Integrated planning and scheduling method and system for hot rolling production line based on ant colony optimization

Abstract

The present invention discloses an integrated planning and scheduling method and system for a hot rolling production line based on ant colony optimization, the method comprising the following steps: in the planning stage, according to order requirements and hot rolling process requirements, with the goal of minimizing the width, thickness, hardness and heating time jumps between adjacent slabs, a vehicle path model with bonus collection is constructed; in the scheduling stage, according to slab sorting and heating furnace process requirements, a resource allocation model with limited heating furnace capacity is constructed; an ant colony optimization algorithm integrating heuristic scheduling methods and constraint feedback mechanisms is designed to solve the model. The technical solution is used to uniformly model and solve the hot rolling production plan and heating furnace scheduling, which is conducive to reducing both the hot rolling production cost and the redundant furnace time of the heating furnace.

Description

Technical Field

[0001] The invention belongs to the technical field of production planning and scheduling of hot rolling production lines, and relates to an integrated planning and scheduling method and system for hot rolling production lines based on ant colony optimization. Background Art

[0002] Steel is a basic material that supports the development of the national economy. Heating furnace-hot rolling is the main section of steel manufacturing, which aims to reheat the slabs from the continuous casting machine through the heating furnace and then form steel coils and steel plates that meet the order requirements through continuous rolling. At present, the contradiction between the diversified and personalized requirements of steel product orders and the high energy consumption and long cycle process characteristics of the steel manufacturing process is becoming increasingly prominent, prompting the production management departments of enterprises to implement more efficient planning and scheduling technologies to optimize production and energy costs while meeting the process specifications of each process.

[0003] A typical hot rolling production line includes two main processes: heating furnace and hot rolling. The process flow is as follows: Figure 1 As shown in the figure: the selected slabs in the slab warehouse are sent to the heating furnace for heating in turn. When they reach the specified furnace temperature, they are sent to the hot rolling unit for continuous processing. Usually, the production organization of the hot rolling production line includes the following two stages:

[0004] (1) The dispatcher combines the pre-selected orders into several rolling units in batches according to the rolling mileage of the rollers and the arrangement constraints of adjacent slabs, and establishes an effective connection between the orders and the manufacturing process to achieve the goal of reducing production costs.

[0005] (2) According to the rolling sequence defined by the rolling unit plan, the slabs are allocated to different heating furnaces, and then the time for each slab to enter the furnace, exit the furnace, and go on the hot rolling machine is determined. By reasonably allocating production resources and schedules, the total amount of excess slab time in the furnace and idle time of the rolling mill is minimized, thereby improving production efficiency and reducing energy consumption.

[0006] At present, the mainstream research idea on the hot rolling production scheduling problem is to describe it as a type of traveling salesman problem (TSP) or vehicle routing problem (VRP) with special constraints, and then design an efficient optimization algorithm to solve it. The general method for solving such problems is mainly heuristic algorithms such as genetic algorithm (GA), particle swarm optimization algorithm (PSO) and ant colony optimization algorithm (ACO).

[0007] However, the existing production organization model with separated planning and scheduling ignores the process coupling relationship between the heating furnace and the hot rolling process, making it difficult to achieve global optimization of production and energy costs within the entire process - the hot rolling plan does not take into account the heating furnace process and the heating furnace scheduling has no room for adjustment in the slab sequence. The optimization of the rolling unit plan may result in additional slab waiting time in the furnace and hot rolling idle time when the heating furnace is scheduled. The traditional production organization model with separated planning and scheduling is difficult to further promote the global optimization of production and energy costs. Summary of the invention

[0008] The purpose of the present invention is to provide an integrated planning and scheduling method and system for a hot rolling production line based on ant colony optimization, so as to reduce the redundant furnace time in the heating furnace production process and optimize the algorithm convergence under the condition of ensuring the computational efficiency.

[0009] In order to achieve the above object, the basic scheme of the present invention is: a hot rolling production line integrated planning and scheduling method based on ant colony optimization, comprising the following steps:

[0010] In the planning stage, according to the order demand and hot rolling process requirements, a vehicle routing model with bonus collection is constructed with the goal of minimizing the jump in width, thickness, hardness and heating time between adjacent slabs;

[0011] In the scheduling stage, a resource allocation model with limited heating furnace capacity is constructed according to the slab sorting and heating furnace process requirements;

[0012] An ant colony optimization algorithm that combines heuristic scheduling method and constraint feedback mechanism is designed to solve the model.

[0013] The working principle and beneficial effects of this basic solution are as follows: This technical solution proposes an integrated planning and scheduling mode covering the heating furnace-heating process, and constructs a mathematical model based on constraint optimization. The model is solved by an ant colony optimization algorithm that incorporates the heating furnace heuristic scheduling method and constraint feedback mechanism. The constructed hot rolling production line integrated planning and scheduling model is introduced to uniformly model and solve the hot rolling production plan and heating furnace scheduling, which is conducive to reducing the hot rolling production cost and significantly reducing the redundant furnace time in the heating furnace production process; the designed constrained ant colony optimization algorithm can optimize the algorithm convergence while ensuring computational efficiency.

[0014] Furthermore, the vehicle routing model with bonus collection is:

[0015]

[0016] Among them, minF 1 It represents minimizing the jump penalty between two adjacent slabs and the cost penalty of not entering the slab; is the rolling unit set, k is the serial number of the rolling unit; For the slab order collection, i, j represent the serial number of the slab order; d i,j represents the jump penalty between slabs i and j, α j is the loss cost caused by not selecting order j; y j,k It means that when slab order j is rolled in rolling unit k, y j,k =1; otherwise, y j,k =0.

[0017] The hot-rolling scheduling problem is formulated as a bonus-collecting vehicle routing problem (PCVRP) to facilitate imposing constraints.

