Multi-agent based casting-rolling interface logistics simulation system, method, and computer device

Abstract

The present invention discloses a casting-rolling interface logistics simulation system, method, and computer device based on multi-agents. The steps include: dividing the casting-rolling interface into a continuous casting area, a connection area, and a rolling area, establishing a continuous casting agent, a connection area agent, a rolling agent, a slab agent, and a scheduling agent, and establishing a digital simulation model according to a 1:1 ratio; formulating a global objective under multiple constraint conditions such as resources, time, space, and temperature; the scheduling agent uses the space-time conversion and process coupling methods to decompose the global objective into local objectives and establish an intelligent scheduling model; through the division of labor and cooperation of agents, simulate the logistics process of the slab agent; according to the simulation results, evaluate the model performance, adjust the model parameters, and optimize the intelligent scheduling model; complete the logistics simulation, obtain the optimal logistics plan, and form a rule base and a knowledge base. The present invention can optimize the logistics process of the casting-rolling interface, optimize and improve the process plan, and reduce energy consumption.

Description

Technical Field

[0001] The present invention relates to the technical fields of iron and steel metallurgy, logistics simulation, and intelligent manufacturing. More specifically, it relates to a logistics simulation method for the casting-rolling interface based on multi-agent technology. Background Art

[0002] Under the development requirements of the new era and the strong promotion of new technologies, intelligent manufacturing and green manufacturing have become the mainstream directions for the transformation and upgrading of the iron and steel industry. In the bar and wire rod production line, the continuous casting-rolling section generally includes three main processes: continuous casting, reheating furnace, and rolling. Its main function is to solidify molten steel into billets and roll them into steel products. Taking the energy consumption of typical bar and wire rod rolling production as an example, the energy consumed for billet heating accounts for about 80%, and the energy consumption for steel rolling only accounts for about 15%. The direct rolling technology and hot charging and hot delivery technology can enable the billets after continuous casting to enter the rolling mill for rolling without passing through the reheating furnace or after supplementing part of the heat in the reheating furnace, with remarkable energy-saving effects.

[0003] In recent years, in the field of long profiles, especially bar and wire rod technology, many domestic iron and steel enterprises have tried the direct rolling process without using a reheating furnace for continuous casting billets, but most of them have not achieved ideal results. High casting speed continuous casting reflects the requirements of efficient and green development of the iron and steel manufacturing process and has been gradually promoted and applied in the industry. The production mode of one continuous casting machine for multiple rolling lines has become the mainstream design, production, and operation mode of iron and steel enterprises, and at the same time, it has also put forward higher requirements for the logistics at the casting-rolling interface. The core of the direct rolling technology or hot charging and hot delivery technology lies in the connection between the continuous casting and rolling processes. Whether large-scale direct rolling or hot charging and hot delivery can be achieved is closely related to the logistics level at the casting-rolling interface.

[0004] The simulation method based on virtual reality and digital modeling technology can effectively explore the logistics operation rules, verify the feasibility of process plans, discover key problem links, propose optimization and improvement measures, improve the direct rolling rate or hot delivery rate, and provide important support for the management and decision-making in the logistics system planning, design, and operation, playing a significant role in the design, production, and operation of iron and steel projects. Summary of the Invention

[0005] Aiming at the defects and deficiencies of the existing technology, the present invention proposes a logistics simulation method for the casting-rolling interface based on multi-agent technology. Through digital modeling and intelligent decision-making, it simulates the actual iron and steel production process, explores the logistics operation rules, verifies the feasibility of process plans, discovers key problem links, proposes optimization and improvement measures, improves the direct rolling rate / hot delivery rate, provides important support for the management and decision-making in the logistics system planning, design, and operation, and plays a significant role in the design, production, and operation of iron and steel projects. This method can improve the intelligent and green level of the casting-rolling interface and promote the green, low-carbon, and high-quality development of China's iron and steel industry.

