Production scheduling forecasting method, device, electronic device and storage medium for dock

Abstract

The present invention discloses a production scheduling prediction method, device, electronic device and storage medium for a dock, and relates to the field of production technology; wherein the method comprises: obtaining historical production scheduling information of the dock; inputting the historical production scheduling information into a preset berthing and unberthing planning model and a preset bucket wheel machine task allocation planning model respectively, to obtain ship berthing planning information and bucket wheel machine planning information; inputting the ship berthing planning information and bucket wheel machine planning information into a preset simulation model, to obtain a dock resource evolution result; according to the dock resource evolution result, determining an evaluation index value corresponding to the dock resource evolution result; judging whether the evaluation index value is within a preset range; when judging that the evaluation index value is not within the preset range, adjusting the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model; through the present invention, the problem of low resource allocation utilization rate of the dock in the prior art is solved, and the resource allocation utilization rate of the dock is improved.

Description

Technical Field

[0001] The present invention relates to the field of production technology, and in particular to a method, device, electronic device and storage medium for predicting production schedules at a dock. Background Art

[0002] With the development of economy, the production level of the terminal is gradually improving, and the complexity of production scheduling is also increasing. The terminal has a variety of resources, including berths, yards, loading and unloading equipment, manpower and energy, etc. At present, the allocation of various resources of the terminal basically depends on the scheduling experience of the central control dispatcher. The manual scheduling forecast cannot fully consider various limiting factors, and cannot meet the complex and changeable resource allocation situation in time, which easily leads to the problem of low resource allocation utilization of the terminal.

[0003] Currently, no effective solution has been proposed for the problem of low resource allocation utilization rate at docks in related technologies. Summary of the invention

[0004] The embodiments of the present application provide a method, device, electronic device and storage medium for predicting production schedules at a terminal, so as to at least solve the problem of low resource allocation utilization rate at a terminal in the related art.

[0005] In a first aspect, an embodiment of the present application provides a method for predicting production schedule of a terminal, including:

[0006] S1, obtain the historical production scheduling information of the terminal;

[0007] S2, inputting the historical production scheduling information into a preset berthing and unberthing planning model and a preset bucket wheel machine task allocation planning model respectively, to obtain ship berthing planning information and bucket wheel machine planning information;

[0008] S3, inputting the ship berthing planning information and the bucket wheel machine planning information into a preset simulation model to obtain a dock resource evolution result;

[0009] S4, determining an evaluation index value corresponding to the terminal resource evolution result according to the terminal resource evolution result;

[0010] S5, determining whether the evaluation index value is within a preset range;

[0011] S6, when it is determined that the evaluation index value is not within the preset range, adjusting the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model.

[0012] Furthermore, the method further comprises:

[0013] The evolution result of the wharf resources is saved.

[0014] Furthermore, the ship berthing planning information and the bucket wheel machine planning information are input into a preset simulation model, and the terminal resource evolution results obtained include:

[0015] The operation process of the wharf is simulated by the preset simulation model based on the ship berthing planning information and the bucket wheel machine planning information to obtain a simulation evolution result;

[0016] According to the simulation evolution result, the terminal resource evolution result is determined.

[0017] Furthermore, the simulation evolution result includes: cargo loading and unloading result; before determining the terminal resource evolution result according to the simulation evolution result, the method includes:

[0018] According to the simulation evolution result, judging whether the cargo loading and unloading result at each preset time satisfies the preset cargo loading and unloading result;

[0019] If yes, then determining the terminal resource evolution result according to the cargo loading and unloading result;

[0020] If not, the first user input information is obtained, and the cargo loading and unloading result is modified according to the first user input information, and the terminal resource evolution result is determined according to the modified cargo loading and unloading result.

[0021] Furthermore, the simulation evolution result includes: yard and mixed ore evolution results; before determining the terminal resource evolution result according to the simulation evolution result, the method includes:

[0022] Obtain the stockpile and mixed ore evolution results at each preset moment;

[0023] Update the ore mixing task table according to the stockpile and ore mixing evolution results at each preset moment;

[0024] According to the mixed ore task table, the terminal resource evolution result is determined.

[0025] Furthermore, after the step S5, the method further comprises:

[0026] When it is determined that the evaluation index value is within the preset range, the production scheduling task is performed according to the ship berthing planning information and the bucket wheel excavator planning information.

[0027] Furthermore, the step S6 comprises:

[0028] If it is determined that the evaluation index value is not within the preset range, obtaining second user input information;

[0029] According to the second user input information, the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel excavator task allocation planning model are adjusted.

