A ship steel plate yard storage operation planning method considering pre-processing time

Abstract

The application provides a ship steel plate yard storage operation planning method considering pretreatment time, which comprises the following steps: collecting the storage sequence of the steel plate, the pretreatment time of the storage steel plate, grouping according to the manufacturing date of the section where the steel plate is located, determining the parameters of the yard, and determining the moving time of the travelling crane between different stacking positions; determining the initial storage sequence of the steel plate and the plate turning result through a heuristic algorithm; setting the pheromone matrix value of the ant colony and the weight of the pheromone value and the heuristic value, adopting the ant colony algorithm, and iteratively obtaining the steel plate storage operation scheme of each stage; determining the plate turning result of the storage operation scheme obtained at each iteration, and updating the optimal storage operation scheme, the pheromone matrix and the weight of the pheromone value and the heuristic value; and judging whether the stopping condition of the method is reached. The method fully considers the pretreatment time information of the steel plate, reasonably plans the storage stacking position of the steel plate, and reduces the plate turning times when the steel plate is discharged.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of steel plate storage, in particular to a ship steel plate yard storage operation planning method considering pretreatment time. BACKGROUND

[0002] For the shipbuilding industry, steel plate is the most important raw material for shipbuilding, and there are a large number of steel plates in the shipyard. Therefore, the extraction and transportation of steel plates has become a major constraint on the shipbuilding capacity of the shipyard. Storage is the first link of shipbuilding, and the storage operation process directly determines the position of the steel plate in the yard. The position of the steel plate in the yard determines the number of plate turning when the steel plate is discharged, which affects the supply of steel plate and thus affects the subsequent production of the ship. Therefore, steel logistics is the first and very important link of ship logistics. Steel plates come from multiple external suppliers of the shipyard, so multiple batches of steel plates need to be stored at the same time. Steel plates need to be pretreated and cut before they can be processed into sections and then into ship sections. However, the storage and discharge times of steel plates are affected by external supply chains, internal production fluctuations of the shipyard, rework, and other factors, and there is great uncertainty in the discharge and storage times of steel plates.

[0003] In the early stage of the industry, the storage, sorting, turning, and extraction of steel plates in the shipyard were mostly completed by manual experience due to the lack of information and intelligent means. However, with such a large amount of work and information, the historical experience of workers cannot be used to obtain the most reasonable operation scheme, resulting in low efficiency in the discharge process of steel plates. Manual and simple rule processing of storage operations cannot consider the impact of steel plate storage on subsequent discharge operations, resulting in increased number of plate turning during discharge, low discharge efficiency, and other problems. Therefore, to overcome the long-term reliance on historical experience of workers for storage operations in existing shipyards, which leads to problems such as high cost, low efficiency, and poor results during discharge in the yard, a computer-based intelligent storage scheme generation method is needed. SUMMARY

[0004] In view of the defects in the prior art, the purpose of the present application is to provide a ship steel plate yard storage operation planning method considering pretreatment time, which fully considers the discharge time, pretreatment time, and other information of the steel plate, and reduces the number of plate turning during discharge by reasonably planning the storage location of the steel plate.

[0005] To solve the above problems, the technical scheme of the present application is as follows:

[0006] A ship steel plate yard storage operation planning method considering pretreatment time, comprising the following steps:

[0007] collecting the storage sequence of the steel plates, the pretreatment time of the storage steel plates, grouping according to the manufacturing date of the section where the steel plate is located, determining the parameters of the stockyard, determining the moving time of the travelling crane between different stacking positions;

[0008] determining the initial storage sequence of the steel plates and the plate turning result by a heuristic algorithm;

[0009] setting the pheromone matrix value of the ant colony and the weight of the pheromone value and the heuristic value, adopting the ant colony algorithm, and iteratively obtaining the steel plate storage operation scheme of each stage;

[0010] determining the plate turning result of the storage operation scheme obtained at each iteration, and updating the optimal storage operation scheme, the pheromone matrix, and the weight of the pheromone value and the heuristic value;

[0011] judging whether the stopping condition of the method is reached.

