CN109376438B - Reinforcing steel bar blanking optimization method and device and storage equipment - Google Patents
Reinforcing steel bar blanking optimization method and device and storage equipment Download PDFInfo
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Abstract
The invention discloses a method, a device and a storage device for steel bar blanking optimization, wherein the method comprises the following steps: for the steel bar to be blanked, which meets the requirement that the length of the steel bar to be blanked is greater than the length of the minimum raw material steel bar, directly blanking if the direct blanking condition is met, otherwise, screening the whole steel bar blanking combination if the direct blanking condition is not met, and eliminating the condition that the welding node is positioned in the beam span; and for the steel bars to be blanked, which meet the requirement that the length of the steel bars to be blanked is less than or equal to the length of the minimum raw material steel bar, and the steel bars to be blanked, which have welding nodes in the beam span, dividing the rest steel bars to be blanked into two groups according to a preset splitting threshold, respectively optimizing by using the lingo models, respectively establishing respective lingo models by considering the steel bar waste rate, the number of the welding nodes and the welding node beam span factors, and calculating the optimal solution by using the lingo models. The invention can save material cost, avoid welding nodes in the beam span and reduce labor cost.
Description
Technical Field
The invention relates to a method and a device for optimizing steel bar blanking and storage equipment, and belongs to the technical field of civil engineering.
Background
After various civil engineering construction projects are researched and researched, workers generally adopt an empirical method to carry out steel bar blanking or utilize the existing commercial software to sample steel bars, but the blanking method generally has a large steel bar waste rate which is generally more than or equal to 5%. In a typical 10 ten thousand property project, the total amount of funds wasted is:
100000 50kg (steel quantity/square)/1000 (converted to ton) × 4500 (steel bar market price) × 5% (waste rate) =112.5 ten thousand yuan
In addition, in the steel bar optimization calculation process, the welding node is always a problem which is difficult to solve in the beam span, and even if constraint conditions in the beam span can be given, the optimal solution of the problem is usually difficult to obtain due to complex conditions.
Therefore, the optimization method of the steel bar blanking with lower waste rate is provided, and the economic and social benefits are very obvious.
The optimized blanking of the reinforcing steel bars is a one-dimensional optimized combination problem, and the optimized blanking of the reinforcing steel bars is researched by adopting a simulated annealing algorithm, a genetic algorithm and the like, but the methods are still in the theoretical research level and have various problems when being applied to engineering practice. The subsequent research discusses the problem of steel bar optimized blanking by simplifying and adopting a linear programming algorithm, and in fact, the steel bar optimized blanking in the actual engineering is not a pure linear problem, a solving model meeting the engineering requirements comprises a plurality of nonlinear constraints, and the whole solving model is a nonlinear model. Solving the nonlinear problem with the linear model results in errors or even errors between the optimization results and the actual engineering requirements.
The chinese patent database of 2012, 1-18 th discloses a patent name: the intelligent steel bar screening and blanking method (with the publication number of CN 102322151A): screening a large number of steel bar blanking combinations to be processed by dynamically setting screening conditions, comparing screened preliminary steel bar blanking combination schemes, adjusting optimized combinations, and determining a final steel bar blanking combination scheme. However, the method simulates an empirical screening technology, the foundation of which is not a well-known operational research optimization theory, and a local optimal solution may be found by the method, but a global optimal solution is not obtained, or a final reinforcing steel bar blanking combination scheme is not an optimal scheme. In addition, the method does not consider labor cost, in fact, the labor cost is not a negligible project cost, and when the labor cost such as the cutting times of the steel bars and the welding joints is reduced, the material waste is generally increased, namely, the labor cost is in inverse proportion to the material waste rate; meanwhile, the technical problem that whether the welding node is in the beam span is not considered, the fact that the welding node cannot be located at Liang Kuazhong is a mandatory provision of specification, and the fact that the mandatory provision is not considered is not acceptable.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a method, a device and storage equipment for steel bar blanking optimization, which can save materials and labor cost and ensure that a welding node is not positioned in a beam span.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the invention provides a method for optimizing steel bar blanking, which comprises the following steps:
step A: collecting the length data of all raw material reinforcing steel bars and the length data of reinforcing steel bars to be blanked;
and B: for the steel bar to be blanked which meets the condition that the length of the steel bar to be blanked is larger than the length of the minimum raw material steel bar, the blanking is optimized by adopting the following method:
when the steel bar wave rate after blanking is less than or equal to the preset minimum steel bar wave rate, directly blanking;
otherwise, screening the whole steel bar blanking combination according to the length of the rest raw material steel bars, further optimizing the screened whole steel bar blanking combination, eliminating the condition that the welding node is positioned in the beam span, and obtaining the optimized whole steel bar blanking combination;
and C: for the steel bar to be blanked which meets the requirement that the length of the steel bar to be blanked is less than or equal to the length of the minimum raw material steel bar, and the steel bar to be blanked which meets the requirement that the length of the steel bar to be blanked is greater than the length of the minimum raw material steel bar and has a welding node in a beam span, the blanking is optimized by adopting the following method:
splitting the length of the steel bar to be blanked according to a preset splitting threshold value;
the first situation is as follows: for the steel bars to be blanked, the length of the steel bars to be blanked is larger than or equal to a preset splitting threshold value, a nonlinear lingo model is established and the blanking combination of the whole steel bars is optimized by using the lingo model by taking the minimum waste rate of the steel bars and the fact that a welding node is not in a beam span as a target and taking the maximum length of each residual steel bar as a hard constraint by combining two sections of steel bars, so that a steel bar blanking list and a steel bar cutting method are obtained;
case two: for the reinforcing steel bars to be blanked, the length of the reinforcing steel bars to be blanked is smaller than a preset splitting threshold value, the reinforcing steel bar waste rate is the minimum, the length of each residual reinforcing steel bar is only combined by one section of reinforcing steel bar to form a hard constraint, a nonlinear lingo model is established, the blanking combination of the whole reinforcing steel bar is optimized by using the lingo model, and a reinforcing steel bar blanking list and a reinforcing steel bar cutting method are obtained;
wherein: the length of the residual steel bar = the length of the steel bar to be blanked-the length of the raw material steel bar + the number of steel bar nodes is s, and s represents the loss of the welded nodes.
