CN111507846A - Asset screening and packaging method and device, storage medium and electronic equipment - Google Patents
Asset screening and packaging method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The invention discloses an asset screening and packaging method, an asset screening and packaging device, a storage medium and electronic equipment, wherein the asset screening and packaging method comprises the following steps: a threshold value calculation step: calculating a packet threshold; and (3) asset planning step: screening out the asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package in the residual assets, and putting the asset set into an unplanned small package; and (3) circulating step: and circularly executing the threshold value calculation step and the asset planning step until the sum of the residual assets is zero. The method can be used for unpacking the big packet into the small packets, obtaining the optimal strategy, saving the query time when the asset data volume is overlarge, preventing the back end from easily overflowing the memory and improving the efficiency of asset management.
Description
Technical Field
The invention relates to the technical field of computers and finance, in particular to an asset screening and packaging method, an asset screening and packaging device, a storage medium and electronic equipment.
Background
The asset management system is used for performing business operations such as asset screening package, structured design, shelf life management and the like on an asset pool, wherein the asset screening package is particularly important and can directly influence the structured design and the overall performance of a product during distribution.
In the prior art, the asset screening package is to perform database dropping processing on asset information, and during query, the database level is filtered according to a single field without the need of computing screening conditions (for example: the number of remaining assets is greater than 12), and then secondary filtering of complex filtering conditions is performed through a back-end code (for example: the mortgage rate [ loan amount/mortgage evaluation value ] is not more than 70%); the big package and small package splitting is to sort the assets in the big package from small to large according to the money amount, such as: big pack {1,2,3,4,5 … … 19,20}, which needs to be split into 5 small packs,
the existing solutions are as follows:
the assets are stuffed into each asset pack in a dragon tail-wagging manner to achieve a relative balance of the total amount in each pack.
But such big-pack unpacking yields results that are not optimal in some cases.
Disclosure of Invention
Objects of the invention
The invention aims to provide an asset screening and packaging method, an asset screening and packaging device, a storage medium and electronic equipment to solve the problem that in the prior art, the obtained result is not an optimal strategy when a big package is unpacked.
(II) technical scheme
To solve the above problem, a first aspect of the present invention provides an asset screening encapsulation method, including: a threshold value calculation step: calculating a packet threshold; and (3) asset planning step: screening out the asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package in the residual assets, and putting the asset set into an unplanned small package; and (3) circulating step: and circularly executing the threshold value calculation step and the asset planning step until the sum of the residual assets is zero.
Further, the threshold calculation step further includes: and calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value.
Further, the threshold calculation step includes: calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value; and when the calculation result is larger than the preset variation coefficient threshold value, calculating the result of dividing the residual asset sum by the number of the residual unplanned small packages, and taking the result as a small package threshold value.
Further, the threshold calculation step includes: calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value; and when the calculation result is less than or equal to the preset variation coefficient threshold value, calculating the result of the initial average value + (the initial average value-the sum of the assets of the previous packet), and taking the result as a packet threshold value.
Further, still include: a small packet screening step: and selecting the packet closest to or with the highest profit according to the target money amount.
According to another aspect of the present invention, there is provided an asset screening encapsulation apparatus, including: the threshold value calculating module is used for calculating the packet threshold value; the asset planning module is used for screening out an asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package from the residual assets, and putting the asset set into an unplanned small package; and the circulation module is used for circularly executing the functions executed by the threshold calculation module and the asset planning module until the sum of the residual assets is zero.
Further, the threshold calculation module includes: a calculation unit and a comparison unit; the computing unit is used for computing the coefficient of variation value of the residual assets; the comparison unit is used for comparing the result of the calculated coefficient of variation value of the calculation unit with a preset coefficient of variation threshold value.
Further, the threshold calculation module includes: a calculation unit and a comparison unit; the computing unit is used for computing the coefficient of variation value of the residual assets; the comparison unit is used for comparing the calculated coefficient of variation value result of the calculation unit with a preset coefficient of variation threshold value; and when the calculation result is larger than the preset variation coefficient threshold value, the calculation module calculates the result of dividing the residual asset sum by the number of the residual unplanned small packages, and takes the result as a small package threshold value.