[0030] In a second aspect, an embodiment of the present application provides a production scheduling prediction device for a dock, comprising:

[0031] The acquisition module is used to obtain the historical production scheduling information of the terminal;

[0032] A first input module is used to input the historical production scheduling information into a preset berthing and unberthing planning model and a preset bucket wheel machine task allocation planning model, respectively, to obtain ship berthing planning information and bucket wheel machine planning information;

[0033] A second input module is used to input the ship berthing planning information and the bucket wheel machine planning information into a preset simulation model to obtain a dock resource evolution result;

[0034] A determination module, used to determine the evaluation index value corresponding to the terminal resource evolution result according to the terminal resource evolution result;

[0035] A judgment module, used to judge whether the evaluation index value is within a preset range;

[0036] The adjustment module is used to adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model when it is determined that the evaluation index value is not within the preset range.

[0037] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the production scheduling forecasting method for a terminal as described in the first aspect above is implemented.

[0038] In a fourth aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the production scheduling forecasting method for a terminal as described in the first aspect above.

[0039] Compared with the related art, the production scheduling prediction method, device, electronic device and storage medium for the terminal provided in the embodiment of the present application obtain the historical production scheduling information of the terminal; input the historical production scheduling information into the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model respectively to obtain the ship berthing planning information and the bucket wheel machine planning information; input the ship berthing planning information and the bucket wheel machine planning information into the preset simulation model to obtain the terminal resource evolution result; according to the terminal resource evolution result, determine the evaluation index value corresponding to the terminal resource evolution result; judge whether the evaluation index value is within the preset range; when it is judged that the evaluation index value is not within the preset range, adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model, thereby realizing intelligent prediction and scheduling of the terminal, without relying on the production scheduling experience of the central control dispatcher for resource allocation, solving the problem of low resource allocation utilization rate of the terminal in the prior art, and improving the resource allocation utilization rate of the terminal.

[0040] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0042] Figure 1 It is a hardware structure block diagram of a terminal of the method for production scheduling prediction of a wharf according to an embodiment of the present invention;

[0043] Figure 2 is a flow chart of a method for predicting production schedules at a terminal according to an embodiment of the present application;

[0044] Figure 3 It is a structural block diagram of a production scheduling prediction device for a terminal according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] 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 this field without making creative work are within the scope of protection of the present application. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the contents disclosed in the present application, some changes such as design, manufacturing or production based on the technical contents disclosed in the present application are only conventional technical means, and should not be understood as insufficient contents disclosed in the present application.

[0046] 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.

[0047] 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 quantity limitation, and may indicate 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 means greater than or equal to two. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. The terms "first", "second", "third" and the like involved in the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects.

[0048] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. Taking running on a terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a terminal of a method for predicting production schedule of a terminal according to an embodiment of the present invention. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0049] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the production scheduling prediction method of the dock in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0050] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0051] This embodiment provides a method for predicting production schedule of a terminal. Figure 2 is a flow chart of a method for predicting production schedule of a terminal according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps:

[0052] S1, obtain the historical production scheduling information of the terminal.

[0053] In S1, the historical production scheduling information may include but is not limited to production scheduling demand task information, objective environment information, terminal static information, and terminal dynamic information.

[0054] Among them, the production scheduling demand task information, objective environment information, terminal static information, and terminal dynamic information specifically include the following information:

[0055] The production scheduling demand task information mainly includes the first-leg ship task, the second-leg ship task and the mixed ore task.

[0056] A ship mission mainly includes the following fields:

[0057]

[0058] The second-pass ship task mainly includes the following field information:

[0059]

[0060] The mixed ore task mainly includes the following field information:

[0061]

[0062] Objective environmental information mainly includes day and night visibility, tides, and weather, which are key factors affecting production scheduling.

[0063] 1. Sunset and sunrise:

[0064]

[0065] 2. Tidal data:

[0066]

[0067] 3. Weather information:

[0068]

[0069] The terminal static information mainly includes the static properties of the resources and equipment within the terminal, as follows:

[0070] 1. Ship loaders, ship unloaders, bucket wheel excavators, stackers, and reclaimers:

[0071]

[0072] 2. Belt conveyor and process:

[0073]

[0074] 3. Berth:

[0075]

[0076] 4. Yard:

[0077]

[0078] The terminal dynamic information mainly includes the internal resources, equipment and attributes of the docked ships at the start of the scheduling algorithm, as follows:

[0079] 1. Overall production target

[0080]

[0081] 2. Ship loaders, ship unloaders, bucket wheel excavators, stackers, and reclaimers:

[0082]

[0083] 3. Belt conveyor and process:

[0084]

[0085] 4. Berths and berthed ships:

[0086]

[0087] 5. Stacking in the yard:

[0088]

[0089] S2, inputting the historical production scheduling information into the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model respectively, to obtain the ship berthing planning information and the bucket wheel machine planning information.

[0090] In S2, the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model may be established based on the data information input by the user, or may be established based on the data in the historical production scheduling information.

[0091] S3, inputting the ship berthing planning information and bucket wheel machine planning information into the preset simulation model to obtain the terminal resource evolution result.