In a second aspect, the present invention provides a steel bar blanking optimization apparatus, including:
a processor adapted to implement instructions; and
and the storage device is suitable for storing a plurality of instructions, and the instructions are suitable for being loaded by the processor and executing the steps of the reinforcing steel bar blanking optimization method.
In a third aspect, the present invention provides a storage device having stored therein a plurality of instructions adapted to be loaded by a processor and to perform the steps of the foregoing method for optimizing rebar blanking.
Compared with the prior art, the method, the device and the storage equipment for optimizing the steel bar blanking provided by the invention consider a plurality of influence factors such as steel bar waste rate, the number of welding nodes and whether the welding nodes are positioned in a beam span, simulate a manual blanking method, and adopt Matlab to extract the optimal combination of the whole steel bar; the large matrix is cut into a plurality of sub-matrixes, so that the calculation efficiency is improved; establishing an operation research optimization model, solving the optimal solution of the residual steel bars, and obtaining a steel bar cutting method and a residual steel bar blanking method; the steel bar cutting method and the residual steel bar blanking method are optimized, and the number of steel bar welding nodes is reduced; the steel bar blanking method not only controls the material consumption to the maximum extent and reduces the material waste, but also reduces the cutting times and the number of welding nodes and optimizes the number of welding nodes by controlling the total number of the steel bars, thereby greatly reducing the labor cost.
Drawings
Fig. 1 is a flowchart of a method for screening the length combinations of entire reinforcing bars of the length of reinforcing bars to be blanked according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for handling a problem of a welded joint being located in a beam span according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method of matrix splitting provided in accordance with an embodiment of the present invention;
FIG. 4 is a flowchart of a method for optimizing the length combination of the whole steel bar by using a lingo model according to an embodiment of the invention;
fig. 5 is a flowchart of a method for determining whether a welding node is located in a beam span according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
It should be understood that: the beam span in the invention is not a point but a length area, and the area size is as follows: the left and the right of the middle point of the beam extend to the length section with the equivalent height value of the beam.
The reinforcing steel bar blanking optimization method provided by the embodiment of the invention comprises the following steps:
step A: gather all raw and other materials reinforcing bar length and treat unloading reinforcing bar length data to use minimum raw and other materials reinforcing bar length as the threshold value, treat unloading reinforcing bar length data and carry out the split, it is specific: constructing a row matrix A according to the length data of the steel bar to be blanked, wherein the length of the steel bar to be blanked is less than or equal to the length of the minimum raw material steel bar; and constructing a row matrix B according to the length data of the steel bar to be blanked, wherein the length of the steel bar to be blanked is larger than the length of the minimum raw material steel bar.
And B, step B: for the steel bar to be blanked, the length of the steel bar to be blanked is larger than the length of the minimum raw material steel bar; as shown in fig. 1, the following method is adopted to optimize blanking:
the first situation is as follows: when the steel bar wave rate after blanking is less than or equal to the preset minimum steel bar wave rate, directly blanking;
the minimum steel bar waste rate can be preset according to the requirements of a construction party, the matrix B is traversed circularly, the length data of the steel bar to be blanked, which can be blanked directly, is stored into the cutting method matrix C together with the length data of the corresponding raw material steel bar, and the length of the rest steel bar to be blanked is stored into the matrix P.
The second situation: when the steel bar waste rate after blanking is larger than the preset minimum steel bar waste rate, screening the whole steel bar blanking combination according to the length of the rest raw material steel bars, further eliminating the condition that a welding node is positioned in a beam span for the screened whole steel bar blanking combination, and obtaining the optimized whole steel bar blanking combination;
screening the whole steel bar blanking combination corresponding to the length of the steel bar to be blanked from the length data of the remaining raw material steel bar one by one, judging whether the problem that the welding node is in the beam span exists through a discrimination function, if the return value of the discrimination function is false, saving the result to a matrix W, and if the return value of the discrimination function is true, saving the result to a matrix P1 until traversing the matrix P.
