marked with the three-dimensional coordinates of shells, stacks, and layers, and additional marking is used to determine whether there is a container in the slot;

[0025] S24: Mark the bay position attributes according to the bay coordinates of the three-dimensional coordinates, determine whether the corresponding bay position is suitable for assembling special containers through the bay position attributes, and limit the stacking height and stacking weight of the container in units of stacks. The bay position attributes include bay position size, bay position position, and the cabin to which the bay position belongs.

[0026] In an optional embodiment, adapting the intelligent loading algorithm to the cargo loading attributes based on the loading task includes:

[0027] S25: Using the loading task as a task unit, marking the departure port, destination port, container weight, container type and special container tasks associated with the loading task through an intelligent loading algorithm;

[0028] S26: marking the bays that can be loaded currently through the intelligent loading algorithm;

[0029] S27: Marking the cargo loaded on the deck and in-hold positions through an intelligent loading algorithm.

[0030] In an optional embodiment, the packing algorithm sorts the loading tasks according to the task sorting strategy ①, and the steps of the packing algorithm include:

[0031] S41: Obtain loading task;

[0032] S42: The stowage task generates a loadable bay for the current task based on the conditions of satisfying the special loading constraint and the container turning constraint;

[0033] S43: using a roulette mechanism to select a loading bay from the available loading bays on the premise that the loading preference ① and the loading preference ② are satisfied;

[0034] S44: packing the containers in the loading task layer by layer according to the selected packing positions under the first-level loading constraint;

[0035] S45: Repeat steps S42-S44 until the number of unloaded containers reaches zero, and obtain the next loading task;

[0036] S46: Repeat steps S42-S45 until all loading tasks are completed.

[0037] In an optional embodiment, the container turnover optimization algorithm performs a cyclic solution to the loading schemes of multiple loading tasks, and the steps include:

[0038] S51: Generate a corresponding loading task sequence according to the task sequencing strategy;

[0039] S52: Obtaining loading tasks according to the order of the loading task sequence;

[0040] S53: generating the available loading bays for the current stowage task based on the no-turnover constraint and the secondary loading constraint. If there are feasible loading bays in the stowage task, jump to step S55, otherwise continue to execute step S54;

[0041] S54: Generate the available loading bays for the current loading task based on the secondary loading constraint and the container turning constraint. If there are feasible loading bays in the loading task, continue to execute step S55. Otherwise, jump to step S52 to iterate the loading tasks of the current loading task sequence for multiple times. If no feasible solution can be generated, jump to step S59 to execute the next loading task sequence.

[0042] S55: Selecting a loading bay from the available loading bays in the current loading task sequence through a roulette mechanism under the conditions of satisfying loading preference ①, loading preference ②, and loading preference ③;

[0043] S56: packing containers layer by layer for the loading tasks of the current loading task sequence according to the selected packing positions under the first-level loading constraint;

[0044] S57: Repeat steps S52-S56 until the number of unloaded containers is zero, and obtain the next loading task in the current loading task sequence;

[0045] S58: Repeat steps S52-S57 until all loading tasks under the current loading task sequence are completed, and all loading task records are generated into the current loading task sequence to achieve the optimal loading plan;

[0046] S59: Repeat steps S52-S58 until the optimal loading scheme under all loading task sequences is solved, and output the target loading scheme according to the optimal loading scheme.

[0047] In an optional embodiment, the unpacked quantity optimization algorithm is used to cyclically solve the loading schemes of multiple loading tasks, and the steps of the unpacked quantity optimization algorithm include:

[0048] S61: Generate a corresponding loading task sequence according to the task sequencing strategy;

[0049] S62: Obtaining loading tasks according to the order of the loading task sequence;

[0050] S63: Generate the available loading bays for the current stowage task based on the no-turnover constraint and the secondary loading constraint. If there are feasible loading bays in the stowage task, jump to step S65, otherwise continue to execute step S64;

[0051] S64: Generate the available loading bays for the current loading task based on the secondary loading constraint and the container turning constraint. If there are feasible loading bays in the loading task, continue to execute step S65. Otherwise, jump to step S62 to perform multiple iterations of the loading tasks of the current loading task sequence. If no feasible solution can be generated, jump to step S69 to execute the next loading task sequence.

[0052] S65: selecting a loading bay position through a roulette mechanism for the loading bay positions existing in the stowage task under the current loading task sequence based on the conditions of satisfying loading preference ①, loading preference ② and loading preference ③;

[0053] S66: packing containers layer by layer for the loading tasks of the current loading task sequence according to the selected loading bays under the first-level loading constraint;

[0054] S67: Repeat steps S62-S66 until the number of unloaded containers is zero, and obtain the next loading task in the current loading task sequence;

[0055] S68: Repeat steps S62-S67 to traverse all loading tasks in the current loading task sequence, and record the preferred loading solutions generated by all loading tasks in the current loading task sequence;

[0056] S69: Repeat steps S62-S68 until the optimal loading scheme under all loading task sequences is solved, and output the target loading scheme according to the optimal loading scheme.

[0057] In an optional embodiment, the box type recognition optimization algorithm includes primary size box type recognition, secondary size box type recognition and tertiary size box type recognition, and the primary size box type recognition includes:

[0058] The positions of the first-level size boxes are prioritized, which are the first-level box positions in the cabin, the first-level box positions on the deck, the non-first-level box positions on the deck, and the non-first-level box positions in the cabin. The first-level size boxes are prioritized and the corresponding positions are selected for packing through the box packing position selection function and identification rules;

[0059] The identification rule traverses the bays on the ship to determine whether the bay is an odd bay for which there is no corresponding even bay. If so, the odd bay is added to the pre-packing list of the first-level size box according to the priority of the position; it is determined whether there is a new odd bay in the original odd bay in the pre-packing list that can form a new even bay with the original odd bay. If not, the original odd bay in the pre-packing list is retained. If there is a new odd bay, it is determined whether the position distribution of the new odd bay that forms the new even bay with the original odd bay is the same as the position distribution of the original odd bay on the ship. If the position distribution is different, the original odd bay is saved in the pre-packing list. If the position distribution is the same, the original odd bay is removed from the pre-packing list.