[0092] In S3, the preset simulation model is used to perform corresponding simulation scheduling operations according to the ship berthing planning information and bucket wheel excavator planning information, and obtain the terminal resource evolution results corresponding to the scheduling operations.

[0093] It should be noted that terminal resources refer to the various hardware and software resources involved in terminal operations, which work together to ensure the safe, efficient and orderly handling of cargo and ships. The following are some key scheduling resources:

[0094] 1. Hardware resources

[0095] Berth: A terminal's berth is where ships dock. The number and size of berths determine the number and type of ships the terminal can handle simultaneously.

[0096] Loading and unloading equipment: including but not limited to bridge cranes (gantry cranes), mobile cranes, forklifts, reach stackers, stackers, conveyor belts, etc., used for loading, unloading and handling of goods.

[0097] Yard: used to store goods to be loaded and unloaded, including container yard, bulk cargo yard, roll-on / roll-off cargo parking area, etc.

[0098] Warehousing facilities: Warehouses are used to store specific types of goods, such as refrigerated warehouses, hazardous goods warehouses, etc.

[0099] Transport vehicles: such as trucks, trailers, etc., used for transportation within the terminal or connecting with the outside.

[0100] Auxiliary facilities: including offices, maintenance workshops, gas stations, sewage treatment facilities, power supply facilities, etc.

[0101] 2. Software Resources

[0102] Information systems: such as terminal operating systems (TOS), automated identification systems (such as RFID), cargo tracking systems, etc., used to manage cargo information, dispatch resources, and monitor operation progress.

[0103] Communication system: ensure effective communication between departments within the terminal and with external partners.

[0104] Security and monitoring systems: including video surveillance, fire and theft prevention systems, environmental monitoring systems, etc., to ensure the safety and environmental protection of the terminal.

[0105] Data analysis and forecasting system: used to collect and analyze operational data, predict future demand, and optimize production scheduling.

[0106] 3. Human Resources

[0107] Operators: including terminal operators, stevedores, equipment operators, etc.

[0108] Managers: Various personnel responsible for planning, scheduling, supervising and coordinating terminal operations.

[0109] Technicians: Professionals responsible for equipment maintenance, system development and maintenance.

[0110] Safety and Security Officers: Responsible for maintaining safety and order at the terminal.

[0111] 4. Logistics resources

[0112] Supply chain partners: including carriers, freight forwarders, logistics companies, etc., who work with terminals to complete the transportation and distribution of goods.

[0113] Customer relations: Good relations with customers such as cargo owners and shipping companies ensure the stability and expansion of business.

[0114] 5. Energy and environmental resources

[0115] Power supply: Provide necessary electricity for terminal operations, including the power needs of loading and unloading equipment, lighting, office equipment, etc.

[0116] Environmental protection measures: wastewater treatment, exhaust emission control, noise control, etc., to ensure that terminal operations meet environmental protection standards.

[0117] 6. Regulations and Permits

[0118] Operating license: Ensure that terminal operations comply with local and international laws and regulations, including safety, environmental protection, customs and other permits.

[0119] Standards and procedures: Comply with international and industry standards such as ISO certification, safe operating procedures, etc.

[0120] Effectively managing these resources and ensuring their coordination is the key to efficient terminal production. By optimizing resource allocation and utilization, the terminal's throughput capacity and customer service level can be improved while reducing operating costs and environmental impact.

[0121] S4, determining the evaluation index value corresponding to the terminal resource evolution result according to the terminal resource evolution result.

[0122] In S4, according to the evolution of terminal resources, such as the maintenance of terminal structure, the replacement of equipment, the growth of throughput, etc., the weights and calculation methods of the above indicators can be adjusted accordingly to reflect the impact of resource changes on the overall performance of the terminal. The final evaluation index value can be used to evaluate the current status of the terminal and guide future planning and improvement measures.

[0123] S5, determining whether the evaluation index value is within a preset range.

[0124] In S5 , the preset range may be set by the user.

[0125] S6, when it is determined that the evaluation index value is not within the preset range, adjusting the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model.

[0126] In S6, identify which model parameters have a direct impact on these evaluation indicators. For example, in the berthing and unberthing planning model, the key parameters may include:

[0127] berth allocation strategy;

[0128] dispatch of pilots and tugboats;

[0129] Berthing and unberthing time windows;

[0130] Weather and sea conditions apply.

[0131] In the bucket wheel machine task allocation planning model, key parameters may include:

[0132] Bucket wheel excavator duty cycle;

[0133] Task priority and sequencing;

[0134] Loading and unloading rate;

[0135] Energy consumption and efficiency.

[0136] When adjusting model parameters, based on the results of the indicator analysis, adjust the model parameters to optimize those areas that are performing poorly. For example, if the berth occupancy rate is too low, it may be necessary to adjust the berthing time window or optimize the berth allocation strategy to improve the efficiency of berth utilization. If the utilization rate of the bucket wheel machine is not high, it may be necessary to reconsider the task allocation logic to ensure that the bucket wheel machine is loaded evenly during the working cycle.

