CN110223010B - Intelligent ex-warehouse method integrating multiple factors - Google Patents
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Abstract
The invention discloses an intelligent ex-warehouse method integrating multiple factors, which comprises the following steps: s1, establishing an intermediate calculation database; s2, obtaining goods information according to the delivery order; s3, performing parcel level screening; s4, performing warehouse combination level screening; s5, judging whether the warehouse is divided into a plurality of areas by the firewall, if so, carrying out area combination level screening; s6, library position combination screening is carried out; s7, judging whether only one candidate ex-warehouse result exists, if yes, executing the step S8, otherwise, respectively calculating the performance score of each candidate ex-warehouse result, and then selecting the ex-warehouse result with the highest performance score as a final recommendation result; and S8, returning the selected ex-warehouse scheme to the calling layer. The invention evaluates the ex-warehouse result by forward screening and reverse calculation to select the out-warehouse result with the optimal score, can meet the requirements of companies and truck drivers as far as possible, and ensures that the ex-warehouse result recommended by the algorithm is more stable and has better performance than manual selection.
Description
Technical Field
The invention belongs to the technical field of warehouse management, and particularly relates to an intelligent ex-warehouse method integrating multiple factors.
Background
In the existing warehouse ex-warehouse storage location selection, a large number of enterprises still adopt manual experience to select the storage location, namely, a plurality of managers with rich experience are recruited to select the storage location for ex-warehouse. The existing warehouse management software only realizes the display of the storage information of the warehouse goods, such as quantity, batch number and the like, and does not have the function of intelligently recommending the warehouse location. Although a skilled warehouse manager can select the warehouse-out position group within a short time according to the order requirement and the warehouse goods storage information, the warehouse manager is often busy and can not open the warehouse during the warehouse-out peak period, so that the selected warehouse-out position group cannot enable goods to be delivered out of the warehouse as soon as possible, and the requirement of enterprises on the first-out of old goods cannot be met.
For the ex-warehouse position recommendation system, two very important indexes are ex-warehouse cost and production date of goods. For truck drivers, time is money, and if the time is wasted on delivery, the time is obviously ineligible, so that the truck drivers pay more attention to the delivery time, and the delivery time is directly influenced by the delivery cost. For the company, what is most important is the circulation degree of the goods, that is, the goods with the production date being earlier can be taken out of the warehouse preferentially, and of course, the company also considers the situation of the goods storage position of the warehouse after the goods are taken out of the warehouse, such as whether the rest goods are gathered together. However, in the prior art, no technology for intelligently recommending library bit groups for ex-warehouse orders exists.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide the comprehensive multi-factor intelligent ex-warehouse method which evaluates the ex-warehouse results through multi-level screening, forward screening and backward calculation to select the out-warehouse results with the optimal scores, can meet the requirements of drivers of official and freight cars as far as possible, ensures that the ex-warehouse results recommended by an algorithm are more stable and better in performance than manual selection, and saves the cost of a company engaging a warehouse manager and the time cost of a goods driver.
The purpose of the invention is realized by the following technical scheme: an intelligent ex-warehouse method integrating multiple factors comprises the following steps:
s1, establishing an intermediate calculation database, and synchronizing data from the enterprise production library to the intermediate calculation database;
s2, obtaining goods information according to the delivery order, and obtaining all candidate areas in the city where the driver is located according to the driver positioning;
s3, performing parcel level screening according to the order information and the candidate parcels; counting the quantity of various goods stored in the order placed in each candidate area, then comparing whether the quantity of the goods stored in the candidate area is greater than or equal to the quantity of the goods required in the order, and if so, executing the step S4; otherwise, the calling layer is informed through a feedback interface that the stock can not meet the order requirement;
s4, performing warehouse combination level screening;
s5, judging whether the warehouse is divided into a plurality of areas by the firewall, if so, performing area combination level screening, otherwise, not performing area combination level screening;
s6, library position combination screening is carried out;
s7, judging whether only one candidate ex-warehouse result screened out through the steps S3-S6 exists, if yes, executing the step S8, otherwise, respectively calculating the performance score of each candidate ex-warehouse result, then selecting the ex-warehouse result with the highest performance score as a final recommendation result, and executing the step S8;
and S8, returning the selected ex-warehouse scheme to the calling layer.