[0018] Furthermore, the constraints of the vehicle routing model with bonus collection include:

[0019] Make sure that each slab is assigned to one rolling unit at most once:

[0020]

[0021] It is required that each rolling unit has a virtual slab at the beginning and end:

[0022]

[0023] Make sure that each selected slab has its predecessor and successor slabs, and require that slabs be allocated to all rolling units:

[0024]

[0025] Eliminate subloops using a method based on MTZ (a method for eliminating subloops proposed by Miller Tucker and Zemlin):

[0026]

[0027] Define the order in the hot roll material:

[0028]

[0029]

[0030] Limit the maximum jump in width, thickness, hardness and temperature between two adjacent slabs:

[0031]

[0032]

[0033]

[0034]

[0035] Limit the cumulative length of slabs of the same width:

[0036]

[0037]

[0038] Simultaneous changes in width, hardness, thickness and temperature are prohibited:

[0039]

[0040] Make sure that the total length of the slab assigned to the rolling unit does not exceed its limit:

[0041]

[0042] Define the jump penalty for hot roll and main body parts:

[0043]

[0044]

[0045] Among them, x 0,j,k Indicates that slab j is the adjacent slab after virtual slab 0; x j,0,k Indicates that slab j is the last slab before virtual slab 0; x i,j,k It means that when slabs i and j are in the same rolling unit k, and the two slabs are adjacent, and j is behind i, x i,j,k =1, otherwise, x i,j,k =0;θ i represents the order of slab i in rolling unit k, θ j represents the order of slab j in rolling unit k; J represents the total number of slab orders; z j,k When slab j is rolled as hot roll material in rolling unit k, z j,k =1; otherwise, z j,k =0; a k is the amount of slab in the hot rolling section of rolling unit k; bigM represents a very large positive number; w i represents the width of slab i, w j Indicates the width of slab j; g i Indicates the thickness of order i, g j represents the thickness of order j; h i Indicates the hardness of order i, h j represents the hardness of order j; T i represents the temperature of slab i, T jrepresents the temperature of slab j; ΔW, ΔG, ΔH, ΔT represent the maximum jump of width, hardness, thickness and temperature allowed by the slab respectively; ζ j is the length of adjacent slabs of the same width; Represents slabs of the same width. If slabs i and j have the same width, then otherwise, Represents a slab of the same hardness. If the hardness of slabs i and j is the same, then otherwise, Represents slabs of the same thickness. If the thickness of slabs i and j is the same, then otherwise, Represents the same temperature slab. If the temperatures of slabs i and j are the same, then otherwise, n is the total number of slabs; l i is the length of slab j, is the maximum mileage allowed for rolling unit k; It indicates the width, hardness, thickness and temperature jump penalty between slabs i and j in the hot roller material. It indicates the width, hardness, thickness and temperature jump penalty between slabs i and j in the main material.

[0046] Setting constraints is helpful for solving the objective function.

[0047] Furthermore, the optimal resource allocation model of the heating furnace is:

[0048]

[0049] Among them, minF 2 represents minimizing the excess time of slabs in the furnace; n is the total number of slabs, e i represents the time when slab i is discharged from the furnace, b i represents the time when slab i enters the furnace, RT min,i is the shortest furnace time of slab order i.

[0050] According to the planned slab sequence, the optimal resource allocation model of the heating furnace is constructed to determine the time for the slabs to enter and exit the furnace.

[0051] Furthermore, the constraints of the optimal resource allocation model for the heating furnace include:

[0052] Each slab can be assigned to only one heating furnace:

[0053]

[0054] Ensure the uniqueness of the slab position in the heating furnace:

[0055]

[0056] Constrain the slab to meet the first-in-first-out rule in the heating furnace:

[0057]

[0058]

[0059] They respectively indicate that the heating time of the slab must meet the specified time window requirements:

[0060]

[0061]

[0062] Specifies the total time range for all slabs in the heating furnace stage:

[0063]

[0064]

[0065] Ensure that the heating time of the slab is continuous:

[0066]

[0067] Indicates the capacity limit of the heating furnace:

[0068]

[0069] Define the constraints for continuous processing of slabs within the same rolling unit and the preparation time of adjacent rolling units

[0070] Interval:

[0071]

[0072] Among them, u i,m When slab i is heated in heating furnace m, u i,m =1; otherwise, u i,m =0; M is the set of heating furnaces, M = {1,…,m,…M}; Π k represents the slab sequence contained in rolling unit k, Respectively represent the first and last slab; v ij When slab orders i and j are heated in the same heating furnace and adjacent to each other, v ij =1; otherwise, v ij =0; TL is the slab loading and unloading time, bigM represents a very large positive number; RT max,i represents the longest furnace time of slab order i, τ is the time sequence number, τ=1,…,Γ; w i,τrepresents that slab order i is assigned to the heating furnace for processing at time τ, w i,τ =1; otherwise, w i,τ =0; Q is the heating furnace capacity, r i-1 is the rolling time of slab order i-1; x i-1,i,k It means that when slab orders i-1 and i are in the same rolling unit k, and the two slab orders are adjacent, and i is after i-1, x i-1,i,k =1; otherwise, x i-1,i,k =0; TW represents the rolling mill adjustment time between rolling units.

[0073] The design of the heating furnace scheduling plan is based on the slab rolling information determined in the hot rolling production plan to complete the heating furnace allocation and furnace entry and exit time arrangement for the slab to be rolled.

[0074] Furthermore, the capacity-constrained resource allocation model of the heating furnace is integrated into each evolution process of the hot rolling production schedule, and the objective function of the resource allocation model is used as the constraint condition for the feasible solution of the hot rolling production schedule:

[0075] min x,y,z F 1 ,

[0076] The excess furnace time of the heating furnace scheduling scheme of the rolling unit sequence based on the hot rolling production schedule is limited to within θ, and the hot rolling production schedule and the heating furnace scheduling are coupled in the form of constraints, so as to realize the integrated planning and scheduling IPS of the hot rolling production line:

[0077]

[0078] Among them, F 1 is the objective function of the hot rolling model, i.e., the total penalty for hot rolling process jump, F 2 is the objective function of the heating furnace, i.e., the total excess time of the slab in the furnace, and θ is the limit value of the total acceptable time of the slab in the furnace set by the model.

[0079] The optimal resource allocation model of the heating furnace is integrated into the hot rolling production schedule to ensure the feasibility of the final solution, with multi-objective processing capabilities and strong flexibility.

