CN111507527A - Furniture blanking typesetting optimization method considering raw material diversity and uncertainty - Google Patents
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Abstract
The invention discloses a furniture blanking typesetting optimization method considering raw material diversity and uncertainty, which relates to the field of furniture blanking typesetting, and comprises the following steps: sorting the input part parameters; generating N sub-problems of three length combinations according to the length range of the raw material; calculating the quantity of raw materials required under each length combination according to the quantity proportion of each length combination and the three self-defined lengths; in each subproblem, performing typesetting optimization on raw materials of all parts under each length combination to obtain N typesetting results; and searching and iterating the N typesetting results by a heuristic algorithm, and outputting an optimal typesetting result. According to the method and the device, under the condition that the length of the raw materials is unknown, the length combination of the most saved raw materials can be obtained and the specific typesetting scheme of the part can be generated at the same time according to the user-defined length range and the raw material quantity proportion requirement, so that the production efficiency is improved, and the waste of the raw materials is reduced.
Description
Technical Field
The invention relates to the field of furniture blanking typesetting, in particular to a furniture blanking typesetting optimization method considering the diversity and uncertainty of raw materials.
Background
In the current furniture production industry, the order generation, the analysis, the material selection and the typesetting during the blanking are all completed manually. The biggest difference between the furniture blanking and the common metal cutting blanking lies in the particularity of the raw materials. The standardization of metal raw materials is perfect, the raw wood materials are generally adopted for the furniture blanking, and the raw wood materials are likely to be internally corroded in the earliest treatment process, so that the specification of the furniture raw materials cannot be fixed. The raw materials obtained by the furniture processor are not of the same specification, but rather, the specification and quantity of the raw materials required are planned according to the product of each order, and the blanking layout is planned to reduce the waste raw wood material. The material supplier will cut the log material according to the material specifications and quantities required by the furniture processor, and such a procedure can generate raw material orders in a shorter time and reduce waste material by manual planning in the case of smaller orders. However, once the order integration is large, the speed of manual planning becomes relatively slow, and it is difficult to optimize the waste simultaneously. Most of the existing blanking software typesets metal raw materials and other materials with relatively fixed raw material specifications, and optimizes and calculates the quantity of the finally required materials. However, due to the particularity of the raw wood material, the raw wood material can be subjected to blanking optimization according to the fixed raw material alone, and the requirements of the furniture industry cannot be met. Therefore, a method for automatically generating the required material specification and quantity according to the order and planning the blanking and typesetting on the basis of reducing the waste amount is needed.
Disclosure of Invention
Aiming at the problems and the technical requirements, the invention provides a furniture blanking typesetting optimization method considering the diversity and uncertainty of raw materials, and the technical scheme of the invention is as follows:
the furniture blanking typesetting optimization considering the diversity and uncertainty of raw materials comprises the following steps:
sorting part parameters to ensure that the width and the height of all parts are consistent, and sorting the parts according to the length, wherein the part parameters comprise the number and the length of the required parts;
the method comprises the steps of obtaining a length range of raw materials, dividing the length of the raw materials into a long material interval, a middle material interval and a short material interval according to the length range, randomly selecting the length of one raw material from the long material interval, the middle material interval and the short material interval to form a subproblem, and generating N subproblems with three length combinations according to the difference of randomly selected raw material lengths;
acquiring the quantity expected proportion of the raw materials of the three length combinations, and calculating the initial quantity of the raw materials of the three length combinations for each subproblem according to the quantity expected proportion and the total length of the part;
in each subproblem, performing typesetting optimization on all input parts on three length combined raw materials to obtain N typesetting results, wherein the typesetting is carried out according to the number and the length of the parts and the initial number of the three length combined raw materials;
and searching and iterating the N typesetting results by a heuristic algorithm, and outputting an optimal typesetting result.
The further technical scheme is that each subproblem calculates the initial quantity of the raw materials with three length combinations according to the quantity expected proportion and the total length of the parts, and the method comprises the following steps:
setting a desired quantity of long material, a desired quantity of medium material and a desired quantity of short material as a: b: c, wherein each subproblem is based on a desired ratio of quantity a: b: c and total length L of all partsTCalculating initial quantities a × k, b × k and c × k of three length combined raw materials, wherein k is a scale factor and k is an integer, wherein a × k represents the initial quantity of long materials, b × k represents the initial quantity of medium materials, c × k represents the initial quantity of short materials, and when the initial quantities are equal to the initial quantities of the short materials, the initial quantities of the long materials are calculated
When k is 1, when
When the temperature of the water is higher than the set temperature,
symbol
Indicating a rounding down.