Further, the step S4 includes the following sub-steps:
s41, counting the quantity of various goods in the order stored in each warehouse under the candidate area;
s42, removing warehouses without any order goods, taking the rest warehouses as a set, and solving all proper subsets of the set, wherein each proper subset is a warehouse combination;
s43, screening according to the sizes of the warehouse combinations from small to large, if a certain warehouse combination meets the types and the number of the order goods, no longer screening warehouse combinations larger than the certain warehouse combination, and taking the warehouse combination as the optimal warehouse combination;
s44, judging whether the size of the warehouse combination is equal to 1, and if the size of the warehouse combination is equal to 1, taking goods across warehouses is not needed;
sequentially selecting the library positions from high to low according to the library position performance score to be delivered out of the library, preferentially selecting the adjacent library positions in the selection process, namely when one library position is selected, directly selecting the adjacent library positions and sequentially recursively going until no adjacent library positions are selected if the adjacent library positions can be selected; then selecting a library position with a lower performance score by one level;
s45, if the warehouse combination size is larger than 1, cross-warehouse goods taking is needed, and the warehouse selection sequence needs to be determined;
summing the performance scores of the warehouse positions under each warehouse and taking an average value to obtain a warehouse performance score;
selecting the warehouse from high to low according to the warehouse performance score, and if the warehouse is not the last selected warehouse, taking all goods in all stored orders in the warehouse out of the warehouse; if the last warehouse is available, the warehouse does not need to take all the stored goods out of the warehouse, but only needs to meet the order requirement, and the method of step S44 is adopted for the selection of the position of the warehouse in the last area.
Further, the region combination level filtering in step S5 includes the following sub-steps:
s51, counting the quantity of various goods in the order of each region of each warehouse in the warehouse combination according to the warehouse combination obtained in the step S4; then removing the areas without any order goods, taking the rest areas as a large set, and solving all proper subsets of the set, wherein each proper subset is an area combination;
screening according to the area combinations from small to large, if a certain area combination meets the requirements of the types and the quantity of the order goods, further judging whether all the areas in the area combination are continuously adjacent, if so, taking the area combination as the optimal area combination, otherwise, continuously screening the next area combination; if all the areas in the area combination meeting the requirements of the type and the quantity of the order goods do not meet the continuous adjacency, taking the minimum area combination meeting the conditions as the optimal area combination;
s52, judging whether the size of the area combination obtained in the step S51 is equal to 1: if the area combination size is equal to 1, go to step S53; if the area combination size is larger than 1 but the warehouse combination size is equal to 1, go to step S54; if the area combination size is larger than 1 and the warehouse combination size is also larger than 1, the step S55 is entered;
s53, the size of the area combination is equal to 1, which indicates that cross-warehouse and cross-area goods taking are not needed;
sequentially selecting the positions from large to small according to the position performance score until the order requirement is met;
in the selection process, the adjacent library positions are preferentially selected, namely when one library position is selected, the adjacent library positions are found to be available for selection, the adjacent library positions are directly selected and recursion is carried out in sequence until no adjacent library positions are selected; then selecting a library position with a lower performance score;
s54, the size of the area combination is larger than 1, the warehouse combination is equal to 1, and the situation that goods do not need to be taken across warehouses and goods need to be taken across areas is indicated;
for each region in the region combination, summing all the bin performance scores and taking the average value to obtain a region score;
sequentially selecting areas from large to small according to the area scores, and if the areas are not the areas selected at last, taking all goods in all stored orders in the areas out of the warehouse; if the area is the last area, the area does not need to discharge all the stored goods, but only needs to meet the order requirement, and for the last area, the warehouse location is screened and selected by adopting the warehouse location combination;
s55, the size of the area combination is larger than 1, the size of the warehouse combination is larger than 1, and the situation that goods are required to be taken across warehouses and across areas is indicated;
calculating the scores of the regions according to the method for calculating the scores of the regions in the step S54, summing the scores of the regions, averaging the scores, and adding a cross-region penalty cost to obtain a warehouse score;
sequentially selecting warehouses from top to bottom according to the warehouse scores, and if the warehouses are not the last warehouse selected, taking all goods in all stored orders in the warehouse out of the warehouse; if the warehouse is the last selected warehouse and the size of the area combination under the warehouse is equal to 1, performing ex-warehouse position combination selection according to the ex-warehouse method when the size of the area combination is equal to 1 in the step S53; if the size of the area combination under the last selected warehouse is larger than 1, the warehouse entering position is selected according to the method of warehouse exiting when the size of the area combination is larger than 1 in step S54.