[0012] Preferably, the step of collecting the storage sequence of the steel plates, the pretreatment time of the storage steel plates, grouping according to the manufacturing date of the section where the steel plate is located, determining the parameters of the stockyard, and determining the moving time of the travelling crane between different stacking positions specifically comprises: for the sorting of the steel plates, first obtaining the number of each storage steel plate and the section information corresponding to each steel plate from the arrival list, finding the manufacturing date of the section where the steel plate is located from the schedule plan, thereby determining the approximate delivery time of each storage steel plate, grouping the steel plates delivered on the same day in the same group according to the approximate delivery time of the steel plates, and sorting the groups according to the delivery time, defining the group with the earliest delivery as the first group, the group with the second earliest delivery as the second group, and so on; determining the parameters of the stockyard, including the number of stacking positions in the stockyard and the capacity of the steel plates that can be stored in each stacking position; determining the moving parameters of the travelling crane, including the time for storing the storage steel plates between different stacking positions and the plate turning time between different stacking positions.

[0013] Preferably, the step of determining the initial storage sequence of the steel plates and the plate turning result by a heuristic algorithm specifically comprises: determining the storage stacking position of the storage steel plates by a heuristic algorithm, starting from the first stacking position, if it is blank, storing it in the stacking position; if the steel plate on the stacking position is full, storing it in the next stacking position, and so on.

[0014] Preferably, the step of setting the pheromone matrix value of the ant colony and the weight of the pheromone value and the heuristic value, adopting the ant colony algorithm, and iteratively obtaining the steel plate storage operation scheme of each stage specifically comprises: establishing a feasible set of plate turning operations, calculating the heuristic value of each plate turning movement by a heuristic rule, combining the heuristic value and the pheromone matrix value, and determining the storage stacking position in the form of roulette.

[0015] Preferably, in the step of updating the optimal storage scheme, pheromone matrix and the weight of pheromone value and heuristic value according to the flipper result of the obtained storage scheme in each iteration, the updating of the pheromone matrix value is calculated according to the following formula for each flipper action of each ant i:

[0016]

[0017] Wherein f i represents the flipper number estimation value of the ant i, λ is a correction value to ensure that the reward value is not too large or too small, is the flipper action set walked by the single ant; the pheromone reward value of the single ant is obtained Then, the pheromone matrix is updated according to the following formula:

[0018]

[0019] Wherein A is the number of ants, ρ is the weight decay value; the updating mode of the pheromone value weight α and the heuristic value weight β is:

[0020]

[0021] α = 1-β

[0022] Wherein t is the iteration number, and MAX_ITER is the maximum iteration value.

[0023] Preferably, in the step of judging whether the stopping condition of the method is reached, the maximum iteration number is set as the stopping condition of the method.

[0024] Preferably, in the step of judging whether the stopping condition of the method is reached, if the stopping condition of the method is reached, the determined steel plate storage sequence and storage scheme are expressed as system output in a standard semantic model.

[0025] Compared with the prior art, the present application proposes a steel plate storage operation optimization scheme based on an ant colony algorithm for the steel plate storage operation process. The method fully considers the information such as the delivery time of the steel plate and the pretreatment time, reasonably plans the storage position of the steel plate and the flipping of the in-storage steel plate, and reduces the flipping number when the steel plate is delivered. BRIEF DESCRIPTION OF DRAWINGS

[0026] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments with reference to the following drawings:

[0027] Figure 1 The flow chart of the ship steel plate yard storage operation planning method considering the pretreatment time of the present application;

[0028] Figure 2 Flow chart of the method for generating the initial storage operation of the steel plate based on the heuristic algorithm;

[0029] Figure 3 Schematic diagram of the judgment method for the blocking plate;

[0030] Figure 4 Flow chart of the method for generating the storage operation scheme of a single iteration. DETAILED DESCRIPTION

[0031] The present application will be described in detail below with specific embodiments. The following examples will help those skilled in the art to further understand the present application, but do not limit the present application in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present application. These are within the scope of protection of the present application.

[0032] Specifically, the present application provides a ship steel plate yard storage operation planning method considering pretreatment time, as shown in Figure 1 The method comprises the following steps:

[0033] S1: Collect the storage sequence of the steel plate, the pretreatment time of the storage steel plate, group according to the manufacturing date of the section where the steel plate is located, determine the parameters of the yard, and determine the moving time of the trolley between different stacking positions;

[0034] Specifically, for the sorting of the steel plate, first get the number of each storage steel plate from the arrival list, and the section information corresponding to each steel plate. Find the manufacturing date of the section where the steel plate is located from the schedule, so as to determine the approximate delivery time of each storage steel plate. According to the approximate delivery time of the steel plate, the steel plates delivered on the same day are grouped in the same group, and the groups are sorted according to the delivery time. The first group is defined as the earliest delivery group, the second group is defined as the second earliest delivery group, and so on.