The further technical scheme is that typesetting optimization is carried out on all input parts on three length combination raw materials to obtain N typesetting results, and the method comprises the following steps:
when each part is typeset, one length interval raw material capable of accommodating the length of the part is preferably selected, and when the part is arranged in one length interval raw material, the remaining length of the one length interval raw material is the least of all three length combination raw materials capable of accommodating the length of the part;
in the typesetting process, if a certain part cannot be discharged into any length interval raw material, newly adding the raw material, wherein the length of the newly added raw material is equal to or more than the length of the certain part and is closest to the length of the certain part in the three length combined raw materials;
and obtaining N typesetting results after the typesetting of all the parts is finished, wherein the N typesetting results comprise the total length of N used raw materials, the number of the raw materials and a specific typesetting scheme on each raw material.
The further technical scheme is that the number of the raw materials is equal to the sum of the initial number of the raw materials with the three-length combination, or when the raw materials are added in the typesetting process, the number of the raw materials is equal to the sum of the initial number of the raw materials with the three-length combination plus the added number of the raw materials.
The further technical scheme is that the searching and iteration of the heuristic algorithm is carried out on the N typesetting results, and the method comprises the following steps:
acquiring the total length of N used raw materials, determining a preset number, selecting the preset number of subproblems with the minimum total length of the used raw materials from the total length of the N used raw materials, performing iterative optimization on the subproblems through a genetic algorithm to obtain the preset number of subproblems after iterative optimization, and deleting the remaining subproblems;
judging whether a preset iteration number is reached, if not, combining the sub-problems after the iteration optimization and the original sub-problems with the preset number to form new sub-problems, and in the new sub-problems, executing the step of generating new N sub-problems with three length combinations according to the difference of randomly selected raw material lengths again; if so, the final output uses the raw material length with the least length and can accommodate the raw material length combination of all the parts and the specific typesetting scheme of all the parts on the raw material length combination.
The further technical scheme is that a preset number of subproblems with the minimum total length of used raw materials are selected from the total lengths of N used raw materials and are subjected to genetic algorithm iterative optimization, and the genetic algorithm iterative optimization comprises the following steps: and randomly selecting the lengths of the raw materials belonging to the same length interval from the selected sub-problems with the preset number, exchanging the lengths of the raw materials to obtain the sub-problems with the preset number after iterative optimization, and randomly generating a plurality of new sub-problems, so that the total number of the selected sub-problems with the preset number, the sub-problems with the preset number after iterative optimization and the randomly generated sub-problems is N.
The beneficial technical effects of the invention are as follows:
according to the method, under the condition that the length of raw materials is unknown, N raw material length combinations can be obtained and a specific typesetting scheme of parts can be generated at the same time according to the requirements of a user-defined raw material length range and a quantity expected proportion, the optimal typesetting result of each iteration is screened out through iterative optimization of a genetic algorithm, the optimal typesetting result and the original solution are combined to form a new sub-problem, the final part typesetting result is output through repeated iterative calculation, the final part typesetting result comprises the raw material length combination which has the least raw material length and can accommodate all the parts and the specific typesetting scheme of all the parts on the raw material length combination, the solving speed is high, the second level can be basically controlled, the production efficiency can be improved by using the typesetting optimization method, the waste of the raw materials is reduced, and the production cost is reduced.
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Fig. 1 is a schematic flow chart of a furniture blanking layout optimization method provided by the present application.
Detailed Description
The following further describes the embodiments of the present invention with reference to the drawings.
The application discloses a furniture blanking typesetting optimization method considering raw material diversity and uncertainty, wherein a flow schematic diagram of the method is shown in fig. 1, and the method specifically comprises the following steps:
step 1: and sorting the part parameters to ensure the width and height of all parts to be consistent, and sequencing the parts according to the length, wherein the part parameters comprise the number and the length of the required parts. Optionally, sorting is carried out according to the length of the parts from large to small, and typesetting is carried out according to the sorting sequence.