[0137] After adjusting the model parameters, model iteration and verification can also be performed. For example, after adjusting the parameters, the model is rerun to evaluate the performance of terminal operations under the new parameter settings. This may involve multiple iterations until a set of optimal parameter combinations is found so that the evaluation indicators reach the optimal or close to the target value.

[0138] After iterative validation, the model can also be implemented and monitored. For example, the optimized model parameters can be applied to actual operations and their effects can be continuously monitored. External conditions (such as market demand, weather, and regulatory changes) may change over time, so it is necessary to review and adjust model parameters regularly.

[0139] Secondly, after the above steps, a feedback loop can also be set up, which can be to establish a feedback mechanism to collect operational data and employee feedback to continuously improve the model. This includes regular review of evaluation indicators and comparison with model predictions to verify the accuracy and applicability of the model.

[0140] Through the above steps, it can be ensured that the berthing and unberthing planning model and the bucket wheel machine task allocation planning model can be adjusted according to the actual operation of the terminal, thereby improving the efficiency and economic benefits of the terminal while meeting safety and environmental standards.

[0141] Based on the above steps S1 to S6, by acquiring the historical production scheduling information of the terminal; inputting the historical production scheduling information into the preset berthing and unberthing planning model and the preset bucket wheel excavator task allocation planning model respectively, to obtain the ship berthing planning information and the bucket wheel excavator planning information; inputting the ship berthing planning information and the bucket wheel excavator planning information into the preset simulation model to obtain the terminal resource evolution result; according to the terminal resource evolution result, determining the evaluation index value corresponding to the terminal resource evolution result; judging whether the evaluation index value is within the preset range; when judging that the evaluation index value is not within the preset range, adjusting the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel excavator task allocation planning model, the intelligent predictive production scheduling of the terminal is realized, and there is no need to rely on the production scheduling experience of the central control dispatcher for resource allocation, which solves the problem of low resource allocation utilization rate of the terminal in the prior art and improves the resource allocation utilization rate of the terminal.

[0142] In some of the embodiments, the dock resource evolution result may also be saved to facilitate visualization of the dock resource evolution result.

[0143] In the above embodiment, the preset simulation model is in Python language, wherein the preset simulation model includes a main program and a calling function. The main program includes: simulation.py. The calling function includes at least one of the following: input_parameter.py function, input_state.py function, input_demand.py function, berth_and_time.py function, berth_arrangement.py function, zhijinchu_mission.py function, yard_arrangement.py function, hunkuang_mission.py function, path_identification.py function.

[0144] Use Python language to do production scheduling simulation, where the main program is simulation.py, and there are 9 other functions that need to be called at appropriate times in the main program. The following describes the overall framework of the simulation, focusing on the execution order and main contents of the main program and each function.

[0145] In some of the embodiments, the ship berthing planning information and the bucket wheel excavator planning information are input into a preset simulation model to obtain the terminal resource evolution result, including: simulating the terminal operation process based on the ship berthing planning information and the bucket wheel excavator planning information through the preset simulation model to obtain the simulation evolution result; determining the terminal resource evolution result based on the simulation evolution result.

[0146] In this embodiment, the terminal operation process is simulated based on the ship berthing planning information and the bucket wheel machine planning information by using a preset simulation model, and then the terminal resource evolution result is determined according to the simulation evolution result. This is a systematic process, which mainly includes the following steps:

[0147] Step 1. Data preparation and input

[0148] Ship berthing planning information: including the ship's arrival time, departure time, required berth type, cargo information (type, quantity), loading and unloading requirements, etc.

[0149] Bucket wheel machine planning information: involves bucket wheel machine availability, working hours, task allocation, maintenance plan, etc.

[0150] Step 2. Build a simulation model

[0151] Build a preset simulation model using appropriate simulation software or programming language (such as Python, MATLAB, ARENA, etc.).

[0152] The model should be able to simulate the physical layout of the terminal, resource flows, operational processes, and potential random events (e.g., equipment failure, severe weather).

[0153] Step 3. Simulation run

[0154] The ship berthing planning information and bucket wheel excavator planning information are input into the simulation model and the simulation operation is started.

[0155] Based on the input information, the model will simulate the daily operations of the terminal, including the berthing and departure of ships, the loading and unloading of cargo, and the execution of bucket wheel excavator tasks.

[0156] Step 4. Collect simulation evolution results

[0157] After the simulation run is completed, the data from the simulation process are collected, which reflect the operating status of the terminal under the given planning information.

[0158] The simulation evolution results may include but are not limited to berth occupancy rate, bucket wheel machine utilization rate, cargo loading and unloading efficiency, yard storage status, equipment failure rate, operating costs, etc.