Further, the threshold calculation module includes: a calculation unit and a comparison unit; the computing unit is used for computing the coefficient of variation value of the residual assets; the comparison unit is used for comparing the calculated coefficient of variation value result of the calculation unit with a preset coefficient of variation threshold value; and when the calculation result is less than or equal to the preset variation coefficient threshold value, the calculation module calculates the result of the initial average value + (the initial average value-the sum of the assets of the previous packet), and the result is used as a packet threshold value.
Further, still include: screening small packet modules: and selecting the packet closest to or with the highest profit according to the target money amount.
According to a further aspect of the present invention, there is provided a computer storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of the method of any one of the above-described aspects.
According to a further aspect of the present invention, there is provided an electronic device comprising a memory, a display, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of the above aspects when executing the program.
(III) advantageous effects
The technical scheme of the invention has the following beneficial technical effects:
the method and the system can be used for unpacking the big packet into the small packets, obtaining the optimal strategy, saving the query time when the asset data volume is overlarge, preventing the back end from being easy to overflow, and improving the efficiency of asset management.
Drawings
FIG. 1 is a flow chart of an asset screening package method according to a first embodiment of the present invention;
FIG. 2 is a diagram illustrating an optimized packet policy screening process according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a first result of calculating a threshold for a small packet according to an embodiment of the present invention;
fig. 4 is a diagram illustrating a second result of calculating a threshold of a small packet according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, in a first aspect of the present invention, there is provided an asset screening encapsulation method, including:
s1: calculating a packet threshold;
s2: screening out the asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package in the residual assets, and putting the asset set into an unplanned small package;
s3: the loop executes S1 and S2 until the total of remaining assets is zero.
According to the method, the big packet can be disassembled into the small packets, the optimal strategy is obtained, the query time can be saved when the asset data volume is too large, the phenomenon that the memory of the back end is easy to overflow is prevented, and the asset management efficiency is improved.
Optionally, the threshold calculation step further includes:
and calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value.
Optionally, the threshold calculation step includes:
calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value;
and when the calculation result is larger than the preset variation coefficient threshold value, calculating the result of dividing the residual asset sum by the number of the residual unplanned small packages, and taking the result as a small package threshold value.
Optionally, the threshold calculation step includes:
calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value;
and when the calculation result is less than or equal to the preset variation coefficient threshold value, calculating the result of the initial average value + (the initial average value-the sum of the assets of the previous packet), and taking the result as a packet threshold value.
Optionally, the method further includes:
a small packet screening step: and selecting the packet closest to or with the highest profit according to the target money amount.
In a specific embodiment of the invention, the method of the invention is used for manufacturing a rule engine, wherein the rule engine is a component which can be nested in a program and can strip out business rules; screening packets by a rules engine
The system summarizes all the rules into ten rules of more than RU L E _ GREATER, less than RU L E _ L0 ESS, equal to RU L1E _ L2 ESS, NOT equal to RU L3E _ NOT _ EQUA L4, more than or equal to RU L5E _ GREATER _ EQUA L, less than or equal to RU L E _ L ESS _ EQUA L, including RU L E _ CONTAINS, NOT including RU L E _ NOT _ CONTAINS, belonging to RU L E _ MEMOROF, NOT belonging to RU L E _ NOT _ MEMBEROF, and the like.
At the same time, general processing logic is added to the 10 rules in the rules engine application.
Code values are also formulated for various attributes of the asset, such as: AGE, YEAR _ INCOME, etc.
All items will be configured with custom check attributes, and the configured check attributes will be stored in the disk in the form of files, such as AGE GREATER than 20(AGE: RU L E _ GREATER:20) annual INCOME GREATER than 15 ten thousand (YEAR _ INCOME: RU L E _ GREATER: 150000).
Assets to be screened only need to substitute the corresponding attributes into the rule engine, asset information does not need to be filtered in service codes, OOM caused by overlarge data volume can be prevented, the asset information does not need to be put into a database and filtered by using sql, and IO (input/output) expenditure for interaction with the database is reduced.
And decomposing the complex problem, solving the sub-problems step by step, dynamically forming a decision sequence, and developing from a local optimal solution to an overall optimal solution. Taking the classic 0-1 backpack problem as an example, if there is a sample set of { a, b, c, d, e }, the corresponding weight is {3,1,5,7,8}, and the corresponding value is {4,3,8,9,11}, there is now a backpack with the maximum load of 14, please select the asset combination with the maximum value to be placed in the backpack.