Further, the calculation method of the library position performance score comprises the following steps: calculating the warehouse-out cost of each warehouse location, the warehouse location type score and the temporary condition of goods in the order placed by the warehouse locationAnd (4) keeping the rate, and then weighting and summing all the features to obtain a library position performance score: let the weight of the ex-warehouse cost be WcoutThe weight of the bin type score is WsltThe weight of the temporary protection rate is WrexprThen the bin performance score SlpThe formula is as follows:
Slp＝Wcout*Cout+Wslt*Slt+Wrexpr*Rexpir
Coutrepresents the outbound cost, SltIndicates the bin type score, RexpirRepresenting the clinical rate.
The warehouse performance score swarehouseThe calculation method comprises the following steps: let m regions under the warehouse in the screened region combination be { Re }1，Re2，…，RemThe corresponding regional performance score is { S }region1,Sregion2,…,SregionmGet a cross-region penalty of { C }crossRegion1,CcrossRegion2,…,CcrossRegionmW is the cross-region penalty cost weightcostCRAnd then:
exit result performance score SresultThe calculation method comprises the following steps: let n regions under the warehouse in the screened region combination be respectively { Wh1,Wh2,…,WhnThe corresponding regional performance score is { S }warehouse1,Swarehouse2,…,SwarehousenGet the penalty of { C across regions }crossWh1，CcrossWh2，…，CcrossWhnW is the cross-region penalty cost weightcostCWAnd then:
the invention has the beneficial effects that:
1. according to the method, the ex-warehouse result is evaluated through multi-level screening and multiple factors, and a forward screening and reverse calculation method, so that the out-warehouse result with the optimal score is selected, the requirements of a company and a truck driver can be met as far as possible, the out-warehouse result recommended by an algorithm is more stable than manual selection and better in performance, and the cost of a warehouse manager engaged by the company and the time cost of a cargo driver are saved;
2. according to the invention, by adding the intermediate calculation database, the ex-warehouse recommendation algorithm can be easily adapted to other enterprises under the condition of only modifying the data synchronization program, a set of ex-warehouse recommendation algorithm does not need to be designed for each enterprise, the storage of the intermediate calculation database also greatly accelerates the operation speed of the ex-warehouse algorithm, improves the user experience, and can process large orders in a short time.
Drawings
FIG. 1 is a flow chart of the four-stage screening of the present invention;
FIG. 2 is a flow chart of the integrated multi-factor intelligent ex-warehouse method of the present invention;
Detailed Description
In the invention, the warehouse-out position is recommended by mainly adopting four-level screening, which is respectively district-level screening, warehouse combination-level screening, area combination-level screening and warehouse position combination-level screening, wherein the several levels of screening not only accelerate the quick generation of algorithm results, but also ensure better warehouse-out position recommendation results, as shown in figure 1. The effect of each stage of screening is described below.
And (3) screening in a parcel level: the level screening is mainly used for enterprise service with a plurality of areas for storing goods, and mainly has the functions of judging whether the areas meet order requirements or not, judging which areas meet the order requirements, screening out the areas which do not meet the order goods type requirements and goods quantity requirements, and avoiding performing operation under invalid areas and accelerating an algorithm.