[0006] To achieve the above object, the present invention provides a multi-agent based logistics simulation method for the continuous casting and rolling interface, including a continuous casting agent, a connection area agent, a rolling agent, a billet agent, and a scheduling agent, characterized by the following steps:

[0007] Step 1: According to the continuous casting and rolling production processes and the layout plan, divide the continuous casting and rolling interface into a continuous casting area, a connection area, and a rolling area. Combining factors such as the process flow, production line equipment, and logistics process, establish a continuous casting agent, a connection area agent, a rolling agent, a billet agent, and a scheduling agent;

[0008] Step 2: According to the continuous casting production plan, the rolling production plan, and the logistics path of the continuous casting and rolling interface, formulate a global objective under multiple constraints such as resources, time, space, and temperature;

[0009] Step 3: According to the global objective, the scheduling agent uses methods such as space-time conversion and process coupling to decompose the global objective into local objectives and establish an intelligent scheduling model;

[0010] Step 4: Through the division of labor and cooperation of relevant agents, simulate the logistics process of the billet agent at the continuous casting and rolling interface;

[0011] Step 5: According to the simulation results, evaluate the model performance, adjust the model parameters, and optimize the intelligent scheduling model;

[0012] Step 6: Complete the logistics simulation, obtain the optimal logistics plan, form a rule base and a knowledge base, optimize the logistics process of the continuous casting and rolling interface, find the problem links at the continuous casting and rolling interface, adjust the problems existing in the process plan, improve the direct rolling rate and hot charging rate, reduce the hot loss of billets, reduce energy consumption, and promote the green and low-carbon transformation and upgrading of the iron and steel industry.

[0013] Furthermore, according to a multi-agent based logistics simulation method for the continuous casting and rolling interface described in claim 1, the continuous casting agent is used to simulate the process of molten steel solidifying into billets, including the continuous casting production plan, maintenance plan, and abnormal shutdown, etc.; the continuous casting agent generates billet agents according to process parameters such as the operating state of the continuous casting machine, steel grade, specification, number of strands, and casting speed, and sends them to direct rolling or hot charging through the lifting baffle on the roller table, or unloads them from the continuous casting cooling bed into the billet storage through a tilting machine, pusher, overhead crane, etc., and provides billet agents to the connection area agent;

[0014] Further, a multi-agent-based casting-rolling interface logistics simulation method according to claim 1, wherein the connection area agent is used to simulate the logistics process of the slab agent, including the direct rolling roller path agent, the hot delivery roller path agent, the slab storage agent, the heating furnace agent, and the cold charging roller path agent; among them, the direct rolling roller path agent is used to transport the slab agent to the rolling agent through the direct rolling roller path; the hot delivery roller path agent is used to transport the slab agent to the heating furnace agent through the hot delivery roller path; the slab storage agent is used to store the slab agent offline from the continuous casting cooling bed through the steel turning machine, pusher, overhead crane, etc., the slab agent offline from the direct rolling roller path and the hot delivery roller path, and the slab agent returned from the heating furnace agent, and provide the slab agent to the heating furnace agent through the cold charging roller path agent; the cold charging roller path agent is used to transport the slab agent from the slab storage agent to the heating furnace agent through the cold charging roller path; the heating furnace agent is used to receive the slab agent transported from the hot delivery roller path agent and the cold charging roller path agent, heat it to meet the rolling temperature requirements, and provide the slab agent to the rolling agent through the roller path;

[0015] Further, a multi-agent-based casting-rolling interface logistics simulation method according to claim 1, wherein the rolling agent is used to simulate the process of rolling the slab into steel, including rolling production plans, maintenance plans, abnormal shutdowns, etc.; the rolling agent receives the slab agent from the connection area agent, rolls the slab agent into steel according to the rolling production plan, or returns the slab agent to the connection area agent through the roller path, overhead crane, etc.;

[0016] Further, a multi-agent-based casting-rolling interface logistics simulation method according to claim 1, wherein the slab agent, as an intermediate carrier between molten steel and steel, receives the scheduling rules from the scheduling agent, enters the rolling agent or the heating furnace agent in the forms of direct rolling, hot delivery, and cold charging through the direct rolling roller path agent, the hot delivery roller path agent, the slab storage agent, the heating furnace agent, and the cold charging roller path agent, combined with the temperature evolution model, and is finally rolled into steel. Multiple slab agents together form a slab agent group;