[0035] Determine the parameters of the yard, including the number of stacking positions in the yard and the capacity of the steel plate that can be stored in each stacking position. Determine the moving parameters of the trolley, including the time of storing the storage steel plate between different stacking positions and the turnover time between different stacking positions.

[0036] S2: Determine the initial storage sequence of the steel plate and the turnover result by a heuristic algorithm;

[0037] Specifically, as shown in Figure 2 First, determine the storage stacking position of the storage steel plate by using a heuristic algorithm. Start from the first stacking position. If it is blank, store it in the stacking position. If the steel plate on the stacking position is full, store it in the next stacking position. Repeat the above steps.

[0038] Furthermore, the number of blocking plates is used as an estimate of the number of outbound flip plates. Figure 3 As shown in the figure, if there is a steel plate with an earlier delivery time under a stack, then the plate is a blocking plate.

[0039] S3: Set the pheromone matrix value of the ant colony and the weights of the pheromone value and the heuristic value, and use the ant colony algorithm to iteratively obtain the steel plate storage operation plan for each stage;

[0040] Specifically, the pheromone τ is an S×S matrix, and each value in the matrix is ​​initialized to 1. The weight of the pheromone value is set to α, and the weight of the heuristic value is set to β. Initially, α = 0.1 and β = 0.9.

[0041] A single iteration process is as follows Figure 4 As shown, assume that a=(s1,s2) represents the flipping action of moving the top steel plate of stack s1 to stack s2. First, the probability p of flipping action a is determined by the following formula: a .

[0042]

[0043] Where τ(a) represents the pheromone value of flip action a, is the inspiration value of the flip action a. The calculation method is as follows:

[0044] If the steel plate being moved is a blocking plate before it is moved and is still a blocking plate after it is moved to the new stack, then The value is calculated as follows:

[0045]

[0046] Where G is the number of groups, is the minimum grouping of the steel plates stored in stack s, g n is the grouping of steel plate n, is the number of steel plates grouped as g.

[0047] If the steel plate being moved is a blocking plate before being moved and becomes a non-blocking plate after being moved to the new stacking position, then The value is calculated as follows:

[0048]

[0049] Where ε is a constant. If the steel plate being moved is a non-blocking plate before and after the movement, then The value is calculated as follows:

[0050]

[0051] If the steel plate to be moved is a non-blocking plate before the movement and becomes a blocking plate after the movement, then The value is calculated in the following manner:

[0052]

[0053] The probability p of the flipping action a is determined a After that, the next step is to select the flipping action in the manner of roulette and determine whether the action is feasible.

[0054] The selected flipping action (s1, s2) needs to satisfy the following two conditions at the same time:

[0055] (1)

[0056] (2)

[0057] If the selected flipping action does not satisfy the above conditions, a flipping action needs to be selected again in the manner of roulette.

[0058] After the flipping action is determined, the next step is to move the uppermost steel plate of the stack position s1 to the stack position s2 in the yard. After that, it is necessary to determine whether there is a steel plate that can be put into the warehouse, and if so, the storage stack position of the steel plate to be put into the warehouse needs to be selected. Assuming that the steel plate to be put into the warehouse is n, g n is grouped. For each alternative stack position s, it is first determined whether it has an empty layer. If so, the probability μ(s) of storing the steel plate is determined according to the following formula,

[0059]

[0060] The stack position with the maximum μ(s) is preferentially selected for storage. After that, the above flipping and storage operations are continued until all the steel plates are put into the warehouse.

[0061] S4: The flipping result of the storage operation scheme obtained in each iteration is determined, and the optimal storage operation scheme, the pheromone matrix, and the weight of the pheromone value and the heuristic value are updated;

[0062] Specifically, for the storage operation scheme obtained by each ant, the number of blocking plates is calculated as an estimate of the number of flipping times according to the method proposed in step S2. If the number of blocking plates obtained by the operation scheme of an ant is less than the optimal result, the optimal result is updated.

[0063] For the update of the pheromone matrix value, for each ant i, the pheromone reward value of each flipping action is calculated according to the following formula:

[0064]

[0065] where fi represents the estimated value of the number of turn plates of the ant i, and λ is a correction value to ensure that the reward value is not too large or too small, is a set of turn plate actions performed by a single ant. The pheromone reward value of a single ant is obtained After that, the next step is to update the pheromone matrix according to the following formula:

[0066]

[0067] where A is the number of ants, and ρ is the weight decay value. The update method of the pheromone value weight α and the heuristic value weight β is as follows:

[0068]

[0069] α = 1 - β

[0070] where t is the number of iterations, and MAX_ITER is the maximum iteration value.