As shown in fig. 5, the method for determining whether the welding node is located in the beam span by using the discriminant function includes:
(1) Naming the ith behavior W in the entire rebar length combination matrix W i Line vector, calculate W i The number m of the steel bar sections is included, and whether the number m of the steel bar sections is more than 10 is judged;
(2) If the number m of the steel bar sections is more than 10, the row vector W i Can be disassembled as W i1 、W i2 、…W i10 、W i11 …W i1m Selecting the first 10 numbers W i1 、W i2 、…W i10 Using a recursive method, the full permutation of the 10 numbers is written out and the remaining W is added at the end of each permutation i11 …W i1m Form 10! Arrangement, taking into account the loss of the welded joint, is judged at 10! Whether a certain arrangement exists in the arrangement or not meets the condition that all welding nodes are not in the beam span: if so, then W is replaced with this one permutation i When the judgment is finished, the program jumps out of the judgment function to run; if not, from the second number W i2 Starting with 10 counts, i.e. W i2 、…W i10 、W i11 Write its full array, add the remaining number at the end of each array, make 10! Judging whether the welding joint meets the condition in the beam span or not by arranging, and repeating the steps until all the arrangements are judged;
if all the arrays are judged and the conditions that the welding nodes are in the beam span are met, the fact that the welding nodes are in the beam span in the steel bar welding of the beam is indicated;
(3) If the number m of the steel bar sections is not more than 10, writing the full arrangement of the number m by using a recursion method, judging whether a certain arrangement exists or not, and meeting the requirements of all welding nodesAre not in the beam span situation, and if so, replace W with the permutation i And if not, the welding node in the steel bar welding of the beam is in the beam span.
As shown in fig. 2, the method of excluding the case where the welded joint is located in the beam span includes:
deleting the length data of the raw material reinforcing steel bars with the length less than 9m from the length of the residual raw material reinforcing steel bars, circularly taking out each row in the matrix P1, re-screening the whole reinforcing steel bar length combination of all the lengths of the blanking reinforcing steel bars in the matrix P1, testing whether the problem that the welding nodes are in the beam span exists by adopting a discriminant function, if so, calculating the length of the reinforcing steel bars to be blanked in the row, storing the length of the reinforcing steel bars to be blanked in the matrix A, and if not, storing the whole reinforcing steel bar length combination in a row form in the matrix W. And executing in a loop until the matrix P1 is traversed. And extracting the first row in which the length of the residual steel bar is stored from the matrix W and storing the first row in the matrix S.
Step C: for the steel bar to be blanked which meets the requirement that the length of the steel bar to be blanked is less than or equal to the length of the minimum raw material steel bar, and the steel bar to be blanked which meets the requirement that the length of the steel bar to be blanked is greater than the length of the minimum raw material steel bar and has a welding node in a beam span, the blanking is optimized by adopting the following method:
splitting the length of the steel bar to be blanked according to a preset splitting threshold value: when the length of the residual steel bar is short, the steel bar cannot be welded by two short steel bars, because the length of a single steel bar is at least greater than (35d + s), d is the diameter of the steel bar, and s is the loss of a welding joint. When the length of the residual steel bar is less than 2 (35d + s), the steel bar is usually composed of one steel bar, no welding node is provided, and the problem that the welding node is in the beam span is solved.
For this reason, considering blanking convenience, the splitting threshold is set to be 2 (35d + s), and the matrix A is divided into two matrices A1 and A2. And the length of the steel bars in the matrix A2 is less than or equal to a splitting threshold value.
In order to increase the post-optimization calculation speed and reduce the waste rate of the reinforcing steel bar material, the matrices A1 and A2 should be split, as shown in fig. 3, specifically as follows:
for matrix A1:
storing the length of the raw material steel bar and the length of the residual steel bar into two rows in the same excel file, and respectively arranging the lengths in a descending order;
the excel file with the length of the raw material steel bar and the length of the residual steel bar is cut into a plurality of subfiles, and the requirements are as follows: each subfile comprises 50-60 pieces of residual steel bar length data, and the difference between the total length of the original material steel bars and the total length of the residual steel bars in each subfile is less than or equal to 10.
For matrix A2:
counting the lengths of the reinforcing steel bars to be blanked and the number of the reinforcing steel bars corresponding to the lengths of the reinforcing steel bars to be blanked, wherein the lengths of the reinforcing steel bars to be blanked are less than or equal to a preset splitting threshold value;
establishing a reinforcing steel bar type matrix, wherein the length of reinforcing steel bars to be blanked is stored in a first row, and the number of reinforcing steel bars corresponding to the length of the reinforcing steel bars to be blanked is stored in a second row;
saving the length of the residual raw material steel bar and the length of the residual steel bar into the same excel file, and splitting the excel file into a plurality of subfiles, wherein the requirements are as follows: each subfile comprises 50-60 pieces of length data of the residual steel bars;
dividing the second row by the number of the sub-files to obtain the number of the steel bars to be cut in the sub-matrix according to the length of each steel bar to be cut;
and respectively storing all the sub-matrixes into corresponding excel files.