[0017] Further, a multi-agent based casting-rolling interface logistics simulation method according to claim 1, characterized in that the scheduling agent provides intelligent decision-making support for the casting-rolling interface logistics process by establishing an intelligent scheduling model, and is responsible for task allocation and resource scheduling of all agents including the continuous casting agent, the connection area agent, the rolling agent, and the billet agent group, and coordinates the division of labor and cooperation among the agents. The scheduling agent obtains the continuous casting production plan and the rolling production plan from the continuous casting agent and the rolling agent respectively, generates a global goal, decomposes it into local goals, generates scheduling rules according to the global goal and local goals, and executes them through the connection area agent to complete the scheduling task; the scheduling agent receives feedback from other agents through interaction with other agents, and dynamically adjusts the intelligent scheduling model through self-learning and self-adaptation to optimize the logistics process;

[0018] Further, a multi-agent based casting-rolling interface logistics simulation method according to claim 1, characterized in that the agent is described by identification, type, knowledge base, rule set, attribute, and parameter; among them, the identification is the number of the agent, which is unique; the type is the type to which the agent belongs, and is used to handle the relationship between agents; the knowledge base is the set of knowledge owned by the agent; the rule set is that the agent reacts to external signals, receives external inputs, matches with the rules in the rule set, and outputs externally; the attribute is the fixed parameter of the agent, such as the steel type, specification, temperature, etc. of the billet agent; the parameter is the quantity that can be changed and regulated in the agent, such as the speed of the direct rolling roller path agent;

[0019] Further, a multi-agent based casting-rolling interface logistics simulation method according to claim 1, characterized in that the simulation system uses modular programming, and the quantity, position, function, etc. of various agents can be dynamically generated according to simulation requirements. The simulation system has good configurability and scalability, and can be customized according to different application scenarios to meet the personalized needs of iron and steel enterprises.

[0020] To achieve the above object, the multi-agent based casting-rolling interface logistics simulation system of the present invention includes: a continuous casting agent, a connection area agent, a rolling agent, a billet agent, and a scheduling agent; among them,

[0021] The continuous casting agent is used to simulate the process of molten steel solidifying into billets, including continuous casting production plans, maintenance plans, and abnormal shutdowns; the continuous casting agent generates billet agents according to the process parameters of the continuous casting machine, and sends them to direct rolling or hot delivery through the lifting baffle on the roller path, or enters the billet storage through the tilting machine, pusher, and overhead crane from the continuous casting cooling bed, and provides billet agents to the connection area agent; the process parameters at least include operating status, steel type, specification, number of strands, and casting speed;

[0022] The described connection area agent is used to simulate the logistics process of the billet agent, including the direct rolling roller path agent, the hot charging roller path agent, the billet storage agent, the heating furnace agent, and the cold charging roller path agent;

[0023] Among them,

[0024] The direct rolling roller path agent is used to transport the billet agent to the rolling agent through the direct rolling roller path;

[0025] The hot charging roller path agent is used to transport the billet agent to the heating furnace agent through the hot charging roller path;

[0026] The billet storage agent is used to store the billet agent that is taken off the continuous casting cooling bed by the tilting machine, pusher, and overhead crane, the billet agent that is taken off the direct rolling roller path and hot charging roller path, and the billet agent that is returned from the heating furnace agent, and provide the billet agent to the heating furnace agent through the cold charging roller path agent;

[0027] The cold charging roller path agent is used to transport the billet agent from the billet storage agent to the heating furnace agent through the cold charging roller path;

[0028] The heating furnace agent is used to receive the billet agent transported from the hot charging roller path agent and the cold charging roller path agent, heat it to meet the rolling temperature requirements, and provide the billet agent to the rolling agent through the roller path;

[0029] The described rolling agent is used to simulate the process of rolling the billet into steel, including at least the rolling production plan, maintenance plan, and abnormal shutdown; the rolling agent receives the billet agent from the connection area agent, rolls the billet agent into steel according to the rolling production plan, or returns the billet agent to the connection area agent through the roller path and overhead crane;

[0030] The billet agent, as an intermediate carrier between molten steel and steel, receives the scheduling rules from the scheduling agent, enters the rolling agent or heating furnace agent in the direct rolling, hot charging, and cold charging modes through the direct rolling roller path agent, hot charging roller path agent, billet storage agent, heating furnace agent, and cold charging roller path agent, and is finally rolled into steel;