Screening in a warehouse combination level: the screening function of the level is to select warehouse combinations meeting the order requirements, and the size of the warehouse combinations is required to be as small as possible, so that excessive warehouse ex-warehouse crossing can be avoided, ex-warehouse time is saved, algorithm operation is accelerated, and the ex-warehouse algorithm result is guaranteed to be better.
And (3) area combination level screening: the level of screening is an enterprise service for managing areas under each warehouse, and is used for selecting area combinations meeting order requirements under each warehouse combination, and the size of the area combinations is required to be as small as possible, so that excessive area ex-warehouse crossing is avoided, and areas in the area combinations are required to be as adjacent as possible, so that the area ex-warehouse can be moved to another area in a short time. This level of screening can speed up the algorithm and make the algorithm result more optimal.
Screening in a library position combination level: the screening of the stage is to generate a final ex-warehouse result, and the screening process ensures that the ex-warehouse result recommended by the algorithm is stable and better than manual work. The weight occupied by the factors influencing the library level performance score can be adjusted by the enterprise according to actual requirements, for example, the weight occupied by the ex-warehouse cost can be increased when the enterprise is more interested in the warehouse.
In the invention, although the ex-warehouse recommendation result is the goods taken from the warehouse location, when the performance of the recommended ex-warehouse result is evaluated, the performance of the ex-warehouse result is evaluated finally by adopting the idea of forward screening and reverse calculation instead of directly using the warehouse location combination performance score for measurement. Forward screening refers to: and screening the chip area level, the warehouse combination level, the area level and the warehouse location combination level to obtain a final warehouse location combination. The inverse calculation refers to: the method comprises the steps of firstly calculating the performance score of each bin in a bin combination, then obtaining the regional performance score on the basis of the bin performance score, then obtaining the warehouse performance score on the basis of the regional performance score, and finally obtaining the ex-warehouse result performance score on the basis of the warehouse performance score.
The technical scheme of the invention is further explained by combining the attached drawings.
As shown in fig. 2, an intelligent ex-warehouse method integrating multiple factors includes the following steps:
s1, establishing an intermediate calculation database, synchronizing data from the enterprise production library to the intermediate calculation database, and then taking all data required by the algorithm from the intermediate database;
s2, obtaining goods information according to the delivery order, and obtaining all candidate parcel areas in the city where the driver is located according to the driver positioning so as to prevent the driver from getting goods across the city;
s3, performing parcel level screening according to the order information and the candidate parcels; since the distance between each region is usually relatively far, the algorithm does not allow the cross-region ex-warehouse. Firstly, counting the quantity of various goods stored in the order placed in each candidate area, then comparing whether the quantity of the goods stored in the candidate area is greater than or equal to the quantity of the goods required in the order, and if so, executing a step S4; otherwise, the calling layer is informed through a feedback interface that the stock can not meet the order requirement;
s4, performing warehouse combination level screening; the method comprises the following substeps:
s41, counting the quantity of various goods in the order stored in each warehouse under the candidate area;
s42, removing warehouses without any order goods, taking the rest warehouses as a set, and solving all proper subsets of the set, wherein each proper subset is a warehouse combination;
s43, screening according to the sizes of the warehouse combinations from small to large, if a certain warehouse combination meets the types and the number of the order goods, no longer screening warehouse combinations larger than the certain warehouse combination, and taking the warehouse combination as the optimal warehouse combination; if the order requirement is met in the size of a certain warehouse combination, the subsequent larger warehouse combination is not screened any more, and the warehouse-out principle of spanning the minimum warehouse is followed;
s44, judging whether the size of the warehouse combination is equal to 1, and if the size of the warehouse combination is equal to 1, taking goods across warehouses is not needed;
sequentially selecting the library positions from high to low according to the library position performance score to be delivered out of the library, preferentially selecting the adjacent library positions in the selection process, namely when one library position is selected, directly selecting the adjacent library positions and sequentially recursively going until no adjacent library positions are selected if the adjacent library positions can be selected; then selecting a library position with a lower performance score by one level;
s45, if the warehouse combination size is larger than 1, cross-warehouse goods taking is needed, and the warehouse selection sequence needs to be determined;
summing the performance scores of the warehouse positions under each warehouse and taking an average value to obtain a warehouse performance score;
selecting the warehouse from high to low according to the warehouse performance score, and if the warehouse is not the last selected warehouse, taking all goods in all stored orders in the warehouse out of the warehouse; if the last warehouse is available, the warehouse does not need to take all the stored goods out of the warehouse, but only needs to meet the order requirement, and the method of step S44 is adopted for the selection of the position of the warehouse in the last area.