The first situation is as follows: for the steel bars to be blanked, the length of the steel bars to be blanked is larger than or equal to a preset splitting threshold value, the purpose that the waste rate of the steel bars is minimum and a welding node is not in a beam span is taken as a target, the length of each residual steel bar is combined into hard constraint by two sections of steel bars at most, a nonlinear lingo model is built, the lingo model is used for solving steel bar optimization combination, and a steel bar blanking list and a steel bar cutting method are obtained;
for example: assuming that the loss of a welding node is 0.06m, the length of the steel bar to be blanked is 4.5m, and 9m and 12m of raw material steel bars exist in the length of the remaining raw material steel bars, the obtained steel bar optimal combination can be as follows, with the goal that the waste rate of the steel bars is minimum and the welding node is not in the span of the beam: 3m from a 9m long bar of the raw material and 1.56m from a 12m long bar of the raw material.
As shown in fig. 4, the specific measures are: one steel bar is in a section [35d + s, L/2-H ], the other steel bar is in a section [ L/2+ H, L ], wherein L is a beam span, and H is a beam height;
the established nonlinear lingo model is concretely as follows:
0≤T j ≤1
X ij ＝K ij Y ij +(1-K ij )Z ij
K ij =0 or 1
In the formula: x i,j Expressing the ratio of the length of the jth raw material steel bar in the length of the ith residual steel bar; y is i,j The ratio of the length of the second section of the ith residual steel bar to the length of the jth raw material steel bar is represented; z is a linear or branched member ij The ratio of the length of the first section of the steel bar of the ith residual steel bar to the length of the jth raw material steel bar is represented; t is j Indicating the proportion of the jth raw material steel bar used; a. The j Denotes the jth raw materialThe length of the steel bar; b (i) represents the length of the ith steel bar to be blanked; m represents the total number of the raw material steel bars; n represents the total number of the reinforcing steel bars to be blanked; h represents the beam height; k is ij Is a 0, 1 variable; d represents the diameter of the raw material steel bar.
The second situation: for the reinforcing steel bars to be blanked, the length of the reinforcing steel bars to be blanked is smaller than a preset splitting threshold value, the minimum waste rate of the reinforcing steel bars is taken as a target, the length of each residual reinforcing steel bar is only combined by one section of reinforcing steel bar to form a hard constraint, a nonlinear lingo model is established, the optimal combination of the reinforcing steel bars is solved by using the lingo model, and a reinforcing steel bar blanking list and a reinforcing steel bar cutting method are obtained;
wherein: the length of the residual steel bar = the length of the steel bar to be blanked-the length of the raw material steel bar + the number of steel bar nodes is s, and s represents the loss of the welded nodes.
The non-linear lingo model established in the second case in the step C is concretely as follows:
0≤3 j ≤1
(35d+s)/A j ≤X ij less than or equal to 1 or X ij ＝0
In the formula: x i,j Expressing the ratio of the length of the jth raw material steel bar in the length of the ith residual steel bar; t is j Showing the proportion of the jth raw material steel bar used; a. The j Representing the length of the jth raw material reinforcing steel bar; b (i) represents the length of the ith steel bar to be blanked; m represents the total number of raw material reinforcing steel bars; n represents the total number of the reinforcing steel bars to be blanked; d represents the diameter of the raw material reinforcing bar.
For the matrix S:
for the first row of remaining rebar lengths extracted from the matrix W, namely: and (5) the length of the residual steel bar, recombining the matrix S, and modeling to obtain the optimal steel bar blanking combination. The method comprises the following steps: aiming at the minimum waste of the steel bars, establishing a nonlinear lingo model by using the combination of two steel bars as a maximum length of each residual steel bar as hard constraint, and optimizing the steel bar blanking combination by using the lingo model to obtain an optimized steel bar blanking list and a steel bar cutting method;
aiming at the minimum waste rate of the steel bars, and taking the maximum length of each residual steel bar as a hard constraint by combining two sections of steel bars, compiling a nonlinear lingo model:
x ij not less than 35d s or x ij ＝0
Wherein: x is the number of i,j Representing the length of the jth section of steel bar forming the ith residual steel bar length divided by the length of the jth raw material steel bar; a. The j Representing the length of the jth raw material reinforcing steel bar; b (i) represents the length of the ith steel bar to be blanked; m represents the total number of raw material reinforcing steel bars; n represents the total number of the reinforcing steel bars to be blanked; d represents the diameter of the raw material steel bar; s represents a weld node loss.
And combining all optimized whole steel bar blanking combinations and cutting method matrixes to obtain a total steel bar blanking list and a steel bar cutting method. According to the steel bar blanking list and the steel bar cutting method, steel bar welding joints are optimized, steel bar materials are optimized, and labor cost and material cost are further reduced.