[0080] Furthermore, an ant colony optimization algorithm that incorporates the heating furnace heuristic scheduling method and constraint feedback mechanism is designed, and the method for solving the model is as follows:

[0081] Based on the probability statistics of the node where the ant is currently located, the slab with the minimum process jump penalty is selected with the maximum probability, and the heuristic information η ij for:

[0082] η ij =1 / d ij

[0083] Among them, d ij is the penalty value of process jump caused when slab j is rolled after slab i;

[0084] The relative weight of the heuristic information α and the relative weight of the pheromone concentration β affect the optimization direction and efficiency of the population from two aspects: the process penalty value information of adjacent rolling of different slabs and the pheromone content on the path; the ants select the next rolling slab according to the probability matrix of the next rolling slab, and the probability P of each slab ij for:

[0085]

[0086] Where t represents the number of iterations; τ ij , τ is Respectively represent the pheromone factors between slab order i and j, s nodes; η ij , η is represents the heuristic information factor between slab orders i and j, s respectively; s represents the slab number; C k is the set of nodes that ant k can access in the next step, that is, the set of slabs that can be rolled next to slab i;

[0087] When solving the hot rolling scheduling model, the allowed list of slabs is updated according to the process jump constraints of adjacent slabs;

[0088] According to the determined rolling unit plan and its slab sequence π, the maximum load priority and minimum load priority rules are used to assign a heating furnace to each slab i, that is, m[i]; the heating furnace is set to be empty in the initial state, that is, the slab has not been put into the heating furnace, where M[i] is the slab number of the i-th slab in the rolling sequence in its assigned heating furnace; then R M[i]-1 and R M[i]-Q are the rolling sequence numbers of the previous slab and the previous Q slabs in the heating furnace where slab i is located, respectively. The forward and reverse scheduling methods are used to determine the time for the slabs to enter and exit the furnace;

[0089] Realize the excess furnace time F of heating furnace scheduling 2 The objective function value F of hot rolling production 1 Constraints and update the optimal solution:

[0090] minimizeF 1 =F 1 +max[(F2-θ),0]*1E7

[0091] Among them, the hot rolling production scheduling plan that meets the preset maximum excess furnace time value θ of the heating furnace is a feasible solution. Otherwise, it is screened out as the worst solution to achieve the update of the IPS optimal solution of the hot rolling production line; E7 is expressed in scientific notation of 10000000;

[0092] When the parameters are initialized, that is, t = 0, no ants pass through any node at present, and the pheromone concentration τ of each path is ij Set to 1; when t≠0, the pheromone concentration of the path passed by the ants needs to be updated accordingly. The pheromone update method for solving the hot rolling model by ant colony optimization is:

[0093]

[0094]

[0095]

[0096] Among them, τ ij (t+1) represents the pheromone factor between i and j when the iteration number is t+1, ρ represents the pheromone concentration volatility coefficient; M is the set of heating furnaces, M = {1, ..., m, ....M}; ψ is the feedback factor of heating furnace scheduling on pheromone update; represents the pheromone factor between nodes i and j when ant m accesses the path at the tth iteration; Q is the capacity of the heating furnace; d i，j represents the jump penalty between slabs i and j, L(i, j) means that slab j is rolled after slab i; Q is the pheromone intensity coefficient;

[0097] The pheromone update of the t+1th iteration depends on the pheromone residual degree of the tth iteration and the path information of the current ant colony. When the excess in-furnace time value F of the heating furnace scheduling in the ant path 2 When it is less than the set threshold value θ, the pheromone of the corresponding path is a superposition effect; otherwise, it is a reduction effect; when it is equal to the threshold value θ, the pheromone volatilization process is performed only based on the pheromone content at time t, and is not affected by the pheromone of the path updated at the current moment.

[0098] Considering the close connection between hot rolling production schedule and heating furnace scheduling of hot rolling production line, the ACO (Ant Colony Optimization) solution framework combined with heating furnace scheduling simulation is used.

[0099] Furthermore, when solving the hot rolling scheduling model, the allowed list of slabs is updated according to the process jump constraints of adjacent slabs. The specific steps are as follows:

[0100] S81, select the widest slab among the uncompiled slabs as the first slab, and obtain its accessible list Ck ;

[0101] S82, select the next slab:

[0102] S821, update the accessible list C of the current slab k ;

[0103] S822, calculate the P of all slabs in the allowed list of the current slab ij , select the slab with the maximum probability;

[0104] S83, complete the production scheduling of the rolling unit:

[0105] S831, if the current rolling unit has not been compiled, that is, the rolling mileage does not exceed the maximum value, repeat step S82;

[0106] S832, the current rolling unit has completed the compilation plan. If the number of rolling units has not reached the compilation target K, repeat steps S82 and S831.

[0107] The evaluation of the constructed hot rolling production schedule is to evaluate the process jump, temperature jump and maximum slab input of the main material part of the rolling unit; after the evaluation, hot roll materials that meet the rolling process constraints are allocated to each rolling unit, and then the heating furnace scheduling constraints are evaluated.

[0108] Furthermore, the method of using the forward scheduling method to determine the slab entering and exiting the furnace is as follows:

[0109] S91, forward charging in hot rolling order:

[0110] When slab i=0, then: b i =0,e i =RT min,i ;

[0111] When i>0 and M[i]=0, the slab is the first slab in the heating furnace, then: b i =0,e i =max{RT min,i ,e i-1 +r i-1 +TL};

[0112] When i>0, and the heating order of the slab M[i]<the capacity Q of the heating furnace where the slab is located, then:

[0113] e i =max{b i +RT min,i ,e i-1 +r i-1 +TL}; express

[0114] At the t-th iteration, when ant m visits a path, the pheromone factor between nodes i and j;

[0115] When i > 0 and M[i] ≥ Q, the reheating furnace that the slab is about to enter is full, then:

[0116] e i = max{b i + RT min,i , e i-1 + r i-1 + TL};

[0117] S92, load the slabs in reverse order according to the hot rolling sequence:

[0118] Slab i is the n-th slab, that is, the last slab i = n. Set the discharging time of the last slab loaded in reverse order as the discharging time of its forward loading, that is, e i = e i , the discharging time of the last slab obtained by forward loading, b i = e i - RT min,i ;

[0119] Load the slabs in reverse order according to the rolling sequence. When i = i - 1 and M[i] = 0, then: e i = e i+1 + r i + TL, b i = e i - RT min,i ;

[0120] Load the slabs in reverse order according to the rolling sequence. When i = i - 1 and M[i] < Q, then:

[0121] When M[i] ≥ Q, then:

[0122]

[0123] S93, calculate the total extra in-furnace time F of the slabs 2 :

[0124]

[0125] The operation steps are simple and convenient for calculation.