[0060] In an optional embodiment, the secondary size box type identification includes:

[0061] Identify the special ship type characteristics of the ship, and determine whether the bottom layer of the last even-numbered bay in the ship's cabin with special ship type characteristics is loaded with second-size containers according to the special ship type constraints. If so, record the current number of containers and cumulatively add second-size containers to the last even-numbered bays until the bottom layer of the last even-numbered bay in the cabin is filled with second-size containers. Traverse all loading tasks and call the packing function to perform the second-size container loading operation until the special ship type constraints are met.

[0062] In an optional embodiment, the three-level size box type identification includes:

[0063] The third-level size boxes and other box types are marked and divided into extra-wide boxes and standard boxes and saved in four-dimensional variables. The first layer of the four-dimensional variables represents the three-dimensional coordinate box positions of standard boxes, and the second layer represents the three-dimensional coordinate box positions of extra-wide boxes. In the process of generating the available box positions for the current task by the intelligent loading algorithm, standard boxes and extra-wide boxes are identified, and the available box positions are divided into standard box positions and extra-wide box positions for loading containers. The standard box positions and extra-wide box positions constrain the containers loaded on the box positions, and only containers of the same box type matching the box positions are loaded.

[0064] In an optional embodiment, the loading preference preconfigured according to manual experience also includes: containers belonging to the same port of departure and port of destination are placed in non-adjacent holds of the ship, adjacent prohibited hold pairs in the ship are defined by an algorithm and saved in prohibited hold pair variables, and containers with the same port of departure and port of destination in the target loading task are traversed according to the prohibited hold pair variables to see whether there are containers placed in adjacent holds, and if so, the optional feasible bays stored in the prohibited hold pair variables are replaced to meet the loading preference of placing containers with the same port of departure and port of destination in non-adjacent holds of the ship.

[0065] The second aspect of the present invention discloses a containerized loading equipment for a special pulp ship, comprising:

[0066] at least one processor, and

[0067] a memory communicatively connected to the at least one processor; wherein,

[0068] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the containerized loading method for a special pulp ship as disclosed in any one of the first aspects of the present invention.

[0069] The third aspect of the present invention discloses a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the containerized loading method for a special pulp ship as disclosed in any one of the first aspect of the present invention.

[0070] Compared with the prior art, the present invention has the following advantages:

[0071] (1) The present invention pre-configures loading constraints and loading preferences based on manual experience, and formulates a task sequencing strategy based on the loading preferences to meet the requirements of flexibility and versatility for container loading processes of different special ships;

[0072] (2) The present invention adapts the intelligent loading algorithm to the ship type attributes and the cargo loading attributes based on the loading task, and converts the ship data and the task data into a unified format for independent packaging to provide to the intelligent loading algorithm for data identification and reading. It is converted into an algorithm program through artificial experience and nested in the overall algorithm framework, which can improve the versatility and efficiency of the algorithm and ensure that the algorithm can output high-quality special ship loading plans that meet the loading requirements.

[0073] (3) The present invention sets the optimization target and corresponding weight of the loading task, and adds the packing algorithm, the container turnover optimization algorithm, the unpacked container quantity optimization algorithm and the box type identification optimization algorithm to the loading solution process, fully considering the influencing factors existing in the assembly process of different special ships, and considering the solution of the whole ship loading from the perspective of the overall container loading balance of the special ship, thereby providing an optimization solution for the research on the container loading problem of special ships. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0075] Figure 1 It is a flow chart of the containerized loading method of the special pulp ship of the present invention;

[0076] Figure 2 It is a flow chart of the intelligent loading algorithm adapting the ship type attributes and cargo loading attributes in the containerized loading method of the pulp special ship of the present invention;

[0077] Figure 3 It is a flow chart of the packing algorithm in the containerized loading method of the special pulp ship of the present invention;

[0078] Figure 4 It is a flow chart of an optimization algorithm for the container turnover amount in the containerized loading method of a special pulp ship of the present invention;

[0079] Figure 5The present invention is a flow chart of an optimization algorithm for the unpacked volume in the containerized loading method for a special pulp ship. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0081] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0082] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0083] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0084] Example 1

[0085] See also Figure 1 The embodiment of the present invention discloses a containerized loading method for a special pulp ship, comprising:

[0086] S1: pre-configure the loading constraints and loading preferences according to manual experience, and formulate the task sorting strategy according to the loading preferences;

[0087] S2: Adapt the intelligent loading algorithm to the ship type attributes and the cargo loading attributes based on the loading task, and convert the ship data and task data into a unified format for independent packaging to provide to the intelligent loading algorithm for data identification and reading. The intelligent loading algorithm includes a packing algorithm, a box turnover optimization algorithm, an unpacked box optimization algorithm, and a box type identification optimization algorithm;

[0088] S3: Setting the optimization objectives and corresponding weights of the stowage task, wherein the optimization objectives include: ① ensuring that the number of unpacked containers is minimized; ② ensuring that the weighted mean of the number of overturned containers in the port of origin and the port of destination is minimized; ③ ensuring that the number of mixed layers of containers in different ports of destination is minimized;

[0089] S4: the packing algorithm is used to cyclically solve the loading schemes of multiple loading tasks. If a loading scheme feasible solution that meets the optimization target of the container turnover quantity exists in multiple cyclic solving processes, the feasible solution is recorded and the optimization target ③ is cyclically optimized based on the feasible solution by the packing algorithm. The target loading scheme is updated and recorded, and the process is skipped to step S7. If a loading scheme feasible solution cannot be generated under the condition of meeting the optimization target of the container turnover quantity in multiple cyclic solving processes, the process is skipped to step S5.