Step 2, obtaining the length range of the raw materials, and dividing the length of the raw materials into long material intervals according to the self definition of the length range [ Lmin,Lmax]Middle material interval [ Mmin,Mmax]And short material interval [ S ]min,Smax]From the long strand interval [ Lmin,Lmax]Middle material interval [ Mmin,Mmax]And short material interval [ S ]min,Smax]Wherein, randomly selecting the length of a raw material to form a subproblem, and generating N subproblems of three length combinations according to the difference of the randomly selected raw material lengths, namely, each subproblem comprises a length array { L, M, S } of the raw materials in the length interval, wherein L∈ [ L ]min,Lmax]，M∈[Mmin,Mmax]，S∈[Smin,Smax]。
And 3, acquiring the quantity expected proportion of the raw materials combined by the three lengths, namely the expected quantity of the long materials, the expected quantity of the medium materials and the expected quantity of the short materials, namely a: b: c, wherein each subproblem is based on the quantity expected proportion a: b: c and the total length L of all partsTCalculating initial quantities a × k, b × k and c × k of three length combined raw materials, wherein k is a scale factor and k is an integer, wherein a × k represents the initial quantity of long materials, b × k represents the initial quantity of medium materials, c × k represents the initial quantity of short materials, and when the initial quantities are equal to the initial quantities of the short materials, the initial quantities of the long materials are calculated
When k is 1, when
When the temperature of the water is higher than the set temperature,
symbol
Indicating a rounding down.
And 4, step 4: in each subproblem, performing typesetting optimization on all input parts on three length combination raw materials to obtain N typesetting results, wherein the typesetting is carried out according to the number and the length of the parts and the initial number of the three length combination raw materials.
The method specifically comprises the following steps: each part is typeset according to the sorting sequence of the lengths of the parts from large to small, one length interval raw material capable of accommodating the length of the next part is preferentially selected, and when the parts are arranged in the length interval raw material, the remaining length of the length interval raw material is the least of all three length combination raw materials capable of accommodating the length of the part.
In the typesetting process, if a certain part cannot be discharged into any length interval raw material, namely the remaining lengths of the three length combination raw materials are all smaller than the length of the part, the new raw material is added, and the length of the new raw material is the length interval raw material which is more than or equal to the length of the part and is closest to the length of the part in the three length combination raw materials.
And obtaining N typesetting results after the typesetting of all the parts is finished, wherein the N typesetting results comprise the total length of N used raw materials, the number of the raw materials and a specific typesetting scheme on each raw material. Wherein the number of raw materials is equal to the sum of the initial numbers of the three length combination raw materials, or, when the raw materials are added in the typesetting process, the number of raw materials is equal to the sum of the initial numbers of the three length combination raw materials plus the added number of raw materials.
And 5: and searching and iterating the N typesetting results by a heuristic algorithm, and outputting an optimal typesetting result.
The method specifically comprises the following steps:
step 5.1: acquiring total lengths of N used raw materials, optionally, sorting the total lengths of the used raw materials in an ascending order, determining a predetermined number, selecting a predetermined number of sub-problems with the minimum total length of the used raw materials from the total lengths of the N used raw materials, performing genetic algorithm iterative optimization on the sub-problems to obtain the predetermined number of sub-problems after iterative optimization, and deleting the remaining sub-problems. And randomly selecting the lengths of the raw materials belonging to the same length interval from the selected sub-problems with the preset number, exchanging the lengths of the raw materials to obtain the sub-problems with the preset number after iterative optimization, and randomly generating a plurality of new sub-problems, so that the total number of the selected sub-problems with the preset number, the sub-problems with the preset number after iterative optimization and the randomly generated sub-problems is N. For example, conventionally, a predetermined number of sub-problems with a minimum total length of the raw material of 20% are selected, the remaining 80% of the sub-problems are deleted, 20% of the predetermined number of sub-problems after iterative optimization are generated, and then 60% of new sub-problems are randomly generated.
Step 5.2: and judging whether the preset iteration times are reached.
If not, combining the sub-problem after the iterative optimization and the original sub-problems with the preset number to form a new sub-problem. In the new sub-problem, the step of randomly selecting the different lengths of the raw material to thereby generate new N sub-problems of the three length combinations is performed again.
If so, the final output uses the raw material length with the least length and can accommodate the raw material length combination of all the parts and the specific typesetting scheme of all the parts on the raw material length combination.
The foregoing is illustrated by way of example in which:
step 1: and (3) sorting part parameters, wherein the part parameters comprise 1 part with the length of 13m, 2 parts with the length of 18m and 3 parts with the length of 27m, the width and the height of all the parts are ensured to be 1m, and the parts are sorted from large to small according to the lengths of the parts.