The method for optimizing the blanking of the reinforcing steel bars provided by the invention is further described in detail by combining the specific examples as follows:
the embodiment of the present invention will be further described in detail by taking the item of middle iron as an example. The diameter of the raw material steel bar of the project is 32mm;
the length data of the raw material steel bar is collected as follows: 957 reinforcing steel bars with the length of 20.59m, 1000 reinforcing steel bars with the length of 12m and 1000 reinforcing steel bars with the length of 9m and 1957 reinforcing steel bars with the length of 4.51m are 4864; wherein: 12m and 9m are standard steel bar lengths, 4.51m is the remaining steel bar length of other projects, and 20.59m is the length of the whole customized steel bar; the loss of the welding node is 0.06m;
3087 reinforcing steel bars to be blanked in total are 112, and the specific optimization steps are as follows:
1. whole steel bar length combination for extracting length of steel bar to be blanked
And reading the length data of the raw material steel bar and the length data of the steel bar to be blanked in the data2 by using the matlab, wherein A columns are the length data of the raw material steel bar, and B columns are the length data of the steel bar to be blanked. Selecting minimum value M from 4% B (i), 0.5 and 35d (d is the diameter of the raw material steel bar), comparing all the values in A and B, and directly blanking if A (i) -B (i) is less than or equal to M.
And calculating the blanking combination of the whole steel bar with the length of the rest steel bar to be blanked. When the process is carried out to 658 steps, the steel bars to be blanked with the length of 8.01m are combined by a whole steel bar with the length of 4.51m, and the length of the rest steel bars is 3.56m. 5363 the interval Liang Kuazhong is [ L/2-H, L/2+H ], the beam height is 0.7m, L is the beam width, L is 8.01m, so the interval Liang Kuazhong of the beam is [3.305,4.705], analysis shows that the welding node is located at Liang Kuazhong, so the step is skipped directly and is not treated temporarily. Similar situations also exist: 7.88m steel bars combined by 3.43m, 4.51 m. And solving the blanking combination of the whole steel bar with the length of the steel bar to be blanked, wherein all welding nodes are not in the beam span, storing the blanking combination into a finished Rebar, and storing the residual raw materials into a variable Surplus Material. All the raw material rebars with the length less than 9m are deleted in the surflus material, in this example, only one raw material rebar length data with the length less than 9m is 4.51m, and all the rebars with the length of 4.51m are deleted in the surflus material.
And screening the whole steel bar blanking combination with the length of the steel bar to be blanked again, wherein the whole steel bar blanking combination of 7 steel bars to be blanked is given in the table, and as can be seen from the following table, the original 8.01m is combined by 4.51m and 3.56m, but the welding node is in the beam span, and after the steel bar with the length of 4.51m is removed, the steel bar is directly combined by 8.01m, and the optimization is carried out on the 8.01m subsequently.
Whole steel bar blanking combination meter (unit: m) of 7 steel bars to be blanked
| Length of residual reinforcing bar | 5.51 | 2.63 | 2.63 | 2.63 | 8.01 | 8.01 | 7.88 |
| |
20.59 | 20.59 | 20.59 | 20.59 | 0 | 0 | 0 |
| |
20.59 | 20.59 | 20.59 | 20.59 | 0 | 0 | 0 |
| Section 3 | 20.59 | 12 | 12 | 12 | 0 | 0 | 0 |
| Section 4 | 20.59 | 0 | 0 | 0 | 0 | 0 | 0 |
| Section 5 | 20.59 | 0 | 0 | 0 | 0 | 0 | 0 |
| Section 6 | 20.59 | 0 | 0 | 0 | 0 | 0 | 0 |
| Section 6 | 20.59 | 0 | 0 | 0 | 0 | 0 | 0 |
| Section 7 | 20.59 | 0 | 0 | 0 | 0 | 0 | 0 |
| Section 8 | 20.59 | 0 | 0 | 0 | 0 | 0 | 0 |
| Section 9 | 4.51 | 0 | 0 | 0 | 0 | 0 | 0 |
2. By splitting the matrix, the problem of welding joints in beam spans is solved by classification
In order to solve the problem of welding joints in beam spans, the steel bar matrix to be blanked is divided into 3 sub-matrixes. Firstly, a steel bar matrix to be blanked is divided into a matrix A and a matrix B, the length of all steel bars to be blanked in the matrix B is larger than 4.51m, the rest of the steel bars are divided into the matrix A, and the matrix A is continuously divided into two matrices, wherein the method comprises the following steps: setting a value larger than 2 (35d + s) as a threshold value, wherein the given threshold value is 2.4m, dividing the reinforcing steel bars with the length of 2.4m or more in the matrix A into a matrix A1, dividing the remaining reinforcing steel bars into a matrix A2, and finally dividing the reinforcing steel bar matrix to be blanked into three sub-matrices A1, A2 and B.