Let V be the capacity, the two-dimensional array f [ i ] [ j ], i represents the available samples, j represents the capacity, and f [ i ] [ i ] represents the maximum value of each stage.
When the weight of the article is larger than the capacity, the article is not packed, and dp [ i ] [ j ] ═ dp [ i-1] [ j ];
otherwise, there are:
dp[i][j]=Max(dp[i-1][j],dp[i-1][j-weight[i-1]]+value[i-1]);
the following table can be obtained:
i | value | 4 | 3 | 8 | 9 | 11 |
|
3 | 1 | 5 | 7 | 8 | |
j | / | / | / | / | / | / |
1 | / | / | 3 | 3 | 3 | 3 |
2 | / | / | 3 | 3 | 3 | 3 |
3 | / | 4 | 4 | 4 | 4 | 4 |
4 | / | 4 | 7 | 7 | 7 | 7 |
5 | / | 4 | 7 | 8 | 8 | 8 |
6 | / | 4 | 7 | 11 | 11 | 11 |
7 | / | 4 | 7 | 11 | 11 | 11 |
8 | / | 4 | 7 | 12 | 12 | 12 |
9 | / | 4 | 7 | 15 | 15 | 15 |
10 | / | 4 | 7 | 15 | 15 | 15 |
11 | / | 4 | 7 | 15 | 16 | 16 |
12 | / | 4 | 7 | 15 | 17 | 18 |
13 | / | 4 | 7 | 15 | 20 | 20 |
14 | / | 4 | 7 | 15 | 20 | 22 |
finally, the maximum value is 22, and specific articles are selected by reverse deduction.
The initial observation point is dp [ i ] [ j ], whether dp [ i ] [ j ] is larger than dp [ i-1] [ j ] is judged, if so, the local optimal solution is changed, the ith article is adopted, and then the observation point is dp [ i-1] [ j- (i article value) ] (which represents the optimal solution when the current maximum capacity minus i article capacity); if equal, it indicates no change, the viewpoint becomes dp [ i-1] [ j ], and the previous process is repeated, as shown in FIG. 2.
Since 22>20, articles with a weight of 8 were used, the capacity 14-8 was 6, the optimal solution for the capacity of 6 in the previous column was observed, and since 11 was the same as the optimal solution 11 for the capacity of 6 in the previous column, articles with a weight of 7 were not used, and so on, it was found that articles with a weight of 1,5,8, respectively, were used with a total weight of 14, a value of 3,8,11, respectively, and a total value of 22.
(2) How to take apart big and small bags
The idea of unpacking the small bags from the big bag is that through recursion, the backpack capacity of each time is continuously adjusted, the used assets are removed, and the optimal solution is gradually planned for each small bag;
①, firstly, calculating a target small packet threshold value, wherein the small packet threshold value is the asset size/small packet number of a big packet;
② dynamically planning the current asset set, and finding out the asset set with the total money as close to the threshold value of the packet as possible but not exceeding the threshold value of the packet as the first packet;
③ removing the current small package asset set from the original asset set to serve as a new asset set, and adjusting the threshold value of the small package;
there are two calculation methods for the packet threshold here: 1 total of current asset set/number of remaining unplanned bundles; and determining which mode is used for calculating the small packet threshold value according to the variation coefficient threshold value of the large packet asset set, wherein if the variation coefficient exceeds the variation coefficient threshold value (default 10%), the discrete degree of the large packet asset set is high, the first mode for calculating the small packet threshold value is required, otherwise, the discrete degree is relatively low, and the second mode for calculating the small packet threshold value can be adopted.
(3) Continuing with the example of asset packs shown above, the set of asset packs is {1,3,7,12,25,26,28,30,35,42,47,54,59,64,64,68,70,72,73,73}, and 20 assets in total are divided into 5 packets.
The results obtained using the first calculation packet threshold are shown in fig. 3; the results obtained using the second calculation packet threshold are shown in figure 4.
At this time, the variance of the amounts of 5 asset packs was only 0.24.
The large package can be known to have 20 assets in total, and the variance is: 397.8717467760843, standard deviation: 19.946722707655116, coefficient of variation: 0.1169210006310382, average per package: 170.6. the coefficient of variation exceeds a threshold (10%), so the first way of calculation is recommended.