Step 2: the method comprises the steps of obtaining a length range [5,35] of raw materials, dividing the length of the raw materials into a long material interval [25,35], a medium material interval [15,25) and a short material interval [5,15) according to the length range, randomly selecting the length of one raw material from the long material interval, forming a subproblem, and generating N subproblems of three length combinations according to the difference of randomly selected raw material lengths, wherein the subproblems comprise {25, 20,14}, {27, 24,10}, {30, 18,7}, {35, 15,5} … ….
And step 3: the desired ratio of the number of combined raw materials of the three lengths, 3:2:1, is obtained, wherein,desired number of long material, desired number of medium material, desired number of short material, 3:2:1, each subproblem according to desired ratio of number 3:2:1 and total length of all parts LT130, the initial number of combined raw materials of three lengths, for example in the sub-problem of {35, 15,5}, is calculated
If the scale factor k is 1, the initial quantities of the three length combined raw materials are 3, 2 and 1, wherein 3 represents the initial quantity of the long material, 2 represents the initial quantity of the medium material, and 1 represents the initial quantity of the short material.
And 4, step 4: each part is typeset according to the sorting order of the lengths of the parts from large to small, the typesetting order of the parts is [27,27,27,18,18,13], for example, in the sub-problem of {35, 15,5}, a raw material with the length of 35m and capable of accommodating the length of the part is preferentially selected, and when the parts are arranged in the raw material with the length of 35m, the remaining length of the raw material in the length interval is the minimum of all the raw materials with the three lengths capable of accommodating the length of the part.
For example, in the composing process of the sub-problem {35, 15,5}, after the part with the part length of 27m is arranged, 2 parts with the length of 18m cannot be arranged into the raw materials with the lengths of 15m and 5m, namely, the remaining lengths of the three length combination raw materials are smaller than the length of the part, 2 raw materials with the length of 20m are newly added, and the length of the newly added raw materials is ensured to be the raw material with the length interval which is more than or equal to the length of the part and is closest to the length of the part in the three length combination raw materials.
And obtaining N typesetting results after the typesetting of all the parts is finished, wherein the N typesetting results comprise the total length of N used raw materials, the number of the raw materials and a specific typesetting scheme on each raw material. Wherein the number of raw materials is equal to the sum of the initial numbers of the three length combination raw materials, or, when the raw materials are added in the typesetting process, the number of raw materials is equal to the sum of the initial numbers of the three length combination raw materials plus the added number of raw materials.
For example, in the sub-problem of {35, 15,5}, the specific typesetting scheme is: 3 parts with the length of 27m are arranged on 3 raw materials with the length of 35m, 2 parts with the length of 18m are arranged on 2 newly added raw materials with the length of 20m, and 1 part with the length of 13m is arranged on 1 newly added raw material with the length of 13 m. The number of raw materials was 3 raw materials of 35m, 2 raw materials of 20m and 1 raw material of 13m, respectively, and the total length of the raw materials used was 193 m.
Step 5.1: the method comprises the steps of obtaining the total length of 10 used raw materials, sequencing the raw materials in an ascending order, selecting 2 sub-problems with the front total length sequencing of the raw materials, performing iterative optimization of a genetic algorithm on the sub-problems, and deleting the remaining 8 sub-problems. For example, 10 subproblems are {25, 20,14}, {27, 24,10}, {30, 18,7}, {35, 15,5} … …, respectively, then the top 2 subproblems with the total length of raw materials are {25, 20,14} and {27, 24,10}, when iterative optimization of the genetic algorithm is performed, the lengths of the raw materials (for example, the selected middle material interval) belonging to the same length interval are randomly selected to be interchanged to obtain 2 subproblems {25, 24,14} and {27, 20,10} after iterative optimization, 6 new subproblems are randomly generated, so that the total number of the 2 subproblems screened, the 2 subproblems after iterative optimization and the 6 subproblems generated randomly is 10, and the remaining 8 subproblems {30, 18,7}, {35, 15,5} … … are deleted.
Step 5.2: and judging whether the preset iteration times are reached.
If not, combining the 2 sub-problems {25, 24,14} and {27, 20,10} after the iterative optimization, the 2 sub-problems {25, 20,14}, {27, 24,10} which are optimized originally and the 6 newly generated random sub-problems to form a new sub-problem. In the new sub-problem, the step of randomly selecting the different lengths of the raw material to thereby generate new N sub-problems of the three length combinations is performed again.
If so, the final output uses the raw material length with the least length and can accommodate the raw material length combination of all the parts and the specific typesetting scheme of all the parts on the raw material length combination.