The matrix B obtains the whole steel bar combination matrix through a Matlab program, extracts the first column of the whole steel bar combination matrix, constructs a residual steel bar length matrix, splits the matrix into a plurality of sub-matrices, and stores 50-60 files in a folder SubFile. For the matrix A1, the similar segmentation matrix is divided into a plurality of sub-matrices, and the sub-matrices are stored in a plurality of excel files and stored in a SubFile 1. For the matrix A2, the optimized steel bars are shorter, and 1 section of steel bar combination is used as hard constraint in the subsequent optimization calculation, so that the long steel bars and the short steel bars are matched to form better grading, the optimization time can be effectively shortened, and the material waste can be reduced. By adopting the principle, the matrix A2 is divided into a plurality of sub-matrices and stored in an excel file, and the length data of the remaining steel bars in one excel is stored in a SubFile 2.
Data statistical table of residual steel bar length part (unit: m)
3. Steel bar optimization:
for the SubFile folder, because all files do not have the problem that welding nodes are in a beam span, a corresponding steel bar blanking list and a steel bar cutting method can be obtained according to a mathematical model of the optimization matrix S.
For the SubFile1 folder, the minimum waste rate of steel bars is taken as a target, the length of each residual steel bar is combined into hard constraint by two sections of steel bars at most, and a welded node is not Liang Kuazhong, and the concrete measures are as follows: one steel bar is in the interval [35d + s, L/2-H ], the other steel bar is in the interval [ L/2+ H, L ], wherein L is the average value of the lengths of the remaining steel bars, H is the beam height, 0.7m is taken, a nonlinear lingo model is compiled, each excel file in SubFile1 is optimized, and the excel files are stored in each text file with the same name in SubFile 1.
calc:
BeamHeight＝0.1*(@sum(RebarSet2(i):B(i))/@sum(RebarSet2(i):@sign(B(i))))；
@for(links(i,j):YC(i,j)＝(B(i)/2+BeamHeight)/A(j))；
@for(links(i,j):ZL(i,j)＝1.2/A(j))；
@for(links(i,j):ZU(i,j)＝(B(i)/2-BeamHeight)/A(j))；
endcalc
min＝@sum(RebarSet(j):(A(j)*(1-T(j))))；
@for(RebarSet2(i):@sum(RebarSet(j):X(i,j)*A(j))
-(@sum(RebarSet(j):@sign(X(i,j)))-1)*0.06＝B(i))；
@for(RebarSet2(i):@sum(RebarSet(j):@sign(X(i,j)))<＝2)；
@for(RebarSet(j):@sum(RebarSet2(i):X(i,j))＝T(j))；
@for(links(i,j):X(i,j)＝K(i,j)*Y(i,j)+(1-K(i,j))*Z(i,j))；
@for(links(i,j):@BND(YC(i,j),Y(i,j),1))；
@for(links(i,j):@semic(ZL(i,j),Z(i,j),ZU(i,j)))；
@for(RebarSet(j):@BND(0,T(j),1))；
@for(links(i,j):@BIN(K(i,j)))；
For the matrix A2, aiming at minimizing the material waste rate, combining a section of steel bar as a hard constraint, compiling a lingo program, optimizing all excels in the folder SubFile2, and storing the excels in the folder SubFile 2. Because only one section of steel bar is arranged in the model, no welding joint exists, and the problem that the welding joint exists in the beam span does not exist.
calc:
@for(links(i,j):Xb(i,j)＝1.12/A(j))；
endcalc
min＝@sum(RebarSet(j):(A(j)*(1-T(j))))；
@for(RebarSet2(i):@sum(RebarSet(j):X(i,j)*A(j))＝B(i))；
@for(RebarSet2(i):@sum(RebarSet(j):@sign(X(i,j)))＝1)；
@for(RebarSet(j):@sum(RebarSet2(i):X(i,j))＝T(j))；
@for(links(i,j):@semic(Xb(i,j),X(i,j),1))；
@for(RebarSet(j):@BND(0,T(j),1))；
And combining the three optimization results to obtain a final steel bar blanking list and a steel bar cutting method, then performing node optimization, and calculating the steel bar waste rate, wherein the total number of the optimized nodes is 4332, and the steel bar waste rate is 0.59%. Obviously, the steel bar welding joints are few, a large amount of labor cost is saved, meanwhile, the material waste rate is only 0.59%, and the material waste is very little. In addition, as can be seen from a steel bar blanking list, the first steel bar of the two 8.01 steel bars is only composed of one section of steel bar and has no welding node, and the second steel bar welding node is not in a span interval [3.305,4.705], so that the problem that the welding node is in a beam span when the whole steel bar combination is obtained for the first time is solved. Other reinforcing bars are verified in sequence, and the problem that the welding joint is in the beam span does not exist, so that the blanking optimization technology can well save materials and labor cost and can well solve the problem that the welding joint is in the beam span.