[0159] Step 5. Determine the evolution results of terminal resources

[0160] The collected simulation evolution results are analyzed to determine the evolution of the terminal resources during the simulation period.

[0161] This includes identifying peak usage periods for resources, bottlenecks, resource idleness, and any potential optimization opportunities.

[0162] In this way, simulation models become a powerful tool that helps terminal managers not only understand current operations but also predict future resource needs and challenges, allowing them to make more effective decisions.

[0163] In some embodiments, the production scheduler inputs information through the user interface of the software platform, and this information will be stored in the underlying database. The production scheduling algorithm needs to read the required information from the database. At the beginning of the main program, several information reading functions input_parameter.py, input_state.py, input_demand.py, berth_and_time.py are called to obtain the production scheduling demand task information, objective environment information, terminal static information, and terminal dynamic information.

[0164] (1) Call the input_parameter.py function to initialize the static information of the terminal.

[0165] (2) Call the input_state.py function to initialize the terminal dynamic state list and define the future transportation task table.

[0166] (3) Call the input_demand.py function to initialize the production demand task information.

[0167] (4) Call the berth_and_time.py function to initialize the objective environment information and identify the berths and times at which the ship can dock and leave.

[0168] After the above information is prepared, in some embodiments thereof, it is also possible to determine whether the cargo loading and unloading results at each preset time meet the preset cargo loading and unloading results based on the simulation evolution results; if so, the terminal resource evolution results are determined based on the cargo loading and unloading results; if not, the first user input information is obtained, and the cargo loading and unloading results are modified based on the first user input information, and the terminal resource evolution results are determined based on the modified cargo loading and unloading results.

[0169] In this embodiment, the berth_arrangement.py function is first called to complete the berthing and unberthing planning model decision, and the berth status transfer in the next N discrete time periods is performed according to the model results. At the beginning of each moment, when the conditions for loading and unloading are not met, the berth status is updated in the main program according to the rules preset by the user. When loading and unloading is required, the zhijinchu_mission.py function is called to make a transportation task decision, and the berth status list at the beginning of the moment and the transportation task list within the moment are filled in.

[0170] (5) Call the berth_arrangement.py function to determine the ship’s berthing position and berthing order.

[0171] (6) Call the zhijinchu_mission.py function to directly load entry and exit tasks according to the berth status at the beginning of each moment and update the berth status list.

[0172] In some of the embodiments, the simulation evolution results include: the evolution results of the yard and the mixed ore; before determining the evolution results of the terminal resources based on the simulation evolution results, the evolution results of the yard and the mixed ore at each preset moment can also be obtained; based on the evolution results of the yard and the mixed ore at each preset moment, the mixed ore task table is updated; based on the mixed ore task table, the evolution results of the terminal resources are determined.

[0173] In this embodiment, we return to the simulation start time and perform the state transfer of the yard and mixed ore tasks in the next N discrete time periods. According to the rules given by the yard decision module preset by the user, when the allocation planning model is needed, the yard_arrangement.py function is called to complete the yard and bucket wheel machine planning for the entry and exit tasks. At the beginning of each moment, the entry and exit tasks are performed according to the results of the planning, and the hunkuang_mission.py function is called at the same time to use the remaining stackers and belts to perform the mixed ore tasks, and then fill in the mixed ore task table. Specifically, it can be and update the yard status table and the mixed ore status table according to the entry and exit tasks and the mixed ore tasks.

[0174] (7) Call the yard_arrangement.py function to determine which stack each entry and exit task should be operated on and which bucket wheel excavator should be used.

[0175] (8) Call the hunkuang_mission.py function to determine which stackers and reclaimers are to be used on which piles for mixing ore.

[0176] At the end of the simulation, traverse the tasks at all times in the direct loading, entry and exit, and mixed ore task tables, and call the path_identification.py function to identify the process.

[0177] (9) Call the path_identification.py function to identify the equipment code according to the key equipment used in each transportation task.

[0178] Further describe the functions of each function in the simulation:

[0179] 1) input_parameter.py:

[0180] Input: None.

[0181] Content: Read the static information of the terminal from the database and define some static model parameters, and perform basic reading and assignment.

[0182] Output: mainly includes the following important sets and parameters related to berths, yards and equipment in the mathematical model: .

[0183] 2) input_state.py:

[0184] Input: None.

[0185] Content: Define the berth, yard, and mixed ore status list, and read the current status from the database, and perform basic reading and assignment. Define the direct loading, entry, exit, and mixed ore task list, and define the task list to be empty initially.

[0186] Output: A data list in dataframe format containing the following fields.

[0187] Unloading berth status list (one status list for each berth): time, berth code, free or busy, berth preparation time, berthed ship name, ship type, berthed time, remaining pre-loading and unloading process time, ore type and cargo owner, and remaining unloading volume for each cargo owner of each ore type.