[0126] The present invention also provides an integrated planning and scheduling system for a hot rolling production line based on ant colony optimization, including a processing unit. The processing unit obtains the information of the hot rolling production line, executes the method of the present invention, conducts integrated planning and scheduling of the hot rolling production line and transmits it to the hot rolling production line.

[0127] The ant colony optimization method combined with taboo search sets an initial accessible list for all slabs, and during the solution process, it is dynamically updated based on the same width constraint of the rolling unit. The system is used to carry out integrated planning and scheduling of hot rolling production lines, promoting the global optimization of production and energy costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0128] Figure 1 It is a schematic diagram of the process flow of the hot rolling production line in the prior art;

[0129] Figure 2 It is a flow chart of the ant colony optimization algorithm of the hot rolling production line integrated planning and scheduling method based on ant colony optimization of the present invention;

[0130] Figure 3 It is a flow chart of the integrated planning and scheduling method for a hot rolling production line based on ant colony optimization of the present invention.

[0131] Figure 4 It is a system integration diagram of the hot rolling production line integrated planning and scheduling method based on ant colony optimization of the present invention. DETAILED DESCRIPTION

[0132] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0133] In the description of the present invention, it is necessary to understand that the terms "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0134] In the description of the present invention, unless otherwise specified and limited, it should be noted that the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the internal connection between two components. It can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to the specific circumstances.

[0135] The present invention discloses a method for hot rolling production line integrated planning and scheduling (HRPL-IPS) based on ant colony optimization, such as Figure 3 and Figure 4 As shown, the following steps are included:

[0136] In the planning stage, according to the order demand and hot rolling process requirements, a vehicle routing model with bonus collection is constructed with the goal of minimizing the jump in width, thickness, hardness and heating time between adjacent slabs;

[0137] In the scheduling stage, a resource allocation model with limited heating furnace capacity is constructed according to the slab sorting and heating furnace process requirements;

[0138] An ant colony optimization algorithm that combines heuristic scheduling method and constraint feedback mechanism is designed to solve the model.

[0139] The introduction of the constructed integrated planning and scheduling model for the hot rolling production line can significantly reduce the redundant furnace time in the heating furnace production process. Compared with the classical genetic algorithm and particle swarm optimization algorithm, the designed constrained ant colony optimization algorithm has obvious advantages in convergence under the condition of ensuring computational efficiency.

[0140] In a preferred embodiment of the present invention, in view of the significant differences between the heating furnace and hot rolling production processes, mathematical models are constructed based on the process constraints of the heating furnace and hot rolling. The vehicle path model with bonus collection is:

[0141]

[0142] Among them, minF 1 It represents minimizing the jump penalty between two adjacent slabs and the cost penalty of not entering the slab; is the rolling unit set, k is the serial number of the rolling unit; For the slab order collection, i, j represent the serial number of the slab order; d i,j represents the jump penalty between slabs i and j, α j is the loss cost caused by not selecting order j; y j,k It means that when slab order j is rolled in rolling unit k, y j,k =1; otherwise, y j,k =0.

[0143] The constraints for the vehicle routing model with bonus collection include:

[0144] Make sure that each slab is assigned to one rolling unit at most once:

[0145]

[0146] It is required that each rolling unit has a virtual slab at the beginning and end:

[0147]

[0148] Make sure that each selected slab has its predecessor and successor slabs, and require that slabs be allocated to all rolling units:

[0149]

[0150] Eliminate subloops using a method based on MTZ (a method for eliminating subloops proposed by Miller Tucker and Zemlin):

[0151]

[0152] Define the order in the hot roll material:

[0153]

[0154]

[0155] Limit the maximum jump in width, thickness, hardness and temperature between two adjacent slabs:

[0156]

[0157]

[0158]

[0159]

[0160] Limit the cumulative length of slabs of the same width:

[0161]

[0162]

[0163] Simultaneous changes in width, hardness, thickness and temperature are prohibited:

[0164]

[0165] Make sure that the total length of the slab assigned to the rolling unit does not exceed its limit:

[0166]

[0167] Define the jump penalty for hot roll and main body parts:

[0168]

[0169]

[0170] Among them, x 0,j,k Indicates that slab j is the adjacent slab after virtual slab 0; x j,0,k Indicates that slab j is the last slab before virtual slab 0; x i,j,k It means that when slabs i and j are in the same rolling unit k, and the two slabs are adjacent, and j is behind i, x i,j,k =1, otherwise, x i,j,k =0;θ i represents the order of slab i in rolling unit k, θ j represents the order of slab j in rolling unit k; J represents the total number of slab orders; z j,k When slab j is rolled as hot roll material in rolling unit k, z j,k =1; otherwise, z j,k =0; a k is the amount of slab in the hot rolling section of rolling unit k; bigM represents a very large positive number; w i represents the width of slab i, w j Indicates the width of slab j; g i Indicates the thickness of order i, g j represents the thickness of order j; h i Indicates the hardness of order i, h j represents the hardness of order j; T i represents the temperature of slab i, T j represents the temperature of slab j; ΔW, ΔG, ΔH, ΔT represent the maximum jump of width, hardness, thickness and temperature allowed by the slab respectively; ζ j is the length of adjacent slabs of the same width; Represents slabs of the same width. If slabs i and j have the same width, then otherwise, Represents a slab of the same hardness. If the hardness of slabs i and j is the same, then otherwise, Represents slabs of the same thickness. If the thickness of slabs i and j is the same, then otherwise, Represents the same temperature slab. If the temperatures of slabs i and j are the same, then otherwise, n is the total number of slabs; l iis the length of slab j, is the maximum mileage allowed for rolling unit k; It indicates the width, hardness, thickness and temperature jump penalty between slabs i and j in the hot roller material. It indicates the width, hardness, thickness and temperature jump penalty between slabs i and j in the main material.

[0171] By solving the hot rolling production scheduling model, a feasible hot rolling production scheduling plan is obtained, namely the division of rolling units and the rolling sequence of slabs; the design of the heating furnace scheduling plan is based on the slab rolling information determined in the hot rolling production scheduling plan to complete the heating furnace allocation and furnace entry and exit time arrangement of the slabs to be rolled.

[0172] In a preferred embodiment of the present invention, the optimal resource allocation model of the heating furnace is:

[0173]

[0174] Among them, minF 2 represents minimizing the excess time of slabs in the furnace; n is the total number of slabs, e i represents the time when slab i is discharged from the furnace, b i represents the time when slab i enters the furnace, RT min,i is the shortest furnace time of slab order i.