[0090] S5: the loading schemes of multiple loading tasks are solved cyclically by using the container turnover optimization algorithm. If a loading scheme feasible solution that satisfies all loading tasks exists in multiple cyclic solution processes, the feasible solution is recorded and the optimization target ② and the optimization target ③ are weightedly optimized on the basis of the feasible solution by using the container turnover optimization algorithm. The target loading scheme is updated and recorded, and the process is skipped to step S7. If the multiple cyclic solution processes cannot satisfy the loading scheme feasible solution that is not optimized for the container turnover quantity under the condition of satisfying the container turnover optimization target, the process is skipped to step S6.

[0091] S6: using the unloaded quantity optimization algorithm to cyclically solve the loading schemes of multiple loading tasks, recording the current solution, sequentially weightedly optimizing the optimization target ①, the optimization target ② and the optimization target ③ through the unloaded quantity optimization algorithm, and updating and recording the target loading scheme;

[0092] S7: Generate a special ship stowage diagram according to the target stowage plan, and call the stowage file in JSON format output by the stowage diagram, wherein the stowage information of all containers of the target stowage plan is recorded in the stowage file.

[0093] In an optional embodiment, the loading constraints preconfigured according to manual experience include primary loading constraints and secondary loading constraints, the primary loading constraints include: stack height limit, weight limit, same width of containers in the same stack, same height of containers in the same layer, bay capacity limit, container location priority constraint, container same-slot matching constraint; the secondary loading constraints include: standard containers are not mixed with extra-wide containers, frame containers are loaded in the cabin, new energy containers are loaded outside the warehouse, standard containers are loaded on the upper cover of the frame containers, and special frame container loading constraints.

[0094] It should be noted that the first-level loading constraints are general loading constraints, including ① stack height and weight restrictions; ② the same width of containers in the same stack; ③ the same height of containers on the same layer (this constraint can be relaxed for the top layer of each shell); ④ shell capacity restrictions; ⑤ 20-foot container position priority: some special shells are given priority, followed by the spaces in the cabin and on the deck that can only accommodate 20-foot containers, and finally the feasible spaces on the deck; ⑥ matching of containers and slot types, where the first-level containers correspond to containers within the 20-foot range.

[0095] Furthermore, the secondary loading constraints are special loading constraints, including ① standard containers and extra-wide containers cannot be mixed; ② frame containers are loaded in the cabin (except for special 40FR frame containers); ③ new energy containers cannot be loaded in certain cabins; ④ a layer of ordinary container must be covered on the frame container; ⑤ special loading requirements for 40FR frame containers (special 40FR frame containers with overflowing cargo can only be placed on the top layer of the bay, and one box may occupy multiple bays).

[0096] In an optional embodiment, the loading preferences preconfigured based on manual experience include: ① containers with the same destination port are loaded on the same layer; ② non-mixed loading preference in the same cabin; ③ the destination port of the upper container is closer than the destination port of the lower container; ④ preference for ship loading volume; ⑤ manual loading preference;

[0097] The task sorting strategy formulated according to the loading preference includes: ① sorting the initial assembly tasks in the order of departure ports from near to far and destination ports from far to near; ② sorting the initial assembly tasks in the order of destination ports from far to near and departure ports from near to far; ③ giving priority to special frame containers, and sorting the initial assembly tasks in the order of departure ports from near to far and destination ports from far to near; ④ giving priority to special frame containers, and sorting the initial assembly tasks in the order of destination ports from far to near and departure ports from near to far.

[0098] It should be noted that the loading preferences include: ① loading containers of the same destination port on the same layer as much as possible; ② moving the hatch covers as little as possible during loading and unloading at the same port: as little mixed loading as possible in the same cabin; ③ as little container unloading as possible: the destination port of the upper container in the same cabin should be as close as possible to the destination port of the container in the cabin (the factor of moving the hatch covers during loading and unloading should also be considered); at the same bay, the destination port of the upper container should be as close as possible to the destination port of the lower container; ④ the ship's loading volume should be as large as possible to complete the loading of all containers; ⑤ satisfying other manual loading preferences, that is, adjusting according to manual experience. The loading preferences are not restricted here, that is, the constraints that meet the manual loading preferences during the loading process can be defined in the loading preferences through the algorithm.

[0099] In an optional embodiment, adapting the intelligent loading algorithm to the ship type attributes includes:

[0100] S21: Divide the ship into multiple compartments horizontally and vertically into deck positions and cabin positions, and number the deck positions and cabin positions;

[0101] S22: dividing the container slots into primary container slots, secondary container slots and tertiary container slots by using the primary size, secondary size and tertiary size container reference units, matching the primary container slots with the secondary container slots and the tertiary container slots, and distinguishing the container slots of standard containers and extra-wide containers;

[0102] S23: All slots are marked with the three-dimensional coordinates of shells, stacks, and layers, and additional marking is used to determine whether there is a container in the slot;

[0103] S24: Mark the bay position attributes according to the bay coordinates of the three-dimensional coordinates, determine whether the corresponding bay position is suitable for assembling special containers through the bay position attributes, and limit the stacking height and stacking weight of the container in units of stacks. The bay position attributes include bay position size, bay position position, and the cabin to which the bay position belongs.