Steel bar blanking list
Method for cutting raw material reinforcing steel bar
With reference to the example, the operation of the discriminant function is described as follows:
taking an 8.01m steel bar formed by combining 4.51 and 3.56 as an example, it is obvious that the node falls within the interval [3.305,4.705], which indicates that the welding node in the beam span is caused by the arrangement sequence of the steel bars. The number of the groups of 4.51 and 3.56 is less than or equal to 10, the full arrangement is directly written, the full arrangement is 4.51, 3.56 and 3.56, the first arrangement is verified, the problem that the welding node is in the beam span exists, the second arrangement is verified, the 3.56 falls in the interval [3.305,4.705], the problem that the welding node is in the beam span exists, the full arrangement of the groups of numbers is verified, the problem that the welding node is in the beam span exists in the sequencing of the groups of numbers, and the combination of 4.51 and 3.56 is indicated to cause the problem that the welding node is in the beam span, and the combination is not preferable. Of course, since the 8.01 bars are relatively short and the number of combined bars is small, the discriminant function candeal center problem is very efficient to implement, and in fact, for a long bar, such as the 55.63m bar in this example, consisting of 4 bars in total, 2.63, 20.59, 12, the full array 24 of which is relatively complex to implement. The full array is as follows:
whether all welding nodes in each array are in the beam span is judged respectively, the Liang Kuazhong interval is [27.115,28.515], for the first array 12, 20.59 and 2.63, the welding joint loss of 0.06 is considered, the distances between the middle three welding nodes and the leftmost end are respectively 12, 32.53 and 53.06, obviously, the three numbers are not in the interval [27.115,28.515], that is, the first array meets the condition that all welding nodes are not Liang Kuazhong, the first array is selected as the placing sequence of the reinforcing steel bars, and the inspection of the array after stopping. If the welding nodes of the first arrangement are in the beam span middle area, other arrangements are continuously checked until one arrangement welding node is found out not to be in the Liang Kuazhong area, if all arrangements are checked, the situation that a certain welding node is in the beam span middle area exists in each arrangement indicates that the blanking method is not advisable, and blanking is required again.
The invention also provides a steel bar blanking optimization device, which comprises:
a processor adapted to implement instructions; and
a storage device adapted to store a plurality of instructions adapted to be loaded by a processor and to perform the steps of any of the foregoing rebar optimization methods.
The present invention also provides a storage device having stored therein a plurality of instructions adapted to be loaded by a processor and to perform the steps of any of the foregoing method of rebar optimization.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. The steel bar blanking optimization method is characterized by comprising the following steps:
step A: collecting the length data of all raw material reinforcing steel bars and the length data of reinforcing steel bars to be blanked;
and B: for the steel bar to be blanked which meets the condition that the length of the steel bar to be blanked is larger than the length of the minimum raw material steel bar, the blanking is optimized by adopting the following method:
when the steel bar wave rate after blanking is less than or equal to the preset minimum steel bar wave rate, directly blanking;
otherwise, screening the whole steel bar blanking combination according to the length of the rest raw material steel bars, further optimizing the screened whole steel bar blanking combination, eliminating the condition that the welding node is positioned in the beam span, and obtaining the optimized whole steel bar blanking combination;
step C: for the steel bar to be blanked which meets the requirement that the length of the steel bar to be blanked is less than or equal to the length of the minimum raw material steel bar, and the steel bar to be blanked which meets the requirement that the length of the steel bar to be blanked is greater than the length of the minimum raw material steel bar and has a welding node in a beam span, the blanking is optimized by adopting the following method:
splitting the length of the steel bar to be blanked according to a preset splitting threshold value;
the first situation is as follows: for the steel bars to be blanked, the length of the steel bars to be blanked is larger than or equal to a preset splitting threshold value, a nonlinear lingo model is established and the optimal combination of the steel bars is solved by utilizing the lingo model by taking the minimum waste rate of the steel bars and the condition that a welding node is not in a beam span as a target and taking the maximum length of each residual steel bar as a hard constraint by combining two sections of steel bars, so that a steel bar blanking list and a steel bar cutting method are obtained;
case two: for the reinforcing steel bars to be blanked, the length of the reinforcing steel bars to be blanked is smaller than a preset splitting threshold value, the purpose of minimizing the waste rate of the reinforcing steel bars is taken, the length of each residual reinforcing steel bar is only combined by one section of reinforcing steel bar to form hard constraint, a nonlinear lingo model is built, the reinforcing steel bar optimal combination is solved by using the lingo model, and a reinforcing steel bar blanking list and a reinforcing steel bar cutting method are obtained;
wherein: the length of the residual steel bar = the length of the steel bar to be blanked-the length of the raw material steel bar + the number of the nodes of the steel bar × S, and S represents the loss of the welded nodes.