3. Cyclically purchasing supplemental assets
And in the screening stage, a rule engine is adopted for screening, and then an optimal set is taken out from the screening result set based on a dynamic programming algorithm.
There are two strategies for this approach, first, scale stabilization takes precedence, such as: if an asset pack requires 500 dollars to be replenished, the size of the assets to be replenished as much as possible will be approximately 500 assets but not more than 500 assets.
Second, revenue first, if there is also an asset pack that needs to be replenished by 500 dollars, then a collection is found that will have the most future cash flow and will not have the size of the replenished assets exceeding 500 dollars.
The existing screened asset set is:
{11,43,63,7,12,6,73,90,33,54,23,12,87,34,12,14,15,19,21,68}
the corresponding annual interest rates are as follows:
{0.12,0.14,0.09,0.09,0.08,0.15,0.12,0.14,0.09,0.09,0.08,0.12,0.14,0.12,0.14,0.09,0.13,0.16,0.18,0.14}, from which the assets whose sum is closest to 500 are selected.
First scheme
Similar to big and small packages, finding a set of assets close to a threshold (500) as
{11,43,63,12,73,90,33,54,87,34} total assets 500
Second embodiment
Considering that the duration of each asset is different, only calculating the cash flow of the unit month, wherein the cash flow of each asset in the unit month is as follows: amount x annual rate/12; the calculated cash flow per month is as follows:
{0.11,0.50,0.47,0.05,0.08,0.08,0.73,1.05,0.25,0.40,0.15,0.12,1.02,0.34,0.14,0.11,0.16,0.25,0.32,0.79}, where the set with the largest cash flow and the size of the assets within 500 can be calculated according to the mode of solving the 0-1 knapsack problem, the complementary set of assets can be obtained
{11,43,7,6,73,90,12,87,34,12,15,19,21,68}, total assets of 498.
The cash flow for the corresponding unit month is:
{0.11,0.5,0.05,0.08,0.73,1.05,0.12,1.02,0.34,0.14,0.16,0.25,0.32,0.79}, total cash flow per month being: 5.66.
the above embodiments demonstrate that the rule engine manufactured by the method of the present invention is policy-optimized in executing the packaging task, and saves the manual screening cost.
In another aspect of the embodiments of the present invention, there is provided an asset screening encapsulation apparatus, including:
the threshold value calculating module is used for calculating the packet threshold value;
the asset planning module is used for screening out an asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package from the residual assets, and putting the asset set into an unplanned small package;
and the circulation module is used for circularly executing the functions executed by the threshold calculation module and the asset planning module until the sum of the residual assets is zero.
Optionally, the threshold calculation module includes: a calculation unit and a comparison unit;
the computing unit is used for computing the coefficient of variation value of the residual assets;
the comparison unit is used for comparing the result of the calculated coefficient of variation value of the calculation unit with a preset coefficient of variation threshold value.
Optionally, the threshold calculation module includes: calculation unit and comparison unit
The computing unit is used for computing the coefficient of variation value of the residual assets;
the comparison unit is used for comparing the calculated coefficient of variation value result of the calculation unit with a preset coefficient of variation threshold value;
and when the calculation result is larger than the preset variation coefficient threshold value, the calculation module calculates the result of dividing the residual asset sum by the number of the residual unplanned small packages, and takes the result as a small package threshold value.
Optionally, the threshold calculation module includes: calculation unit and comparison unit
The computing unit is used for computing the coefficient of variation value of the residual assets;
the comparison unit is used for comparing the calculated coefficient of variation value result of the calculation unit with a preset coefficient of variation threshold value;
and when the calculation result is less than or equal to the preset variation coefficient threshold value, the calculation module calculates the result of the initial average value + (the initial average value-the sum of the assets of the previous packet), and the result is used as a packet threshold value. Wherein, the initial average value is the target packet threshold value of the first step when the big packet is unpacked, namely: asset size/number of packets for big packet
Optionally, the method further includes:
screening small packet modules: and selecting the packet closest to or with the highest profit according to the target money amount.
In a further aspect of the embodiments of the present invention, there is provided a computer storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the method according to any one of the above-mentioned technical solutions.
In another aspect of the embodiments of the present invention, an electronic device is provided, which includes a memory, a display, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method according to any one of the above technical solutions when executing the computer program.