[0104] It should be noted that before executing ship stowage, in order to facilitate the subsequent data maintenance, the initial stage of reading and processing ship data and task data is to set the ship data and task data into a unified format and encapsulate them independently to facilitate the algorithm to read the data. At the same time, in order to make the stowage algorithm adapt to various ship types, the following adjustments need to be made: ① The ship is divided into multiple cabins horizontally and vertically into two parts: on-deck and in-cabin. The bays on the deck and in the cabin are numbered respectively; ② Further, the 20-foot container, 40-foot container and 48-foot container are used as the reference units to divide the container slots, match the 20-foot container with the 40-foot container and the 48-foot container slots, and distinguish between standard containers and extra-wide container slots; ③ Each slot is characterized by the three-dimensional coordinates of (shell, stack, layer), and the existence of the slot is additionally marked; ④ In shells, (shell attributes) mark the shell size, corresponding shell position, and the cabin to which it belongs, and mark whether the shell can be loaded with special containers; ⑤ In stacks, mark the stack height and stack weight limits.

[0105] In an optional embodiment, adapting the intelligent loading algorithm to the cargo loading attributes based on the loading task includes:

[0106] S25: Using the loading task as a task unit, marking the departure port, destination port, container weight, container type and special container tasks associated with the loading task through an intelligent loading algorithm;

[0107] S26: marking the bays that can be loaded currently through the intelligent loading algorithm;

[0108] S27: Marking the cargo loaded on the deck and in-hold positions through an intelligent loading algorithm.

[0109] Furthermore, in order to adapt the algorithm to various cargo stowage forms, the algorithm is processed as follows: ① Taking the task as the unit, mark the departure port, destination port, weight, container type, and whether it is an extra-wide 40FR container, virtual container, new energy container and other special cases. ② Mark the bays that can be currently stowed (to ensure that the stowage results are manually controllable) ③ Mark the cargo that has been stowed on the deck and in the cabin (to achieve collaborative stowage between manual operation and intelligent algorithm).

[0110] In an optional embodiment, the packing algorithm sorts the loading tasks according to the task sorting strategy ①, and the steps of the packing algorithm include:

[0111] S41: Obtain loading task;

[0112] S42: The stowage task generates a loadable bay for the current task based on the conditions of satisfying the special loading constraint and the container turning constraint;

[0113] S43: using a roulette mechanism to select a loading bay from the available loading bays on the premise that the loading preference ① and the loading preference ② are satisfied;

[0114] S44: packing the containers in the loading task layer by layer according to the selected packing positions under the first-level loading constraint;

[0115] S45: Repeat steps S42-S44 until the number of unloaded containers reaches zero, and obtain the next loading task;

[0116] S46: Repeat steps S42-S45 until all loading tasks are completed.

[0117] In an optional embodiment, the container turnover optimization algorithm performs a cyclic solution to the loading schemes of multiple loading tasks, and the steps include:

[0118] S51: Generate a corresponding loading task sequence according to the task sequencing strategy;

[0119] S52: Obtaining loading tasks according to the order of the loading task sequence;

[0120] S53: generating the available loading bays for the current stowage task based on the no-turnover constraint and the secondary loading constraint. If there are feasible loading bays in the stowage task, jump to step S55, otherwise continue to execute step S54;

[0121] S54: Generate the available loading bays for the current loading task based on the secondary loading constraint and the container turning constraint. If there are feasible loading bays in the loading task, continue to execute step S55. Otherwise, jump to step S52 to iterate the loading tasks of the current loading task sequence for multiple times. If no feasible solution can be generated, jump to step S59 to execute the next loading task sequence.

[0122] S55: Selecting a loading bay from the available loading bays in the current loading task sequence through a roulette mechanism under the conditions of satisfying loading preference ①, loading preference ②, and loading preference ③;

[0123] S56: packing containers layer by layer for the loading tasks of the current loading task sequence according to the selected packing positions under the first-level loading constraint;

[0124] S57: Repeat steps S52-S56 until the number of unloaded containers is zero, and obtain the next loading task in the current loading task sequence;

[0125] S58: Repeat steps S52-S57 until all loading tasks under the current loading task sequence are completed, and all loading task records are generated into the current loading task sequence to achieve the optimal loading plan;

[0126] S59: Repeat steps S52-S58 until the optimal loading scheme under all loading task sequences is solved, and output the target loading scheme according to the optimal loading scheme.

[0127] In an optional embodiment, the unpacked quantity optimization algorithm is used to cyclically solve the loading schemes of multiple loading tasks, and the steps of the unpacked quantity optimization algorithm include:

[0128] S61: Generate a corresponding loading task sequence according to the task sequencing strategy;

[0129] S62: Obtaining loading tasks according to the order of the loading task sequence;

[0130] S63: Generate the available loading bays for the current stowage task based on the no-turnover constraint and the secondary loading constraint. If there are feasible loading bays in the stowage task, jump to step S65, otherwise continue to execute step S64;

[0131] S64: Generate the available loading bays for the current loading task based on the secondary loading constraint and the container turning constraint. If there are feasible loading bays in the loading task, continue to execute step S65. Otherwise, jump to step S62 to perform multiple iterations of the loading tasks of the current loading task sequence. If no feasible solution can be generated, jump to step S69 to execute the next loading task sequence.

[0132] S65: for the available loading bays in the stowage task under the current loading task sequence, a loading bay is selected through a roulette mechanism based on the conditions of satisfying loading preference ①, loading preference ② and loading preference ③;

[0133] S66: packing containers layer by layer for the loading tasks of the current loading task sequence according to the selected loading bays under the first-level loading constraint;

[0134] S67: Repeat steps S62-S66 until the number of unloaded containers is zero, and obtain the next loading task in the current loading task sequence;

[0135] S68: Repeat steps S62-S67 to traverse all loading tasks in the current loading task sequence, and record the preferred loading solutions generated by all loading tasks in the current loading task sequence;

[0136] S69: Repeat steps S62-S68 until the optimal loading scheme under all loading task sequences is solved, and output the target loading scheme according to the optimal loading scheme.