[0031] The scheduling agent provides intelligent decision-making support for the logistics process of the casting and rolling interface by establishing an intelligent scheduling model, is responsible for the task assignment and resource scheduling of all agents including the continuous casting agent, connection area agent, rolling agent, and billet agent group, and coordinates the division of labor and cooperation among the agents;

[0032] The scheduling agent obtains the continuous casting production plan and the rolling production plan from the continuous casting agent and the rolling agent respectively, generates a global goal, decomposes it into local goals, generates scheduling rules according to the global goal and local goals, and executes through the connection area agent to complete the scheduling task; the scheduling agent receives feedback from other agents through interaction with other agents, and dynamically adjusts the intelligent scheduling model through self-learning and self-adaptation to optimize the logistics process.

[0033] To achieve the above object, a computer device of the present invention includes a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the above-mentioned multi-agent-based logistics simulation method for the casting and rolling interface when executing the program.

[0034] The present invention can establish a multi-agent system through the logistics simulation method for the casting and rolling interface, adopt digital modeling, simulate the actual steel production process, explore the logistics operation rules, verify the feasibility of the process plan, discover the key problem links, propose optimization and improvement measures, and obtain key information such as the optimal logistics plan, logistics capacity, direct rolling rate / hot charging rate, and theoretical production capacity under various process goals, providing important support for the management and decision-making in the logistics system planning, design, and operation, playing a significant role in the design, production, and operation of steel projects, and significantly reducing the investment cost and operation risk of project construction. This method can improve the intelligence and green level of the casting and rolling interface, and promote the green and low-carbon transformation and upgrading of China's steel industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flowchart of the present invention;

[0036] Figure 2 is a schematic diagram of the logistics simulation of the casting and rolling interface of the present invention.

[0037] In the figure: 1. Continuous casting agent; 2. Connection area agent; 3. Rolling agent; 4. Slab agent; 5. Direct rolling roller path agent; 6. Hot charging roller path agent; 7. Slab yard agent; 8. Heating furnace agent; 9. Cold charging roller path agent. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] In order to enable those skilled in the art of the present technology to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work shall fall within the protection scope of the present invention.

[0039] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0040] In addition, it should be noted that in the technical solution of this application, the acquisition, storage and application of user personal information and transaction information involved are all information authorized by the user or fully authorized by all parties.

[0041] Embodiment 1

[0042] According to an embodiment of the present invention, an embodiment of a casting-rolling interface logistics simulation method based on multi-agent is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0043] Embodiment 2

[0044] A casting-rolling interface logistics simulation method based on multi-agent in this embodiment is applied to the bar and wire rod production line of a certain iron and steel enterprise. The main equipment is 2 8-strand billet continuous casters, mainly producing small billets of 150×150mm and 165mm×165mm. The normal casting speed is 3.5 - 4.5m / min, and the maximum casting speed can reach 5.8 - 6.0m / min; there are 4 bar and wire rod rolling lines, and the required rolling start temperature is 880 - 920°C; there are 4 walking beam reheating furnaces for providing high-temperature billets to the rolling line during non-direct rolling; a combined rail bending roller table is used in the connection area, and the traveling path of the billet is controlled by a switch to perform direct rolling, hot charging or offline. Build a continuous casting agent, a connection area agent, a steel rolling agent, a billet agent, and a scheduling agent, and perform logistics simulation through the following steps:

[0045] Step 1: According to the continuous casting and steel rolling production processes and the plane layout, divide the casting-rolling interface into a continuous casting area, a connection area, and a steel rolling area. Combine factors such as the process flow, production line equipment, and logistics process to build a continuous casting agent, a connection area agent, a steel rolling agent, a billet agent, and a scheduling agent; build a digital simulation model according to a 1:1 ratio;

[0046] Step 2: According to the continuous casting production plan, steel rolling production plan and the logistics path of the casting and rolling interface, formulate global goals based on multiple constraints such as resources, time, space, temperature, etc.; input process parameters, time parameters, path parameters, logic parameters, other parameters, etc. The process parameters of this embodiment mainly include: 1# continuous casting machine produces 150×150mm square billets, 8 streams are turned on, and the pulling speed of each stream is about 4.0m / min; 2# continuous casting machine produces 150×150mm square billets, 6 streams are turned on, and the pulling speed of each stream is about 4.0m / min; 1# rolling line has an hourly capacity of 280t / h, using direct rolling; 2# rolling line has an hourly capacity of 260t / h, using hot delivery and cold loading; 3# rolling line has an hourly capacity of 280t / h, using direct rolling mode; 4# rolling line does not produce;