[0188] Loading berth status list (one status list for each berth): time, berth code, free or busy, berth preparation time, berth name, remaining pre-loading and unloading process time, ore type and cargo owner, and remaining loading quantity of each cargo owner for each ore type.

[0189] Stockpile status list (one status list for the entire stockpile): time, stack number, starting position, ending position, ore type, ore quantity, stockpile path, element attributes, included finished ore batches, and whether it is a previous single pile stack.

[0190] Mixing status list (one status list for all batches): time, mixing task batch number, and remaining mixing quantity.

[0191] Direct loading task list (one list for all tasks): time, ore type, ore quantity, first-leg ship name, berth, second-leg ship name, berth, the first section of the approach belt called, the number of unloaders called, the number of loaders called, and the process number.

[0192] Approaching task list (one list for all tasks): time, ore type, ore quantity, single mixed pile type, element attributes, ore density, element attribute requirements, ship name, berth, the first approaching belt called, the number of ship unloaders called, the bucket wheel machine number called, stack number, new stack number, process number.

[0193] Exit task list (one list for all tasks): time, ore type, ore quantity, single mixed pile type, mixed ore task batch number, element attribute requirements, ship name, berth, called loader number, called bucket wheel machine number, stacking number, process number.

[0194] Mixed ore task list (one list for all tasks): time, mixed ore task batch number, raw ore type 1, called reclaimer 1, stacking number 1, ore taking quantity 1, raw ore type 2, called reclaimer 2, stacking number 2, ore taking quantity 1, finished ore type, called stacking machine, stacking number, process number.

[0195] 3) input_demand.py:

[0196] Input: None.

[0197] Content: Read the production scheduling task information from the database and process it into a suitable data format.

[0198] Output: mainly includes the following sets and parameters related to ships and ore mixing tasks in the mathematical model: , stores the attributes of the berthing and unberthing tasks of the first-leg ship and the second-leg ship and the blending requirements in dataframe format.

[0199] 4) berth_and_time.py:

[0200] Input: The first-leg ship and second-leg ship berthing and departure task attributes output by input_demand.py.

[0201] Content: Calculation It is the sum of the time for constant, drainage and other processes. Environmental factor information is read from the database, and the reliable departure time range of each ship is sorted out by combining factors such as sunrise and sunset, tide, wind force, etc. , according to the ship type, determine the berth set that the ship can dock at .

[0202] Output: The attributes of the first-leg ship and the second-leg ship's berthing and departure tasks in the improved dataframe format.

[0203] 5) berth_arrangement.py:

[0204] Input: The berthing and unberthing task attributes of the first-leg ship and the second-leg ship output by berth_and_time.py and the static attributes of the terminal output by input_parameter.py.

[0205] Content: Solve the planning model for docking and undocking modules.

[0206] Output: An array of the names of the ships that dock at each berth.

[0207] 6)zhijinchu_mission.py:

[0208] Input: the latest updated berth status list and direct loading and unloading task list, the name of the berth that needs to be loaded and unloaded at the current moment, the first-leg ship and second-leg ship berthing and departure task attributes output by berth_and_time.py, and the static attributes of the terminal output by input_parameter.py.

[0209] Content: Identify the cargo owners of the minerals that are being loaded and unloaded at each berth that needs to be loaded and unloaded at this moment, arrange direct loading first, then arrange exit and entry, arrange unloaders and entry belts for each process at the unloading berth, and arrange loaders for each process at the loading process. Fill the arranged direct loading and exit and entry tasks into the transportation task list, and update the status transfer of the berth for loading and unloading.

[0210] Output: Add the transport task table with the tasks within this moment and add the berth status table with the status at the next moment.

[0211] 7) yard_arrangement.py:

[0212] Input: the latest updated yard status list, entry and exit transportation task list.

[0213] Content: Identify the stacks that each task can work on , identify the stacks that each bucket wheel machine can work on , identify the tasks each bucket wheel machine can work on , identifying the optimal stack for each bucket wheel machine and the task it can work on And the impact on the yard score , solve the allocation planning model to determine which bucket wheel machine will complete each entry and exit task and which stack it will work on.

[0214] Output: Added entry and exit task table with bucket wheel machine and stacking information.

[0215] 8) hunkuang_mission.py:

[0216] Input: the current entry and exit task list, the latest updated mixed ore status list and mixed ore task list and yard status list.

[0217] Content: Identify idle bucket wheel machines and conveyors, identify workable stacks and optimal stacks, proportion them according to a fixed mixing volume, and arrange stackers, stacks and conveyors for the mixing task.

[0218] Output: Add the mixed mining task table of tasks within this moment.

[0219] 9) path_identification.py:

[0220] Input: Full-time direct loading, entry, exit, and ore mixing task list.