[0137] In an optional embodiment, the box type recognition optimization algorithm includes primary size box type recognition, secondary size box type recognition and tertiary size box type recognition, and the primary size box type recognition includes:

[0138] The positions of the first-level size boxes are prioritized, which are the first-level box positions in the cabin, the first-level box positions on the deck, the non-first-level box positions on the deck, and the non-first-level box positions in the cabin. The first-level size boxes are prioritized and the corresponding positions are selected for packing through the box packing position selection function and identification rules;

[0139] The identification rule traverses the bays on the ship to determine whether the bay is an odd bay for which there is no corresponding even bay. If so, the odd bay is added to the pre-packing list of the first-level size box according to the priority of the position; it is determined whether there is a new odd bay in the original odd bay in the pre-packing list that can form a new even bay with the original odd bay. If not, the original odd bay in the pre-packing list is retained. If there is a new odd bay, it is determined whether the position distribution of the new odd bay that forms the new even bay with the original odd bay is the same as the position distribution of the original odd bay on the ship. If the position distribution is different, the original odd bay is saved in the pre-packing list. If the position distribution is the same, the original odd bay is removed from the pre-packing list.

[0140] It should be further explained that, according to manual experience, the priority of the loading position of 20-foot containers (first-size containers) is as follows: Priority 1: the space in the cabin that gives priority to loading 20-foot containers (first-size containers); Priority 2: the space on the deck that gives priority to loading 20-foot containers (first-size containers); Priority 3: other spaces on the deck; Priority 4: other spaces in the cabin. The above priority processing is executed through the function of the "genCanBay" algorithm. First, for different ships, the bays in the cabin that can be loaded with 20-foot containers are identified, which are recorded as Prefer_20_Cabin_Bay, and the bays on the deck that can be loaded with 20-foot containers are identified, which are recorded as Prefer_20_Deck_Bay. The identification rule is: if another odd bay that constitutes the same even bay as a certain odd bay is inconsistent with the space distribution of the odd bay, it will be recorded as the bay that can be loaded with 20-foot containers first.

[0141] Furthermore, taking the identification of bays on the deck that can be loaded with 20-foot containers as an example, the bays in the cabin and on the deck that can be loaded with the current task are generated and recorded in Can_Cabin_Bay and Can_Deck_Bay respectively. It is determined whether the current task to be loaded is a 20-foot container. If it is a 20-foot container, the following selection mechanism is triggered to return the bay set that can be loaded with the current task. Through the selection mechanism, it can be ensured that the bays in the cabin that are loaded with 20-foot containers are selected first, otherwise the bays on the deck that are loaded with 20-foot containers are selected first, and then other bays on the deck are selected, and finally other bays in the cabin are selected.

[0142] In an optional embodiment, the secondary size box type identification includes:

[0143] Identify the special ship type characteristics of the ship, and determine whether the bottom layer of the last even-numbered bay in the ship's cabin with special ship type characteristics is loaded with second-size containers according to the special ship type constraints. If so, record the current number of containers and cumulatively add second-size containers to the last even-numbered bays until the bottom layer of the last even-numbered bay in the cabin is filled with second-size containers. Traverse all loading tasks and call the packing function to perform the second-size container loading operation until the special ship type constraints are met.

[0144] It should be noted that the second-level size boxes are 40-foot HQ boxes and HC boxes. Due to the shape restrictions of some special ships, the last even-numbered cabin can only be flattened by laying 9 HQ or HC high boxes on the bottom layer, so that other boxes can be loaded on top to ensure the packing rate. Therefore, according to manual experience, when packing, the bottom layer of the last even-numbered cabin of this type of ship will be filled with HQ or HC high boxes first.

[0145] Furthermore, based on manual experience, the packing process is added to the algorithm rules to identify ships with the above characteristics, and HQ and HC high boxes are preferentially loaded on the bottom layer of the even-numbered shells in the last hold of such ships. The steps are as follows: determine whether it is a ship with the above characteristics; determine whether the bottom layer of the last even-numbered shell has been manually loaded with high boxes (HQ and HC high boxes); record the number of high boxes that need to be loaded on the bottom layer; stop when the bottom layer is filled with high boxes; traverse each task; if the current task is HQ or HC high boxes, call the packing function and perform the loading operation; when the bottom layer is full, stop packing, and continue to perform the next loading task until all the bottom layers are full, then stop packing.

[0146] In an optional embodiment, the three-level size box type identification includes:

[0147] The third-level size boxes and other box types are marked and divided into extra-wide boxes and standard boxes and saved in four-dimensional variables. The first layer of the four-dimensional variables represents the three-dimensional coordinate box positions of standard boxes, and the second layer represents the three-dimensional coordinate box positions of extra-wide boxes. In the process of generating the available box positions for the current task by the intelligent loading algorithm, standard boxes and extra-wide boxes are identified, and the available box positions are divided into standard box positions and extra-wide box positions for loading containers. The standard box positions and extra-wide box positions constrain the containers loaded on the box positions, and only containers of the same box type matching the box positions are loaded.

[0148] It should be noted that there are no fixed slots in the cabin of a special ship when transporting containers, so the slots on each layer can be divided manually according to the width of the container. Containers transported by special ships are of many different types and sizes, but they can be roughly divided into two categories in terms of width, standard containers and extra-wide containers. The results of dividing the slots for standard containers and extra-wide containers are different (compared to extra-wide containers, each layer can hold more standard containers), and extra-wide containers and standard containers cannot be loaded in the same bay.