[0047] Step 3: According to the global goal of maximizing the direct rolling rate, the scheduling agent uses time-space conversion, process coupling and other methods to decompose the global goal into local goals, establish an intelligent scheduling model, take each billet as a local goal, and take all the billets in the connection area as a whole. According to the steel signal of the rolling line, the steel signal of the heating furnace, the billet position, and the time when the billet arrives at each node, the billet agent's travel path is planned in the order of direct rolling, hot delivery, and offline. The temperature of the billet agent at each node is calculated through the temperature evolution model to determine whether the process requirements are met. If not, it will be offline;

[0048] Step 4: Through the division of labor and cooperation among the continuous casting agent, the connection area agent, the steel rolling agent, and the scheduling agent, the simulation model is run at a time multiple of 0.1 to 1000 to simulate the logistics process of the billet agent group at the casting and rolling interface to verify the rationality of the model logic and the correctness of the model operation;

[0049] Step 5: Set the maintenance plan and abnormal shutdown status input, collect and analyze the simulation results such as data, charts, animations, etc. of the model operation, evaluate the model performance, adjust the model parameters, and optimize the intelligent scheduling model;

[0050] Step 6: Output simulation results of indicators such as production capacity, logistics capacity, equipment load, and logistics plan to form a rule base and knowledge base, optimize the logistics process of the casting and rolling interface, find the problematic links in the casting and rolling interface, adjust the problems in the process plan, improve the direct rolling rate and hot delivery rate, reduce the heat loss of the ingot, reduce energy consumption, and promote the green and low-carbon transformation and upgrading of the steel industry.

[0051] The simulation results show that the steel rolling capacity has basically reached the predetermined target, the average transportation time of the ingots has been shortened by 20 to 30 seconds, the average temperature drop has been reduced by 10 to 15°C, the direct rolling rate has reached 90 to 95%, an increase of about 10%, the smoothness of logistics has been improved by about 15%, and the off-line rate of ingots due to poor logistics or unqualified temperature has been reduced by about 20%.

[0052] Through a multi-agent system, the present invention establishes a digital simulation model to simulate the logistics situation at the casting and rolling interface, obtains key information such as the optimal logistics plan, logistics capacity, and theoretical production capacity, conducts a simulation demonstration on the logistics capacity at the casting and rolling interface, and provides important support for the management and decision-making in the planning, design, and operation of the logistics system.

[0053] The above has schematically described the present invention and its implementation manners. This description is not restrictive, and what is shown in the drawings is only one of the implementation manners of the present invention, and the actual situation is not limited thereto. Therefore, if those of ordinary skill in the art are inspired by it and, without departing from the purpose of the present invention, creatively design a structural manner and an embodiment similar to the technical solution, they shall fall within the protection scope of the present invention.