[0221] Content: Read the scheduling results of ship loaders, stackers and reclaimers, and conveyor belts, and generate the process codes used.

[0222] Output: Completed direct loading, entry, exit, and ore mixing task list.

[0223] In some of the embodiments, after S5, when it is determined that the evaluation index value is within a preset range, the production scheduling task can be executed according to the ship berthing planning information and the bucket wheel excavator planning information.

[0224] In this embodiment, through the above method, there is no need to rely on the production scheduling experience of the central control dispatcher, which solves the problem of low resource allocation utilization rate of the terminal due to manual experience and improves the resource allocation utilization rate of the terminal.

[0225] In some of the embodiments, S6 includes: when it is determined that the evaluation index value is not within a preset range, obtaining second user input information; and adjusting parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model according to the second user input information.

[0226] In this embodiment, the user can input information to adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model. After adjusting the model parameters, the model can be iterated and verified. For example, after adjusting the parameters, the model is rerun to evaluate the performance of the terminal operation under the new parameter settings. This may involve multiple iterations until a set of optimal parameter combinations is found so that the evaluation index reaches the optimal or close to the target value.

[0227] This embodiment also provides a production scheduling prediction device for a dock, which is used to implement the above embodiments and preferred implementations, and will not be repeated here. As used below, the terms "module", "unit", "subunit", etc. can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0228] Figure 3 is a structural block diagram of the production scheduling prediction of the terminal according to the embodiment of the present application, such as Figure 3 As shown, the device comprises:

[0229] An acquisition module 31 is used to acquire historical production scheduling information of the terminal;

[0230] The first input module 32 is used to input the historical production scheduling information into the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model respectively, so as to obtain the ship berthing planning information and the bucket wheel machine planning information;

[0231] The second input module 33 is used to input the ship berthing planning information and the bucket wheel machine planning information into the preset simulation model to obtain the terminal resource evolution result;

[0232] A determination module 34, used to determine the evaluation index value corresponding to the terminal resource evolution result according to the terminal resource evolution result;

[0233] A judging module 35 is used to judge whether the evaluation index value is within a preset range;

[0234] The adjustment module 36 is used to adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model when it is determined that the evaluation index value is not within the preset range.

[0235] In some of the embodiments, the device further includes: a saving module, configured to save the dock resource evolution result.

[0236] In some of the embodiments, the second input module 33 includes: a simulation submodule, which is used to simulate the operation process of the terminal based on the ship berthing planning information and the bucket wheel excavator planning information through a preset simulation model to obtain a simulation evolution result; and a first determination submodule, which is used to determine the terminal resource evolution result based on the simulation evolution result.

[0237] In some of the embodiments, the simulation evolution results include: cargo loading and unloading results; the device also includes: a judgment submodule, used to judge whether the cargo loading and unloading results within each preset time meet the preset cargo loading and unloading results based on the simulation evolution results; a second determination submodule, used to determine the terminal resource evolution results according to the cargo loading and unloading results if so; a third determination submodule, used to obtain the first user input information if not, and modify the cargo loading and unloading results according to the first user input information, and determine the terminal resource evolution results according to the modified cargo loading and unloading results.

[0238] In some of the embodiments, the simulation evolution results include: the evolution results of the yard and the mixed ore; the device also includes: a first acquisition submodule, used to obtain the evolution results of the yard and the mixed ore at each preset moment; an update submodule, used to update the mixed ore task table according to the evolution results of the yard and the mixed ore at each preset moment; a fourth determination submodule, used to determine the evolution results of the terminal resources according to the mixed ore task table.

[0239] In some of the embodiments, the device further includes: an execution module for executing production scheduling tasks according to ship berthing planning information and bucket wheel machine planning information when it is determined that the evaluation index value is within a preset range.

[0240] In some of the embodiments, the adjustment module 36 includes: a second acquisition submodule, used to obtain second user input information when it is determined that the evaluation index value is not within a preset range; an adjustment submodule, used to adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model according to the second user input information.

[0241] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0242] This embodiment further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0243] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0244] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0245] S1, obtain the historical production scheduling information of the terminal;

[0246] S2, inputting the historical production scheduling information into the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model respectively, to obtain the ship berthing planning information and the bucket wheel machine planning information;

[0247] S3, inputting the ship berthing planning information and bucket wheel machine planning information into a preset simulation model to obtain the dock resource evolution result;

[0248] S4, determining the evaluation index value corresponding to the terminal resource evolution result according to the terminal resource evolution result;

[0249] S5, determining whether the evaluation index value is within a preset range;

[0250] S6, when it is determined that the evaluation index value is not within the preset range, adjusting the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel machine task allocation planning model.

[0251] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0252] In addition, in combination with the production scheduling forecasting method for a terminal in the above embodiment, the embodiment of the present application can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, any of the production scheduling forecasting methods for a terminal in the above embodiment is implemented.