[0149] Furthermore, the loading requirements for different types of containers are processed through an algorithm, and the slots for extra-wide containers and standard containers are divided and recorded respectively, and stored in CABIN_SLOT_STATE (four-dimensional variable). The first layer represents the three-dimensional slot identification of standard containers, and the second layer represents the three-dimensional slot identification of extra-wide containers. Different types of containers are marked by CON_WIDTH_TYPE. If CON_WIDTH_TYPE is 1, it indicates a standard container, and if CON_WIDTH_TYPE is 2, it indicates an extra-wide container. During the packing process, standard containers are matched with standard container slots, and extra-wide containers are matched with extra-wide container slots. In addition, in order to meet the requirement that extra-wide containers and standard containers cannot be loaded in the same slot, the following judgments are made when generating feasible slots:

[0150] if CABIN_TYPE[bay]! =-1and CABIN_TYPE[bay]! =containerWidthType:

[0151] continue

[0152] In the above rules, CABIN_TYPE[bay] indicates the width type of the container already loaded in the bay, containerWidthType indicates the width type of the container currently to be loaded, and CABIN_TYPE[bay]!=-1 indicates that a certain type of container has already been loaded in the bay. The above rules ensure that if a bay has already been loaded with a container of a certain width type, then the bay cannot continue to load containers of other width types.

[0153] In an optional embodiment, the loading preference preconfigured according to manual experience also includes: containers belonging to the same port of departure and port of destination are placed in non-adjacent holds of the ship, adjacent prohibited hold pairs in the ship are defined by an algorithm and saved in prohibited hold pair variables, and containers with the same port of departure and port of destination in the target loading task are traversed according to the prohibited hold pair variables to see whether there are containers placed in adjacent holds, and if so, the optional feasible bays stored in the prohibited hold pair variables are replaced to meet the loading preference of placing containers with the same port of departure and port of destination in non-adjacent holds of the ship.

[0154] It should be noted that during the actual loading and unloading operations of special ships, when loading and unloading containers in a certain hold, it is first necessary to move the hatch cover corresponding to the hold to the hatch cover of the adjacent hold. Therefore, in order to avoid the need to move the hatch cover multiple times when loading and unloading operations at a certain port, the goods at the same loading and unloading port should not be concentrated in the same hold, but should be loaded at least one hold apart, so that at least two cranes can operate at the same time at the unloading port, saving port time and thus improving loading and unloading efficiency. According to manual experience, we will try our best to ensure that the boxes at the same loading and unloading port are not placed in adjacent hold.

[0155] Furthermore, the stowage requirement that boxes of the same loading and unloading port should not be placed in adjacent prohibited cabins as much as possible is set by the algorithm as follows: First, define the "adjacent prohibited cabin pairs" of each special ship and store them in the variable CABIN_FORBID_BAY, which represents the bays in the prohibited cabins of the cabin where the current bay is located. After generating a feasible bay in the cabin, that is, obtaining Can_Cabin_Bay, it is necessary to select a bay position for actual loading in Can_Cabin_Bay. In the selection process, the bay selection rule is added to calculate temp_Can_Cabin_Bay, which is used to store the feasible bays that can be selected without multiple moves of the hatch cover. If the length of temp_Can_Cabin_Bay is greater than 0, it means that there is a feasible bay without multiple moves of the hatch cover, then Can_Cabin_Bay is replaced with temp_Can_Cabin_Bay, and then the subsequent bay position selection is performed, which can try to ensure that the boxes of the same loading and unloading port are not placed in adjacent cabins.

[0156] The present invention pre-configures loading constraints and loading preferences according to artificial experience, and formulates a task sorting strategy according to the loading preferences to meet the requirements of flexibility and versatility of container loading processes of different special ships; the present invention adapts the intelligent loading algorithm to the loading ship type attributes and the cargo loading attributes based on the loading task, and converts the ship data and the task data into a unified format for independent packaging to provide to the intelligent loading algorithm for data identification and reading, and converts the algorithm program into an algorithm program through artificial experience and nests it in the overall framework of the algorithm, which can improve the versatility and efficiency of the algorithm and ensure that the algorithm can output a high-quality special ship loading plan that meets the loading requirements. The present invention sets the optimization target and corresponding weight of the loading task, and adds the packing algorithm, the box turnover optimization algorithm, the unpacked box optimization algorithm and the box type identification optimization algorithm to the loading plan solution process, fully considers the influencing factors of different special ships in the assembly process, and considers the solution of the whole ship loading from the overall container loading balance of the special ship, and provides an optimization solution for the research of the container loading problem of special ships.

[0157] The second aspect of the present invention discloses a containerized loading equipment for a special pulp ship, comprising:

[0158] at least one processor, and

[0159] a memory communicatively connected to the at least one processor; wherein,

[0160] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the containerized loading method for a special pulp ship as disclosed in any one of the first aspects of the present invention.

[0161] The computer device may be a terminal, and the computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a containerized loading method for a special pulp ship is implemented. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0162] The third aspect of the present invention discloses a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the containerized loading method for a special pulp ship as disclosed in any one of the first aspect of the present invention.

[0163] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the containerized loading method of the pulp special ship as described above. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0164] Alternatively, if the above modules of the present invention are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, RAM, ROM, magnetic disks or optical disks.