[0175] The constraints of the optimal resource allocation model for the heating furnace include:

[0176] Each slab can be assigned to only one heating furnace:

[0177]

[0178] Ensure the uniqueness of the slab position in the heating furnace:

[0179]

[0180] Constrain the slab to meet the first-in-first-out rule in the heating furnace:

[0181]

[0182]

[0183] They respectively indicate that the heating time of the slab must meet the specified time window requirements:

[0184]

[0185]

[0186] Specifies the total time range for all slabs in the heating furnace stage:

[0187]

[0188]

[0189] Ensure that the heating time of the slab is continuous:

[0190]

[0191] Indicates the capacity limit of the heating furnace:

[0192]

[0193] Define the constraints for continuous processing of slabs within the same rolling unit and the preparation time of adjacent rolling units

[0194] Interval:

[0195]

[0196] Among them, u i,m When slab i is heated in heating furnace m, u i,m =1; otherwise, u i,m =0; M is the set of heating furnaces, M = {1,…,m,…M}; Π k represents the slab sequence contained in rolling unit k, Respectively represent the first and last slab; v ij When slab orders i and j are heated in the same heating furnace and adjacent to each other, v ij =1; otherwise, v ij =0; TL is the slab loading and unloading time, bigM represents a very large positive number; RT max，i represents the longest furnace time of slab order i, τ is the time sequence number, τ = 1, ..., Γ; w i，τ represents that slab order i is assigned to the heating furnace for processing at time τ, w i，τ =1; otherwise, w i，τ =0; Q is the heating furnace capacity, r i-1 is the rolling time of slab order i-1; x i-1，i，k It means that when slab orders i-1 and i are in the same rolling unit k, and the two slab orders are adjacent, and i is after i-1, x i-1，i，k =1; otherwise, x i-1，i，k =0; TW represents the rolling mill adjustment time between rolling units.

[0197] In a preferred embodiment of the present invention, a constraint-based HRPL-IPS model is designed to integrate the capacity-constrained resource allocation model of the heating furnace into each evolution process of the hot rolling production scheduling, and the objective function of the resource allocation model is used as the constraint condition of the feasible solution of the hot rolling production scheduling:

[0198] min x，y，z F 1 ,

[0199] The excess furnace time of the heating furnace scheduling scheme of the rolling unit sequence based on the hot rolling production schedule is limited to within θ, and the hot rolling production schedule and the heating furnace scheduling are coupled in the form of constraints, so as to realize the integrated planning and scheduling (IPS) of the hot rolling production line:

[0200]

[0201] Among them, F 1 is the objective function of the hot rolling model, i.e., the total penalty for hot rolling process jump, F 2 is the objective function of the heating furnace, i.e., the total excess time of the slab in the furnace, and θ is the limit value of the total acceptable time of the slab in the furnace set by the model.

[0202] In a preferred embodiment of the present invention, in order to effectively solve the hot rolling model ACO (Ant Colony Optimization) and avoid the algorithm falling into the local optimum, ACO and TS (Tabu Search Algorithm) are combined, and an accessible list C is set for all slabs under the condition that the width, hardness and thickness of adjacent slabs cannot jump at the same time and the length of slabs with the same width is limited. k , while ensuring the feasibility of the solution, speed up the solution rate. Figure 2 As shown in the figure, an ant colony optimization algorithm is designed that incorporates the heating furnace heuristic scheduling method and constraint feedback mechanism. The method for solving the model is as follows:

[0203] Based on the probability statistics of the node where the ant is currently located, the slab with the minimum process jump penalty is selected with the maximum probability, and the heuristic information η ij for:

[0204] η ij =1 / d ij

[0205] Among them, d ij is the penalty value of process jump (width, hardness and thickness jump) caused by slab j when rolling after slab i. When calculating, the heuristic factor value corresponding to the minimum penalty value is the largest, and the chance of selecting this slab is greater;

[0206] The relative weight of the heuristic information α and the relative weight of the pheromone concentration β affect the optimization direction and efficiency of the population from two aspects: the process penalty value information of adjacent rolling of different slabs and the pheromone content on the path; the ants select the next rolling slab according to the probability matrix of the next rolling slab, and the probability P of each slabij for:

[0207]

[0208] Where t represents the number of iterations; τ ij , τ is Respectively represent the pheromone factors between slab order i and j, s nodes; η ij , η is represents the heuristic information factor between slab orders i and j, s respectively; s represents the slab number; C k is the set of nodes that ant k can visit in the next step, that is, the set of adjacent slabs that can be rolled next to slab i; the larger α is, the more likely the ant will choose an adjacent slab with a smaller penalty value, move faster to the optimization target, and the algorithm will converge faster, but an excessively large α will also cause the algorithm to fall into a local optimum; and β reflects the influence of the pheromone left over from the history of the path on its current path selection. The larger β is, the more the population relies on the guidance of pheromones, the more likely the ant will choose the previous adjacent slab, and the algorithm will converge faster.

[0209] In ACO (Ant Colony Optimization), when ants search for the next node location, the nodes they can choose are actually a dynamically updated set of nodes. The initial accessible list C k The construction basis is: the width, thickness and hardness of adjacent slabs cannot change at the same time; update C k The rule is: the slab length satisfies the remaining mileage of the rolling unit and satisfies the same width and length constraint.

[0210] Therefore, when solving the hot rolling scheduling model, the allowed list of slabs is updated according to the process jump constraints of adjacent slabs;

[0211] According to the determined rolling unit plan and its slab sequence π, the maximum load priority and minimum load priority rules are used to assign a heating furnace to each slab i, that is, m[i]; the heating furnace is set to be empty in the initial state, that is, the slab has not been put into the heating furnace, where M[i] is the slab number of the i-th slab in the rolling sequence in its assigned heating furnace; then R M[i]-1 and R M[i]-Q are the rolling sequence numbers of the previous slab and the previous Q slabs in the heating furnace where slab i is located, respectively. The forward and reverse scheduling methods are used to determine the time for the slabs to enter and exit the furnace;

[0212] Optimal solution update and constraint processing: realizing the excess furnace time F of heating furnace scheduling 2 The objective function value F of hot rolling production 1 Constraints and update the optimal solution:

[0213] minimizeF1 =F 1 +max[(F2-θ),0]*1E7

[0214] Among them, the hot rolling production scheduling plan that meets the preset maximum excess furnace time value θ of the heating furnace is a feasible solution. Otherwise, it is screened out as the worst solution to achieve the update of the IPS optimal solution of the hot rolling production line; E7 is expressed in scientific notation of 10000000;

[0215] Pheromone update: When the parameters are initialized, that is, t = 0, no ants pass through any node at present, and the pheromone concentration of each path is τ ij Set to 1; when t≠0, the pheromone concentration of the path passed by the ants needs to be updated accordingly. The pheromone update method for solving the hot rolling model by ant colony optimization is:

[0216]

[0217]

[0218]

[0219] Among them, τ ij (t+1) represents the pheromone factor between i and j when the iteration number is t+1, ρ represents the pheromone concentration volatility coefficient; M is the set of heating furnaces, M = {1,…,m,…M}; ψ is the feedback factor of heating furnace scheduling on pheromone update; represents the pheromone factor between nodes i and j when ant m accesses the path at the tth iteration; Q is the capacity of the heating furnace; d i,j represents the jump penalty between slabs i and j, L(i,j) means that slab j is rolled after slab i; Q is the pheromone intensity coefficient;

[0220] The pheromone update of the t+1th iteration depends on the pheromone residual degree of the tth iteration and the path information of the current ant colony. When the excess in-furnace time value F of the heating furnace scheduling in the ant path 2 When it is less than the set threshold value θ, the pheromone of the corresponding path is a superposition effect; otherwise, it is a reduction effect; when it is equal to the threshold value θ, the pheromone volatilization process is performed only based on the pheromone content at time t, and is not affected by the pheromone of the path updated at the current moment.

[0221] This technical solution designs an IPS model based on constrained optimization: the hot rolling planning problem is planned as a bonus collection vehicle routing model (PCVRP), which maximizes the number of plates to be queued while minimizing the penalty for process jumps (width, thickness and hardness jumps) within the rolling unit under the condition of determining the number of rolling units.

[0222] According to the planned slab sequence, the optimal resource allocation model of the heating furnace is constructed to determine the time for the slabs to enter and exit the furnace. The improved ant colony optimization algorithm is used to solve the model: the path selection of slab arrangement is carried out using "pheromone" feedback; the resource allocation decision of slabs entering the furnace is made based on the scheduling rules; when the heating furnace scheduling index exceeds the budget threshold, the penalty function is processed.

[0223] In a preferred embodiment of the present invention, when solving the hot rolling production scheduling model, the allowed list of slabs is updated according to the process jump constraints of adjacent slabs, and the specific steps are:

[0224] S81, select the widest slab among the uncompiled slabs as the first slab, and obtain its accessible list C k ;

[0225] S82, select the next slab:

[0226] S821, update the accessible list C of the current slab k (List of slabs that meet the process requirements and can be rolled later);

[0227] S822, calculate the P of all slabs in the allowed list of the current slab ij , select the slab with the maximum probability;

[0228] S83, complete the production scheduling of the rolling unit:

[0229] S831, if the current rolling unit has not been compiled, that is, the rolling mileage does not exceed the maximum value, repeat step S82;

[0230] S832, the current rolling unit has completed the compilation plan. If the number of rolling units has not reached the compilation target K, repeat steps S82 and S831.

[0231] The evaluation of the constructed hot rolling production schedule is to evaluate the process jump, temperature jump and maximum slab input of the main material part of the rolling unit; after the evaluation, hot roll materials that meet the rolling process constraints are allocated to each rolling unit, and then the heating furnace scheduling constraints are evaluated.

[0232] In a preferred embodiment of the present invention, in order to improve the efficiency of the algorithm, the strategy of "heuristic rule + forward and reverse scheduling" is adopted to construct the heating furnace scheduling scheme. That is, firstly, according to the determined rolling unit plan and its slab sequence π, the maximum load priority and minimum load priority rules are respectively used to allocate a heating furnace for each slab i, that is, m[i].

[0233] Among them, the maximum load is given priority, that is, starting from improving the utilization rate of the heating furnace, the heating furnace with the smallest remaining capacity under the current conditions is selected; the minimum load is given priority, that is, considering that the slab can be discharged in time, the heating furnace with the largest remaining capacity under the current conditions is selected; if the heating furnaces are all full at the current moment, the slab selects the heating furnace with the earliest discharge time of the next slab. Then, the forward scheduling method is used to determine the slab entry and discharge time.

[0234] The method of using the forward scheduling method to determine the time for slabs to enter and exit the furnace is:

[0235] S91, forward charging in hot rolling order:

[0236] When slab i = 0 (the first rolled slab), then: b i =0,e i =RT min,i ;

[0237] When i>0 and M[i]=0, the slab is the first slab in the heating furnace, then: b i =0,e i =max{RT min,i ,e i-1 +r i-1 +TL};

[0238] When i>0, and the heating order of the slab M[i]<the capacity Q of the heating furnace where the slab is located, then:

[0239] e i =max{b i +RT min,i ,e i-1 +r i-1 +TL}; express

[0240] The time when heating of the slab preceding slab i in the heating furnace begins;

[0241] When i>0, and M[i]≥Q, the heating furnace that the slab will enter is full, then:

[0242] e i =max{b i +RT min,i ,e i-1 +r i-1 +TL};

[0243] S92, reverse charging in hot rolling order:

[0244] The slab i is the nth slab, that is, the last slab i = n. Set the tapping time of the last slab for reverse charging to the tapping time of its forward charging, that is, e i = e i , the tapping time of the last slab obtained by forward charging, b i = e i - RT min,i ;

[0245] Invert the slabs in the rolling order, i = i - 1. When M[i] = 0, then: e i = e i+1 + r i + TL, b i =

[0246] e i - RT min,i ;

[0247] Invert the slabs in the rolling order, i = i - 1. When M[i] < Q, then:

[0248] When M[i] ≥ Q, then:

[0249]

[0250] S93, calculate the total excess in-furnace time F of the slab 2 :

[0251]

[0252] The present invention also provides an integrated planning and scheduling system for a hot rolling production line based on ant colony optimization, including a processing unit. The processing unit obtains the information of the hot rolling production line, executes the method of the present invention, performs integrated planning and scheduling of the hot rolling production line, and transmits it to the hot rolling production line.