[0253] Those skilled in the art should understand that the technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0254] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for predicting production schedule of a terminal, characterized in that: include: S1, obtain the historical production scheduling information of the terminal; S2, inputting the historical production scheduling information into a preset berthing and unberthing planning model and a preset bucket wheel machine task allocation planning model respectively, to obtain ship berthing planning information and bucket wheel machine planning information; S3, inputting the ship berthing planning information and the bucket wheel machine planning information into a preset simulation model to obtain a terminal resource evolution result; wherein, inputting the ship berthing planning information and the bucket wheel machine planning information into the preset simulation model to obtain a terminal resource evolution result comprises: simulating the terminal operation process based on the ship berthing planning information and the bucket wheel machine planning information through the preset simulation model to obtain a simulation evolution result; determining the terminal resource evolution result according to the simulation evolution result; The simulation evolution result includes: cargo loading and unloading result; before determining the terminal resource evolution result according to the simulation evolution result, the method includes: judging whether the cargo loading and unloading result at each preset time meets the preset cargo loading and unloading result according to the simulation evolution result; if so, determining the terminal resource evolution result according to the cargo loading and unloading result; if not, obtaining the first user input information, modifying the cargo loading and unloading result according to the first user input information, and determining the terminal resource evolution result according to the modified cargo loading and unloading result; The simulation evolution result also includes: the evolution result of the stockyard and the mixed ore; before determining the evolution result of the terminal resources according to the simulation evolution result, the method also includes: obtaining the evolution result of the stockyard and the mixed ore at each preset moment; updating the mixed ore task table according to the evolution result of the stockyard and the mixed ore at each preset moment; determining the evolution result of the terminal resources according to the mixed ore task table; S4, determining an evaluation index value corresponding to the terminal resource evolution result according to the terminal resource evolution result; S5, judging whether the evaluation index value is within a preset range; after the step S5, the method further comprises: when judging that the evaluation index value is within the preset range, executing the production scheduling task according to the ship berthing planning information and the bucket wheel machine planning information; S6. When it is determined that the evaluation index value is not within the preset range, adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel excavator task allocation planning model; wherein, the S6 step also includes: when it is determined that the evaluation index value is not within the preset range, obtain second user input information; and adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel excavator task allocation planning model according to the second user input information.

2. The method for predicting the production schedule of a terminal according to claim 1, characterized in that: The method further comprises: The evolution result of the wharf resources is saved.

3. A production scheduling prediction device for a dock, characterized in that: include: The acquisition module is used to obtain the historical production scheduling information of the terminal; A first input module is used to input the historical production scheduling information into a preset berthing and unberthing planning model and a preset bucket wheel machine task allocation planning model, respectively, to obtain ship berthing planning information and bucket wheel machine planning information; A second input module is used to input the ship berthing planning information and the bucket wheel machine planning information into a preset simulation model to obtain a terminal resource evolution result; wherein the second input module is also used to: simulate the operation process of the terminal based on the ship berthing planning information and the bucket wheel machine planning information through the preset simulation model to obtain a simulation evolution result; determine the terminal resource evolution result according to the simulation evolution result; The simulation evolution result includes: cargo loading and unloading result; before determining the terminal resource evolution result according to the simulation evolution result, the second input module is further used to: determine whether the cargo loading and unloading result at each preset time meets the preset cargo loading and unloading result according to the simulation evolution result; if so, determine the terminal resource evolution result according to the cargo loading and unloading result; if not, obtain the first user input information, modify the cargo loading and unloading result according to the first user input information, and determine the terminal resource evolution result according to the modified cargo loading and unloading result; The simulation evolution result also includes: the evolution result of the stockyard and the mixed ore; before determining the evolution result of the terminal resources according to the simulation evolution result, the second input module is also used to: obtain the evolution result of the stockyard and the mixed ore at each preset moment; update the mixed ore task table according to the evolution result of the stockyard and the mixed ore at each preset moment; determine the evolution result of the terminal resources according to the mixed ore task table; A determination module, used to determine the evaluation index value corresponding to the terminal resource evolution result according to the terminal resource evolution result; A judgment module, used to judge whether the evaluation index value is within a preset range; wherein the judgment module is further used to: when it is judged that the evaluation index value is within the preset range, execute the production scheduling task according to the ship berthing planning information and the bucket wheel machine planning information; An adjustment module is used to adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel excavator task allocation planning model when it is determined that the evaluation index value is not within the preset range; wherein the adjustment module is also used to: when it is determined that the evaluation index value is not within the preset range, obtain second user input information; and adjust the parameters corresponding to the preset berthing and unberthing planning model and the preset bucket wheel excavator task allocation planning model according to the second user input information.

4. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the production scheduling forecasting method for a terminal according to any one of claims 1 to 2.

5. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the production scheduling forecasting method for a terminal according to any one of claims 1 to 2 when running.

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