[0165] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A containerized loading method for a special pulp ship, characterized in that: The method comprises: S1: pre-configure the loading constraints and loading preferences according to manual experience, and formulate the task sorting strategy according to the loading preferences; S2: Adapt the intelligent loading algorithm to the ship type attributes and the cargo loading attributes based on the loading task, and convert the ship data and task data into a unified format for independent packaging to provide to the intelligent loading algorithm for data identification and reading. The intelligent loading algorithm includes a packing algorithm, a box turnover optimization algorithm, an unpacked box optimization algorithm, and a box type identification optimization algorithm; S3: Setting the optimization objectives and corresponding weights of the stowage task, wherein the optimization objectives include: ① ensuring that the number of unpacked containers is minimized; ② ensuring that the weighted mean of the number of overturned containers in the port of origin and the port of destination is minimized; ③ ensuring that the number of mixed layers of containers in different ports of destination is minimized; S4: the packing algorithm is used to cyclically solve the loading schemes of multiple loading tasks. If a loading scheme feasible solution that meets the optimization target of the container turnover quantity exists in multiple cyclic solving processes, the feasible solution is recorded and the optimization target ③ is cyclically optimized based on the feasible solution by the packing algorithm. The target loading scheme is updated and recorded, and the process is skipped to step S7. If a loading scheme feasible solution cannot be generated under the condition of meeting the optimization target of the container turnover quantity in multiple cyclic solving processes, the process is skipped to step S5. S5: the loading schemes of multiple loading tasks are solved cyclically by using the container turnover optimization algorithm. If a loading scheme feasible solution that satisfies all loading tasks exists in multiple cyclic solution processes, the feasible solution is recorded and the optimization target ② and the optimization target ③ are weightedly optimized on the basis of the feasible solution by using the container turnover optimization algorithm. The target loading scheme is updated and recorded, and the process is skipped to step S7. If the multiple cyclic solution processes cannot satisfy the loading scheme feasible solution that is not optimized for the container turnover quantity under the condition of satisfying the container turnover optimization target, the process is skipped to step S6. S6: using the unloaded quantity optimization algorithm to cyclically solve the loading schemes of multiple loading tasks, recording the current solution, sequentially weightedly optimizing the optimization target ①, the optimization target ② and the optimization target ③ through the unloaded quantity optimization algorithm, and updating and recording the target loading scheme; S7: Generate a special ship stowage diagram according to the target stowage plan, and call the stowage file in JSON format output by the stowage diagram, wherein the stowage information of all containers of the target stowage plan is recorded in the stowage file.

2. The containerized loading method for a special pulp ship according to claim 1, characterized in that: The loading constraints preconfigured according to manual experience include primary loading constraints and secondary loading constraints. The primary loading constraints include: stack height limit, weight limit, same width of containers in the same stack, same height of containers in the same layer, bay capacity limit, container position priority constraint, and container same-slot matching constraint; the secondary loading constraints include: standard containers are not mixed with extra-wide containers, frame containers are loaded in the cabin, new energy containers are loaded outside the warehouse, standard containers are loaded on the upper cover of frame containers, and special frame container loading constraints.

3. The containerized loading method for a special pulp ship according to claim 2, characterized in that: The loading preferences preconfigured based on manual experience include: ① containers with the same destination port are loaded on the same layer; ② non-mixed loading preference in the same cabin; ③ the destination port of the upper container is closer than the destination port of the lower container; ④ preference for ship loading volume; ⑤ preference for manual loading; The task sorting strategy formulated according to the loading preference includes: ① sorting the initial assembly tasks in the order of departure ports from near to far and destination ports from far to near; ② sorting the initial assembly tasks in the order of destination ports from far to near and departure ports from near to far; ③ giving priority to special frame containers, and sorting the initial assembly tasks in the order of departure ports from near to far and destination ports from far to near; ④ giving priority to special frame containers, and sorting the initial assembly tasks in the order of destination ports from far to near and departure ports from near to far.

4. The containerized loading method for a special pulp ship according to claim 3, characterized in that: Adapting the intelligent loading algorithm to the ship type attributes includes: S21: Divide the ship into multiple compartments horizontally and vertically into deck positions and cabin positions, and number the deck positions and cabin positions; S22: dividing the container slots into primary container slots, secondary container slots and tertiary container slots by using the primary size, secondary size and tertiary size container reference units, matching the primary container slots with the secondary container slots and the tertiary container slots, and distinguishing the container slots of standard containers and extra-wide containers; S23: All slots are marked with the three-dimensional coordinates of shells, stacks, and layers, and additional marking is used to determine whether there is a container in the slot; S24: Mark the bay position attributes according to the bay coordinates of the three-dimensional coordinates, determine whether the corresponding bay position is suitable for assembling special containers through the bay position attributes, and limit the stacking height and stacking weight of the container in units of stacks. The bay position attributes include bay position size, bay position position, and the cabin to which the bay position belongs.

5. The containerized loading method for a special pulp ship according to claim 4, characterized in that: Adapting the intelligent loading algorithm to the cargo loading attributes based on the loading task includes: S25: Using the loading task as a task unit, marking the departure port, destination port, container weight, container type and special container tasks associated with the loading task through an intelligent loading algorithm; S26: marking the bays that can be loaded currently through the intelligent loading algorithm; S27: Marking the cargo loaded on the deck and in-hold positions through an intelligent loading algorithm.

6. The containerized loading method for a special pulp ship according to claim 5, characterized in that: The packing algorithm sorts the loading tasks according to the task sorting strategy ①. The steps of the packing algorithm include: S41: Obtain loading task; S42: The stowage task generates a loadable bay for the current task based on the conditions of satisfying the special loading constraint and the container turning constraint; S43: using a roulette mechanism to select a loading bay from the available loading bays on the premise that the loading preference ① and the loading preference ② are satisfied; S44: packing the containers in the loading task layer by layer according to the selected packing positions under the first-level loading constraint; S45: Repeat steps S42-S44 until the number of unloaded containers reaches zero, and obtain the next loading task; S46: Repeat steps S42-S45 until all loading tasks are completed.