2. The steel bar blanking optimization method according to claim 1, wherein the method for judging whether the welding node is positioned in the beam span comprises the following steps:
b, calculating the number of steel bar sections contained in the whole steel bar blanking combination screened in the step B;
for the whole steel bar blanking combination with the number of steel bar sections larger than 10:
extracting the first 10 elements and carrying out full arrangement;
the remaining elements not extracted are added at the end of each permutation, constituting 10! An arrangement;
consider the loss of a welded joint, judge 10! Whether a certain arrangement exists in the arrangement satisfies the condition that all welding nodes are not located in the beam span:
if so, replacing the whole steel bar blanking combination by the arrangement;
otherwise, the first 10 elements are re-extracted starting with the second element and fully arranged, and the remaining elements are added at the end of each arrangement, forming a new 10! The new 10! Whether a certain arrangement exists in each arrangement meets the condition that all welding nodes are not positioned in the beam span, and so on until the judgment of all arrangements is finished;
if the welding nodes exist in the beam span in all the arrangements, the welding nodes exist in the beam span in the steel bar welding of the beam;
for the whole steel bar blanking combination with the number of steel bar sections less than or equal to 10: and (3) directly performing full-array calculation, and judging whether a certain array meets the condition that all welding nodes are not in the beam span: if so, replacing the whole steel bar blanking combination by the arrangement; otherwise, the welded joint exists in the beam span in the steel bar welding of the beam.
3. The method for optimizing steel bar blanking according to claim 1, wherein the method for further optimizing the screened whole steel bar blanking combination in the step B comprises:
removing length data of the raw material reinforcing steel bar with the length less than 9m from the length of the residual raw material reinforcing steel bar;
and (5) screening the whole steel bar blanking combination by combining the lengths of the rest raw material steel bars again.
4. The steel bar blanking optimization method according to claim 1, wherein the preset splitting threshold is > 2 (35d + s).
5. The steel bar blanking optimization method according to claim 1, wherein the non-linear lingo model established in case one in the step C is specifically as follows:
0≤T j ≤1
X ij ＝K ij Y ij +(1-K ij )Z ij
K ij =0 or 1
Y i，j The ratio of the length of the second section of the ith residual steel bar to the length of the jth raw material steel bar is represented; z ij The ratio of the length of the first section of the ith residual steel bar to the length of the jth raw material steel bar is represented; t is a unit of j Indicating the proportion of the jth raw material steel bar used; a. The j Representing the length of the jth raw material reinforcing steel bar; b (i) represents the length of the ith steel bar to be blanked; m representsThe total number of raw material reinforcing steel bars; n represents the total number of the reinforcing steel bars to be blanked; h represents the beam height; k is ij Is a 0, 1 variable; d represents the diameter of the raw material steel bar.
6. The steel bar blanking optimization method according to claim 1, wherein the non-linear lingo model established in case two in step C is specifically as follows:
0≤T j ≤1
(35d+s)/A j ≤X ij less than or equal to 1 or X ij ＝0
In the formula: x i，j Expressing the ratio of the length of the jth raw material steel bar in the length of the ith residual steel bar; t is j Indicating the proportion of the jth raw material steel bar used; a. The j Representing the length of the jth raw material reinforcing steel bar; b (i) represents the length of the ith steel bar to be blanked; m represents the total number of raw material reinforcing steel bars; n represents the total number of the reinforcing steel bars to be blanked; d represents the diameter of the raw material steel bar.
7. The method for optimizing blanking of steel bars according to claim 1, wherein in case one, before establishing the nonlinear lingo model, the following process should be performed:
storing the length of the raw material steel bar and the length of the residual steel bar into two rows in the same excel file, and respectively arranging the lengths in a descending order;
the excel file with the length of the raw material steel bar and the length of the residual steel bar is cut into a plurality of subfiles, and the requirements are as follows: each subfile comprises 50-60 pieces of residual steel bar length data, and the difference between the total length of the original material steel bars and the total length of the residual steel bars in each subfile is less than or equal to 10.
8. The steel bar blanking optimization method according to claim 1, wherein in case two, the following process should be performed before the non-linear lingo model is established:
counting the lengths of the reinforcing steel bars to be blanked and the number of the reinforcing steel bars corresponding to the lengths of the reinforcing steel bars to be blanked, wherein the lengths of the reinforcing steel bars to be blanked are less than or equal to a preset splitting threshold value;
storing the length of the residual raw material steel bar and the length of the residual steel bar into the same excel file;
splitting the excel file into a plurality of subfiles, and requiring that: each subfile comprises 50-60 pieces of length data of the residual steel bars;
dividing the number of the reinforcing steel bars corresponding to the length of the reinforcing steel bars to be blanked by the number of the subfiles to obtain the number of the reinforcing steel bars to be distributed in each subfile according to the length of each reinforcing steel bar to be blanked; for the case of incomplete division, the remainder part is assigned to the last subfile.
9. The utility model provides a reinforcing bar unloading optimizing apparatus which characterized in that includes:
a processor adapted to implement instructions; and
a storage device adapted to store a plurality of instructions adapted to be loaded by a processor and to perform the steps of any of claims 1 to 8.
10. A memory device having stored therein a plurality of instructions adapted to be loaded by a processor and to carry out the steps of any of claims 1 to 8.
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2018
- 2018-04-26 CN CN201810383424.9A patent/CN108360890A/en active Pending
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| Publication number | Publication date |
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| CN108360890A (en) | 2018-08-03 |
| CN109376438A (en) | 2019-02-22 |
| CN108999447A (en) | 2018-12-14 |
| CN109284858B (en) | 2021-10-22 |
| CN109284858A (en) | 2019-01-29 |
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