Claims

1. A multi-agent based simulation method for the logistics at the casting and rolling interface, characterized in that, The method described above includes the following steps: Step 1: According to the continuous casting, rolling production processes and layout, divide the casting and rolling interface into a continuous casting area, a connection area, and a rolling area. Combining process flow, production line equipment, and logistics process factors, establish a continuous casting agent, a connection area agent, a rolling agent, a billet agent, and a scheduling agent; Step 2: According to the continuous casting production plan, rolling production plan, and the logistics path of the casting and rolling interface, formulate a global objective under multiple constraints based on resources, time, space, and temperature; Step 3: According to the global objective, the scheduling agent uses the methods of space-time conversion and process coupling to decompose the global objective into local objectives and establish an intelligent scheduling model; Step 4: Through the division of labor and cooperation of relevant agents, simulate the logistics process of the billet agent at the casting and rolling interface; Step 5: According to the simulation results, evaluate the model performance, adjust the model parameters, and optimize the intelligent scheduling model; Step 6: Complete the logistics simulation, obtain the optimal logistics plan, form a rule base and a knowledge base, and optimize the logistics process of the casting and rolling interface; The connection area agent described above is used to simulate the logistics process of the billet agent, including a direct rolling roller table agent, a hot charging roller table agent, a billet storage agent, a heating furnace agent, and a cold charging roller table agent; Among them, The direct rolling roller table agent is used to transport the billet agent to the rolling agent through the direct rolling roller table; The hot charging roller table agent is used to transport the billet agent to the heating furnace agent through the hot charging roller table; The billet storage agent is used to store the billet agent that is offline from the continuous casting cooling bed through a tilting machine, a pusher, and a crane, the billet agent that is offline from the direct rolling roller table and the hot charging roller table, and the billet agent that is returned from the heating furnace agent, and provide the billet agent to the heating furnace agent through the cold charging roller table agent; The cold charging roller table agent is used to transport the billet agent from the billet storage agent to the heating furnace agent through the cold charging roller table; The heating furnace agent is used to receive the billet agent transported from the hot charging roller table agent and the cold charging roller table agent, heat it to meet the rolling temperature requirements, and provide the billet agent to the rolling agent through the roller table; The scheduling agent described above provides intelligent decision-making support for the logistics process of the casting and rolling interface by establishing an intelligent scheduling model, and is responsible for task allocation and resource scheduling of all agents including the continuous casting agent, the connection area agent, the rolling agent, and the billet agent group, and coordinating the division of labor and cooperation among the agents.

2. The method for simulating the logistics at the casting-rolling interface based on multi-agent according to claim 1, wherein The continuous casting agent described above is used to simulate the process of molten steel solidifying into billets, including continuous casting production plans, maintenance plans, and abnormal shutdowns; the continuous casting agent generates billet agents according to the process parameters of the continuous casting machine, and sends them to direct rolling or hot charging through the lifting baffle from the roller table, or is offline from the continuous casting cooling bed through a tilting machine, a pusher, and a crane and enters the billet storage, and provides billet agents to the connection area agent; the process parameters include operating status, steel type, specification, number of strands, and casting speed.

3. A multi-agent-based casting-rolling interface logistics simulation method according to claim 1, characterized in that The described rolling mill agent is used to simulate the process of rolling a continuous casting billet into steel, including the rolling mill production plan, maintenance plan, and abnormal shutdown; the rolling mill agent receives the continuous casting billet agent from the connection area agent, rolls the continuous casting billet agent into steel according to the rolling mill production plan, or returns the continuous casting billet agent to the connection area agent through the roller table and overhead crane.

4. A method for simulating the logistics of the casting and rolling interface based on multi-agent according to claim 1, characterized in that, The described continuous casting billet agent serves as an intermediate carrier between molten steel and steel, receives the scheduling rules from the scheduling agent, and enters the rolling mill agent or the heating furnace agent in the direct rolling, hot charging, and cold charging modes through the direct rolling roller table sub-agent, hot charging roller table sub-agent, continuous casting billet storage sub-agent, heating furnace sub-agent, and cold charging roller table sub-agent, in combination with the temperature evolution model, and is finally rolled into steel.

5. A multi-agent based casting-rolling interface logistics simulation method according to claim 1, characterized in that, The agent is described by identification, type, knowledge base, rule set, attributes, and parameters; among them, the identification is the number of the agent, which is unique; the type is the category to which the agent belongs and is used to handle the relationships between agents; the knowledge base is the set of knowledge owned by the agent; the rule set is that the agent responds to external signals, receives external inputs, matches them with the rules in the rule set, and outputs externally; the attributes are the fixed parameters of the agent, including the steel grade, specification, and temperature of the continuous casting billet agent; the parameters are the quantities that can be variably regulated in the agent.

6. The method for simulating the logistics at the casting and rolling interface based on multi-agent according to claim 1, characterized in that The scheduling agent obtains the continuous casting production plan and the rolling mill production plan from the continuous casting agent and the rolling mill agent respectively, generates a global goal, decomposes it into local goals, generates scheduling rules according to the global goal and local goals, and executes them through the connection area agent to complete the scheduling task; the scheduling agent receives feedback from other agents through interaction with other agents, and dynamically adjusts the intelligent scheduling model through self-learning and self-adaptation to optimize the logistics process.

7. A computer device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the multi-agent-based continuous casting and rolling interface logistics simulation method as described in any one of claims 1-6.

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