7. The containerized loading method for a special pulp ship according to claim 6, characterized in that: The container turnover optimization algorithm cyclically solves the loading schemes of multiple loading tasks, and the steps include: S51: Generate a corresponding loading task sequence according to the task sequencing strategy; S52: Obtaining loading tasks according to the order of the loading task sequence; S53: generating the available loading bays for the current stowage task based on the no-turnover constraint and the secondary loading constraint. If there are feasible loading bays in the stowage task, jump to step S55, otherwise continue to execute step S54; S54: Generate the available loading bays for the current loading task based on the secondary loading constraint and the container turning constraint. If there are feasible loading bays in the loading task, continue to execute step S55. Otherwise, jump to step S52 to iterate the loading tasks of the current loading task sequence for multiple times. If no feasible solution can be generated, jump to step S59 to execute the next loading task sequence. S55: Selecting a loading bay from the available loading bays in the current loading task sequence through a roulette mechanism under the conditions of satisfying loading preference ①, loading preference ②, and loading preference ③; S56: packing containers layer by layer for the loading tasks of the current loading task sequence according to the selected packing positions under the first-level loading constraint; S57: Repeat steps S52-S56 until the number of unloaded containers is zero, and obtain the next loading task in the current loading task sequence; S58: Repeat steps S52-S57 until all loading tasks under the current loading task sequence are completed, and all loading task records are generated into the current loading task sequence to achieve the optimal loading plan; S59: Repeat steps S52-S58 until the optimal loading scheme under all loading task sequences is solved, and output the target loading scheme according to the optimal loading scheme.

8. The containerized loading method for a special pulp ship according to claim 7, characterized in that: The unpacked quantity optimization algorithm is used to cyclically solve the loading schemes of multiple loading tasks. The steps of the unpacked quantity optimization algorithm include: S61: Generate a corresponding loading task sequence according to the task sequencing strategy; S62: Obtaining loading tasks according to the order of the loading task sequence; S63: Generate the available loading bays for the current stowage task based on the no-turnover constraint and the secondary loading constraint. If there are feasible loading bays in the stowage task, jump to step S65, otherwise continue to execute step S64; S64: Generate the available loading bays for the current loading task based on the secondary loading constraint and the container turning constraint. If there are feasible loading bays in the loading task, continue to execute step S65. Otherwise, jump to step S62 to perform multiple iterations of the loading tasks of the current loading task sequence. If no feasible solution can be generated, jump to step S69 to execute the next loading task sequence. S65: for the available loading bays in the stowage task under the current loading task sequence, a loading bay is selected through a roulette mechanism based on the conditions of satisfying loading preference ①, loading preference ② and loading preference ③; S66: packing containers layer by layer for the loading tasks of the current loading task sequence according to the selected loading bays under the first-level loading constraint; S67: Repeat steps S62-S66 until the number of unloaded containers is zero, and obtain the next loading task in the current loading task sequence; S68: Repeat steps S62-S67 to traverse all loading tasks in the current loading task sequence, and record the preferred loading solutions generated by all loading tasks in the current loading task sequence; S69: Repeat steps S62-S68 until the optimal loading scheme under all loading task sequences is solved, and output the target loading scheme according to the optimal loading scheme.

9. The containerized loading method for a special pulp ship according to claim 8, characterized in that: The box type recognition optimization algorithm includes first-level box type recognition, second-level box type recognition and third-level box type recognition. The first-level box type recognition includes: The positions of the first-level size boxes are prioritized, which are the first-level box positions in the cabin, the first-level box positions on the deck, the non-first-level box positions on the deck, and the non-first-level box positions in the cabin. The first-level size boxes are prioritized and the corresponding positions are selected for packing through the box packing position selection function and identification rules; The identification rule traverses the bays on the ship to determine whether the bay is an odd bay for which there is no corresponding even bay. If so, the odd bay is added to the pre-packing list of the first-level size box according to the priority of the position; it is determined whether there is a new odd bay in the original odd bay in the pre-packing list that can form a new even bay with the original odd bay. If not, the original odd bay in the pre-packing list is retained. If there is a new odd bay, it is determined whether the position distribution of the new odd bay that forms the new even bay with the original odd bay is the same as the position distribution of the original odd bay on the ship. If the position distribution is different, the original odd bay is saved in the pre-packing list. If the position distribution is the same, the original odd bay is removed from the pre-packing list.

10. The containerized loading method for a special pulp ship according to claim 9, characterized in that: The secondary size box category identification includes: Identify the special ship type characteristics of the ship, and determine whether the bottom layer of the last even-numbered bay in the ship's cabin with special ship type characteristics is loaded with second-size containers according to the special ship type constraints. If so, record the current number of containers and cumulatively add second-size containers to the last even-numbered bays until the bottom layer of the last even-numbered bay in the cabin is filled with second-size containers. Traverse all loading tasks and call the packing function to perform the second-size container loading operation until the special ship type constraints are met.

11. The containerized loading method for a special pulp ship according to claim 10, characterized in that: The three-level size box classification includes: The third-level size boxes and other box types are marked and divided into extra-wide boxes and standard boxes and saved in four-dimensional variables. The first layer of the four-dimensional variables represents the three-dimensional coordinate box positions of standard boxes, and the second layer represents the three-dimensional coordinate box positions of extra-wide boxes. In the process of generating the available box positions for the current task by the intelligent loading algorithm, standard boxes and extra-wide boxes are identified, and the available box positions are divided into standard box positions and extra-wide box positions for loading containers. The standard box positions and extra-wide box positions constrain the containers loaded on the box positions, and only containers of the same box type matching the box positions are loaded.

12. The containerized loading method for a special pulp ship according to claim 11, characterized in that: The loading preference preconfigured according to manual experience also includes: containers belonging to the same port of departure and port of destination are placed in non-adjacent holds of the ship, adjacent prohibited hold pairs in the ship are defined by an algorithm and saved in prohibited hold pair variables, and containers with the same port of departure and port of destination in the target loading task are traversed according to the prohibited hold pair variables to see whether there are containers placed in adjacent holds, and if so, the optional feasible bays stored in the prohibited hold pair variables are replaced to meet the loading preference of placing containers with the same port of departure and port of destination in non-adjacent holds of the ship.

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