[0071] S5: Determine whether the stopping condition of the method is reached;

[0072] Specifically, if the number of iterations t = MAX_ITER, the algorithm stops; otherwise, continue to perform iterative calculations to obtain the steel plate storage operation scheme at each stage, and set the maximum number of iterations as the stopping condition of the algorithm.

[0073] If the stopping condition of the method is reached, the determined yard storage operation scheme is output according to a specific rule, that is, the determined steel plate storage sequence and storage scheme are expressed as a system output in a standard semantic model. For example, a steel plate storage plan semantic model is established by taking the steel plate number and the stack position number as basic semantic units. The steel plate storage statement = <job number, steel plate number, removal stack position number, storage stack position number>, thereby forming a steel plate storage operation plan including steel plate extraction and turn plate operation. If the steel plate is to be stored, the removal stack position number is -1.

[0074] The specific embodiments of the present application are described above. It should be understood that the present application is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essential content of the present application. In the case of no conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for planning ship steel plate storage operations taking into account pre-processing time, characterized in that: The method comprises the following steps: Collect the order of steel plates entering the warehouse and the pre-processing time of the steel plates entering the warehouse, group them according to the manufacturing date of the segment where the steel plates are located, determine the parameters of the yard, and determine the movement time of the crane between different stacking locations, specifically including: for the sorting of steel plates, first obtain the number of each incoming steel plate and the segment information corresponding to each steel plate from the arrival list, find the manufacturing date of the segment where the steel plate is located from the schedule, and thus determine the outbound time of each incoming steel plate, according to the outbound time of the steel plates, group the steel plates shipped on the same day into the same group, and sort the groups according to the outbound time, define the group with the earliest outbound as the first group, the group with the second earliest outbound as the second group, and so on; determine the parameters of the yard, including the number of stacking locations in the yard and the capacity of steel plates that can be stored in each stacking location; determine the movement parameters of the crane, including the time between storing the incoming steel plates in different stacking locations and the turning time between different stacking locations; Determine the initial storage order and turnover result of steel plates through heuristic algorithm; The pheromone matrix value of the ant colony and the weights of the pheromone value and the heuristic value are set, and the ant colony algorithm is used to iteratively obtain the steel plate storage operation plan for each stage; Determine the flipping result of the warehousing operation plan obtained in each iteration, and update the optimal warehousing operation plan, pheromone matrix, and the weights of pheromone values ​​and heuristic values. For the update of the pheromone matrix value, for each ant i, calculate the pheromone reward value of each flipping action according to the following formula: where f i represents the estimated number of flips by ant i, and λ is the correction value to ensure that the reward value is not too large or too small. is the set of flipping actions that a single ant walks through; get the pheromone reward value of a single ant After that, the pheromone matrix is ​​updated according to the following formula: Where A is the number of ant colonies, ρ is the weight decay value; the update method of pheromone value weight α and heuristic value weight β is: α＝1-β Where t is the number of iterations and MAX_ITER is the maximum iteration value; Determine whether the method's stopping condition has been reached.

2. The method for planning ship steel plate storage yard warehousing operations considering pre-processing time according to claim 1 is characterized in that: The steps of determining the initial storage order and turnover result of the steel plates by using a heuristic algorithm specifically include: using a heuristic algorithm to determine the storage stack of the incoming steel plates, starting from the first stack, if there is a blank, storing it in the stack; if the steel plates on the stack are full, storing them in the next stack, and so on.

3. The method for planning ship steel plate storage yard warehousing operations considering pre-processing time according to claim 1 is characterized in that: The pheromone matrix value of the ant colony and the weights of the pheromone value and the heuristic value are set, and the ant colony algorithm is used to iteratively obtain the steel plate warehousing operation plan for each stage, which specifically includes: establishing a feasible set of flipping operations, calculating the heuristic value of each flipping movement through heuristic rules, combining the heuristic value and the pheromone matrix value and determining the storage stack position in the form of roulette.

4. The method for planning ship steel plate storage yard warehousing operations considering pre-processing time according to claim 1 is characterized in that: In the step of determining whether the stopping condition of the method is reached, a maximum number of iterations is set as the stopping condition of the method.

5. The method for planning ship steel plate storage yard warehousing operations considering pre-processing time according to claim 1 is characterized in that: In the step of determining whether the stopping condition of the method is met, if the stopping condition of the method is met, the determined steel plate warehousing sequence and storage plan are expressed in a standardized semantic model as system output.

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