What has been described above is only a preferred embodiment of the present application, and the present invention is not limited to the above embodiment. It is to be understood that other modifications and variations directly derivable or suggested by those skilled in the art without departing from the spirit and concept of the present invention are to be considered as included within the scope of the present invention.
Claims (6)
1. The furniture blanking typesetting optimization method considering the diversity and uncertainty of raw materials is characterized by comprising the following steps of:
sorting part parameters to ensure that the width and the height of all parts are consistent, and sequencing the parts according to the length, wherein the part parameters comprise the number and the length of the required parts;
the method comprises the steps of obtaining a length range of raw materials, dividing the length of the raw materials into a long material interval, a middle material interval and a short material interval according to the length range, randomly selecting the length of one raw material from the long material interval, the middle material interval and the short material interval to form a subproblem, and generating N subproblems with three length combinations according to the different randomly selected lengths of the raw materials;
acquiring the quantity expected proportion of the raw materials of the three length combinations, and calculating the initial quantity of the raw materials of the three length combinations according to the quantity expected proportion and the total length of the part for each subproblem;
in each subproblem, performing typesetting optimization on all input parts on the three length combination raw materials to obtain N typesetting results, wherein the typesetting is based on the number and the length of the parts and the initial number of the three length combination raw materials;
and searching and iterating the N typesetting results by a heuristic algorithm, and outputting an optimal typesetting result.
2. The method of claim 1, wherein each sub-problem calculates an initial quantity of the three length combined stock materials from the quantity desired ratio and a total length of the part, comprising:
setting the expected quantity of the long material: the expected quantity of the medium materials: the desired number of short materials is a: b: c, each subproblem is in accordance with the desired ratio of number a: b: c and all partsTotal length LTCalculating the initial quantities of the three length combined raw materials a × k, b × k and c × k, k being a scale factor and k being an integer, wherein a × k represents the initial quantity of the long material, b × k represents the initial quantity of the medium material, c × k represents the initial quantity of the short material, and when the initial quantities are equal to the total quantity of the short material, the initial quantities are calculated
When k is 1, when
When the temperature of the water is higher than the set temperature,
symbol
Indicating a rounding down.
3. The method according to claim 1, wherein performing layout optimization on all input parts on the three length combined raw materials to obtain N layout results comprises:
when each part is typeset, one length section raw material capable of accommodating the length of the part is preferentially selected, and when the part is arranged in the one length section raw material, the remaining length of the one length section raw material is the minimum of all three length combination raw materials capable of accommodating the length of the part;
in the typesetting process, if a certain part cannot be discharged into any length interval raw material, newly adding the raw material, wherein the length of the newly added raw material is the length interval raw material which is more than or equal to the length of the certain part and is closest to the length of the certain part in the three length combined raw materials;
and obtaining N typesetting results after the typesetting of all the parts is finished, wherein the N typesetting results comprise the total length of N used raw materials, the number of the raw materials and a specific typesetting scheme on each raw material.
4. The method of claim 3, wherein the number of raw materials is equal to the sum of the initial number of the three length combined raw materials or, when adding raw materials during typesetting, the number of raw materials is equal to the sum of the initial number of the three length combined raw materials plus the number of added raw materials.
5. The method of claim 3, wherein the performing heuristic search and iteration on the N typeset results comprises:
acquiring the total length of the N used raw materials, determining a preset number, selecting the preset number of sub-problems with the minimum total length of the used raw materials from the total length of the N used raw materials, performing iterative optimization on the sub-problems through a genetic algorithm to obtain the preset number of sub-problems after iterative optimization, and deleting the remaining sub-problems;
judging whether a preset iteration number is reached, if not, combining the sub-problem after the iteration optimization and the original sub-problems with the preset number to form a new sub-problem, and in the new sub-problem, executing the step of generating N new sub-problems with three length combinations according to the difference of the randomly selected raw material lengths again; if so, the final output uses the raw material length with the least length and can accommodate the raw material length combination of all the parts and the specific typesetting scheme of all the parts on the raw material length combination.
6. The method according to claim 5, wherein the selecting and performing iterative genetic algorithm optimization on a predetermined number of subproblems with the smallest total used raw material length from the N total used raw material lengths comprises: and randomly selecting the lengths of the raw materials belonging to the same length interval from the selected sub-problems with the preset number for interchange to obtain the sub-problems with the preset number after iterative optimization, and randomly generating a plurality of new sub-problems, so that the total number of the selected sub-problems with the preset number, the sub-problems with the preset number after iterative optimization and the randomly generated sub-problems is N.
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