[0253] The ant colony optimization method combined with tabu search sets an initial accessible list for all slabs, and at the same time, during the solution process, it is dynamically updated based on the same-width constraint conditions of the rolling units. Using this system, integrated planning and scheduling of the hot rolling production line are carried out to promote the global optimization of production and energy costs.

[0254] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0255] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. An integrated planning and scheduling method for a hot rolling production line based on ant colony optimization, characterized in that: The steps include: In the planning stage, according to the order demand and hot rolling process requirements, a vehicle routing model with bonus collection is constructed with the goal of minimizing the jump in width, thickness, hardness and heating time between adjacent slabs; In the scheduling stage, a resource allocation model with limited heating furnace capacity is constructed according to the slab sorting and heating furnace process requirements; Design an ant colony optimization algorithm that combines heuristic scheduling methods and constraint feedback mechanisms to solve the model; The vehicle routing model with bonus collection is: Among them, minF1 represents minimizing the jump penalty between two adjacent slabs and the cost loss of the slab not being arranged; is the rolling unit set, k is the serial number of the rolling unit, and K represents the number of rolling units; For the slab order collection, J represents the number of slab orders, i and j represent the serial numbers of slab orders; d i,j represents the jump penalty between slabs i and j, α j is the loss cost caused by not selecting order j; when slab order j is rolled in rolling unit k, y j,k =1; otherwise, y j,k =0; An ant colony optimization algorithm that incorporates the heating furnace heuristic scheduling method and constraint feedback mechanism is designed to solve the model as follows: Perform probability statistics on the node where the ant is currently located, and select the slab with the minimum process jump penalty with the maximum probability, and the inspiration information η ij for: or ij =1 / d i,j Among them, d i,j is the process jump penalty value caused when slab j is rolled after slab i, that is, the jump penalty between slabs i and j; The relative weight α of the heuristic information and the relative weight β of the pheromone concentration affect the optimization direction and efficiency of the population from two aspects: the process penalty value information of adjacent rolling of different slabs and the pheromone content on the path; the ants select the next rolling slab according to the probability matrix of the next rolling slab, and the probability P of each slab ij for: Where t represents the number of iterations; τ ij , τ is Respectively represent the pheromone factors between slab order i and j, s nodes; η ij , η is represents the heuristic information factor between slab orders i and j, s respectively; s represents the slab number; C q is the set of nodes that ant q can access in the next step, that is, the set of slabs that can be rolled next to slab i; When solving the hot rolling scheduling model, the allowed list of slabs is updated according to the process jump constraints of adjacent slabs; According to the determined rolling unit plan and its slab sequence π, the maximum load priority and minimum load priority rules are used to assign a heating furnace to each slab i, that is, m[i]; the heating furnace is set to be empty in the initial state, that is, the slab has not been put into the heating furnace, where M[i] is the slab number of the i-th slab in the rolling sequence in its assigned heating furnace; then R M[i]-1 and R M[i]-Q are the rolling sequence numbers of the previous slab and the previous Q slabs in the heating furnace where slab i is located, respectively. The forward and reverse scheduling methods are used to determine the time for the slabs to enter and exit the furnace; The redundant time F2 of the heating furnace scheduling is constrained on the hot rolling production objective function value F1, and the optimal solution is updated: minimizeF1=F1+max[(F2-θ),0]*1E7 Among them, the hot rolling production scheduling plan that meets the preset maximum excess furnace time value θ of the heating furnace is a feasible solution. Otherwise, it is screened out as the worst solution to achieve the update of the IPS optimal solution of the hot rolling production line; E7 is expressed in scientific notation of 10000000; When the parameters are initialized, that is, t = 0, no ants pass through any node at present, and the pheromone concentration τ of each path is ij Set to 1; when t≠0, the pheromone concentration of the path passed by the ants needs to be updated accordingly. The pheromone update method for solving the hot rolling model by ant colony optimization is: Among them, τ ij (t+1) represents the pheromone factor between i and j when the iteration number is t+1; ρ represents the volatility coefficient of pheromone concentration; M is the set of heating furnaces, ψ is the feedback factor of heating furnace scheduling on pheromone renewal; represents the pheromone factor between nodes i and j when ant q accesses the path at the tth iteration; Q is the capacity of the heating furnace; d i,j represents the jump penalty between slabs i and j, L(i,j) means that slab j is rolled after slab i; Q is the pheromone intensity coefficient; The pheromone update of the t+1th iteration depends on the residual degree of pheromone in the tth iteration and the path information of the current ant colony. When the excess furnace time value F2 of the heating furnace scheduling in the ant's path is less than the set threshold θ, the pheromone of the corresponding path is a superposition effect; otherwise, it is a reduction effect; when it is equal to the threshold θ, the pheromone volatilization process is performed only on the basis of the pheromone content at time t, and is not affected by the pheromone of the path updated at the current moment.

2. The hot rolling production line integrated planning and scheduling method based on ant colony optimization according to claim 1, characterized in that: The constraints of the vehicle routing model with bonus collection include: Make sure that each slab is assigned to one rolling unit at most once: It is required that each rolling unit has a virtual slab at the beginning and end: Make sure that each selected slab has its predecessor and successor slabs, and require that slabs be allocated to all rolling units: Eliminate subloops using the MTZ-based approach: Define the order in the hot roll material: Limit the maximum jump in width, thickness, hardness and temperature between two adjacent slabs: Limit the cumulative length of slabs of the same width: Simultaneous changes in width, hardness, thickness and temperature are prohibited: Make sure that the total length of the slab assigned to the rolling unit does not exceed its limit: Define the jump penalty for hot roll and main body parts: Among them, x 0,j,k Indicates that slab j is the adjacent slab after virtual slab 0; x j,0,k Indicates that slab j is the last slab before virtual slab 0; x i,j,k It means that when slabs i and j are in the same rolling unit k, and the two slabs are adjacent, and j is behind i, x i,j,k =1, otherwise, x i,j,k =0;θ i represents the order of slab i in rolling unit k, θ j represents the order of slab j in rolling unit k; J represents the total number of slab orders; z j,k When slab j is rolled as hot roll material in rolling unit k, z j,k =1; otherwise, z j,k =0; a k is the amount of slab in the hot rolling section of rolling unit k; bigM represents a user-defined extremely large positive number; w i represents the width of slab i, w j Indicates the width of slab j; g i Indicates the thickness of order i, g j represents the thickness of order j; h i Indicates the hardness of order i, h j represents the hardness of order j; T i represents the temperature of slab i, T j represents the temperature of slab j; ΔW, ΔG, ΔH, ΔT represent the maximum jump of width, hardness, thickness and temperature allowed by the slab respectively; ζ j is the length of adjacent slabs of the same width; Represents slabs of the same width. If slabs i and j have the same width, then otherwise, Represents a slab of the same hardness. If the hardness of slabs i and j is the same, then otherwise, Represents slabs of the same thickness. If the thickness of slabs i and j is the same, then otherwise, Represents the same temperature slab. If the temperatures of slabs i and j are the same, then otherwise, n is the total number of slabs, l i is the length of slab i, is the maximum mileage allowed for rolling unit k; It represents the sum of width, hardness, thickness and temperature jump penalty between slabs i and j in the hot roller material. It represents the sum of the width, hardness, thickness and temperature jump penalty between slabs i and j in the main material.