The invention aims to protect an asset screening and packaging method, which comprises the following steps: a threshold value calculation step: calculating a packet threshold; and (3) asset planning step: screening out the asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package in the residual assets, and putting the asset set into an unplanned small package; and (3) circulating step: and circularly executing the threshold value calculation step and the asset planning step until the sum of the residual assets is zero. The method can be used for unpacking the big packet into the small packets, obtaining the optimal strategy, saving the query time when the asset data volume is overlarge, preventing the back end from easily overflowing the memory and improving the efficiency of asset management.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (12)
1. An asset screening package method, comprising:
a threshold value calculation step: calculating a packet threshold;
and (3) asset planning step: screening out the asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package in the residual assets, and putting the asset set into an unplanned small package;
and (3) circulating step: and circularly executing the threshold value calculation step and the asset planning step until the sum of the residual assets is zero.
2. The method of claim 1, wherein the threshold calculating step further comprises:
and calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value.
3. The method of claim 2, wherein the threshold calculating step comprises:
calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value;
and when the calculation result is larger than the preset variation coefficient threshold value, calculating the result of dividing the residual asset sum by the number of the residual unplanned small packages, and taking the result as a small package threshold value.
4. The method of claim 2, wherein the threshold calculating step comprises:
calculating the coefficient of variation values of the residual assets, and comparing the calculation result with a preset coefficient of variation threshold value;
and when the calculation result is less than or equal to the preset variation coefficient threshold value, calculating the result of the initial average value + (the initial average value-the sum of the assets of the previous packet), and taking the result as a packet threshold value.
5. The method according to any one of claims 1-4, further comprising:
a small packet screening step: and selecting the packet closest to or with the highest profit according to the target money amount.
6. An asset screening encapsulation device, comprising:
the threshold value calculating module is used for calculating the packet threshold value;
the asset planning module is used for screening out an asset set which is closest to the threshold value of the small package but not more than the threshold value of the small package from the residual assets, and putting the asset set into an unplanned small package;
and the circulation module is used for circularly executing the functions executed by the threshold calculation module and the asset planning module until the sum of the residual assets is zero.
7. The apparatus of claim 6, wherein the threshold calculation module comprises: a calculation unit and a comparison unit;
the computing unit is used for computing the coefficient of variation value of the residual assets;
the comparison unit is used for comparing the result of the calculated coefficient of variation value of the calculation unit with a preset coefficient of variation threshold value.
8. The apparatus of claim 7, wherein the threshold calculation module comprises: a calculation unit and a comparison unit;
the computing unit is used for computing the coefficient of variation value of the residual assets;
the comparison unit is used for comparing the calculated coefficient of variation value result of the calculation unit with a preset coefficient of variation threshold value;
and when the calculation result is larger than the preset variation coefficient threshold value, the calculation module calculates the result of dividing the residual asset sum by the number of the residual unplanned small packages, and takes the result as a small package threshold value.
9. The apparatus of claim 7, wherein the threshold calculation module comprises: a calculation unit and a comparison unit;
the computing unit is used for computing the coefficient of variation value of the residual assets;
the comparison unit is used for comparing the calculated coefficient of variation value result of the calculation unit with a preset coefficient of variation threshold value;
and when the calculation result is less than or equal to the preset variation coefficient threshold value, the calculation module calculates the result of the initial average value + (the initial average value-the sum of the assets of the previous packet), and the result is used as a packet threshold value.
10. The apparatus of any one of claims 6-9, further comprising:
screening small packet modules: and selecting the packet closest to or with the highest profit according to the target money amount.
11. A computer storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1-5.
12. An electronic device comprising a memory, a display, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method of any one of claims 1 to 5 when executing the program.
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CN115221460A (en) * | 2022-09-20 | 2022-10-21 | 浙江保融科技股份有限公司 | Method for solving ordered knapsack problem segmentation dynamic planning under limited resources |
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CN111986030A (en) * | 2020-09-02 | 2020-11-24 | 河北幸福消费金融股份有限公司 | Data processing method, data processing device, storage medium and computer equipment |
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CN115221460A (en) * | 2022-09-20 | 2022-10-21 | 浙江保融科技股份有限公司 | Method for solving ordered knapsack problem segmentation dynamic planning under limited resources |
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