3. The hot rolling production line integrated planning and scheduling method based on ant colony optimization according to claim 2, characterized in that: The optimal resource allocation model of the heating furnace is: Where minF2 represents minimizing the excess time of slabs in the furnace; n is the total number of slabs, e i represents the time of slab order i to be released from the furnace, b i represents the time when slab i enters the furnace, RT min,i is the shortest time that slab i spends in the furnace.

4. The integrated planning and scheduling method for hot rolling production line based on ant colony optimization according to claim 3, characterized in that: The constraints of the optimal resource allocation model for the heating furnace include: Each slab can be assigned to only one heating furnace: Ensure the uniqueness of the slab position in the heating furnace: Constrain the slab to meet the first-in-first-out rule in the heating furnace: They respectively indicate that the heating time of the slab must meet the specified time window requirements: Among them, RT min,i is the shortest furnace time of slab i; Specifies the total time range for all slabs in the heating furnace stage: Ensure that the heating time of the slab is continuous: Indicates the capacity limit of the heating furnace: Define the constraints for continuous slab processing within the same rolling unit and the preparation time interval between adjacent rolling units: Among them, u i,m When slab i is heated in heating furnace m, u i,m =1; otherwise, u i,m =0; M is the heating furnace set, Π k represents the slab sequence contained in rolling unit k, Respectively represent the first and last slab; v ij When slab orders i and j are heated in the same heating furnace and adjacent to each other, v ij =1; otherwise, v ij =0; TL is the loading and unloading time of the slab, bigM represents a user-defined extremely large positive number; RT max,i represents the longest furnace time of slab order i, τ is the time sequence number, τ=1,…,Γ; w i,τ represents that slab order i is assigned to the heating furnace for processing at time τ, w i,τ =1; otherwise, w i,τ =0; Q is the heating furnace capacity, r i-1 is the rolling time of slab order i-1; x i-1,i,k It means that when slab orders i-1 and i are in the same rolling unit k, and the two slab orders are adjacent, and i is after i-1, x i-1,i,k =1; otherwise, x i-1,i,k =0; TW represents the rolling mill adjustment time between rolling units.

5. The integrated planning and scheduling method for hot rolling production line based on ant colony optimization according to claim 4, characterized in that: The capacity-constrained resource allocation model of the heating furnace is integrated into each evolution process of the hot rolling production schedule, and the objective function of the resource allocation model is used as the constraint condition for the feasible solution of the hot rolling production schedule: my x,y,z F1, The excess furnace time of the heating furnace scheduling scheme of the rolling unit sequence based on the hot rolling production schedule is limited to within θ, and the hot rolling production schedule and the heating furnace scheduling are coupled in the form of constraints, so as to realize the integrated planning and scheduling IPS of the hot rolling production line: Among them, F1 is the objective function of the hot rolling model, that is, the total penalty for hot rolling process jump, F2 is the objective function of the heating furnace, that is, the total excess time of the slab in the furnace, and θ is the limit value of the acceptable total time of the slab in the furnace set by the model.

6. The hot rolling production line integrated planning and scheduling method based on ant colony optimization according to claim 5, characterized in that: When solving the hot rolling scheduling model, the allowed list of slabs is updated according to the process jump constraints of adjacent slabs. The specific steps are as follows: S81, select the widest slab among the uncompiled slabs as the first slab, and obtain its accessible list C k ; S82, select the next slab: S821, update the accessible list C of the current slab k ; S822, calculate the P of all slabs in the allowed list of the current slab ij , select the slab with the maximum probability; S83, complete the production scheduling of the rolling unit: S831, if the current rolling unit has not been compiled, that is, the rolling mileage does not exceed the maximum value, repeat step S82; S832, the current rolling unit has completed the compilation plan. If the number of rolling units has not reached the compilation target K, repeat steps S82 and S831.

7. The integrated planning and scheduling method for hot rolling production line based on ant colony optimization according to claim 6, characterized in that: The method of using the forward scheduling method to determine the time for slabs to enter and exit the furnace is: S91, forward charging in hot rolling order: When slab i=0, then: b i =0,e i =RT min,i ; When i>0 and M[i]=0, the slab is the first slab in the heating furnace, then: b i =0,e i =max{RT min,i ,e i-1 +r i-1 +TL}; When i>0, and the heating order of the slab M[i]<the capacity Q of the heating furnace where the slab is located, then: e i =max{b i +RT min,i ,e i-1 +r i-1 +TL}; Indicates the start time of heating the previous slab of slab i in the heating furnace; When i>0, and M[i]≥Q, the heating furnace that the slab will enter is full, then: S92, reverse charging in hot rolling order: Slab i is the nth slab, i.e. the last slab i=n. Set the outgoing time of the last slab in reverse loading to the outgoing time of the last slab in forward loading. The outgoing time of the last slab in forward loading is b i =e i -RT min,i ; When the slab is turned upside down in the rolling order, i = i-1, M[i] = 0, then: e i =e i+1 +r i +TL,b i =e i -RT min,i ; Invert the slab in the rolling order. When i = i - 1 and M[i] < Q, then: e i = e i+1 + r i + TL, When M[i]≥Q, then: S93, calculate the total excess furnace time F2 of the slab:

8. An integrated planning and scheduling system for hot rolling production line based on ant colony optimization, characterized in that: The method comprises a processing unit, wherein the processing unit obtains information of the hot rolling production line and executes the method according to any one of claims 1 to 7, performs integrated planning and scheduling of the hot rolling production line and transmits the planning and scheduling to the hot rolling production line for execution.

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