S5, judging whether the warehouse is divided into a plurality of areas by the firewall, if so, carrying out area combination level screening, otherwise, not carrying out area combination level screening; the region combination level screening comprises the following sub-steps:
s51, counting the quantity of various goods in the order of each region of each warehouse in the warehouse combination according to the warehouse combination obtained in the step S4; then removing the areas without any order goods, taking the rest areas as a large set, and solving all proper subsets of the set, wherein each proper subset is an area combination;
screening according to the area combinations from small to large, if a certain area combination meets the requirements of the types and the quantity of the order goods, further judging whether all the areas in the area combination are continuously adjacent, if so, taking the area combination as the optimal area combination, otherwise, continuously screening the next area combination; if all the areas in the area combination meeting the requirements of the type and the quantity of the order goods do not meet the continuous adjacency, taking the minimum area combination meeting the conditions as the optimal area combination; since it is most time-saving to deliver the area in consecutive next areas when it has to be delivered across areas, the area combinations of non-consecutive selected areas are discarded if there are area combinations that are consecutively delivered next to the area selected under the same warehouse.
S52, judging whether the size of the area combination obtained in the step S51 is equal to 1: if the area combination size is equal to 1, go to step S53; if the area combination size is larger than 1 but the warehouse combination size is equal to 1, go to step S54; if the area combination size is larger than 1 and the warehouse combination size is also larger than 1, the step S55 is entered;
s53, the size of the area combination is equal to 1, which indicates that cross-warehouse and cross-area goods taking are not needed;
sequentially selecting the positions from large to small according to the position performance score until the order requirement is met;
in the selection process, the adjacent library positions are preferentially selected, namely when one library position is selected, the adjacent library positions can be selected if the adjacent library positions are found, the adjacent library positions are directly selected and recursion is carried out in sequence until the adjacent library positions are not selected, and the dispersion of the regional library positions after being taken out of the library can be reduced by selecting the adjacent library positions by wires; then selecting a library position with a lower performance score by one level;
s54, the size of the area combination is larger than 1, the warehouse combination is equal to 1, and the situation that goods do not need to be taken across warehouses and goods need to be taken across areas is indicated;
for each region in the region combination, summing all the bin performance scores and taking the average value to obtain a region score;
sequentially selecting areas from large to small according to the area scores, and if the areas are not the areas selected at last, taking all goods in all stored orders in the areas out of the warehouse; if the area is the last area, the area does not need to discharge all the stored goods, but only needs to meet the order requirement, and for the last area, the warehouse location is screened and selected by adopting the warehouse location combination;
s55, the size of the area combination is larger than 1, the size of the warehouse combination is larger than 1, and the situation that goods are required to be taken across warehouses and across areas is indicated;
calculating the scores of the regions according to the method for calculating the scores of the regions in the step S54, summing the scores of the regions, averaging the scores, and adding a cross-region penalty cost to obtain a warehouse score;
sequentially selecting warehouses from top to bottom according to the warehouse scores, and if the warehouses are not the last warehouse selected, taking all goods in all stored orders in the warehouse out of the warehouse; if the warehouse is the last selected warehouse and the size of the area combination under the warehouse is equal to 1, performing ex-warehouse position combination selection according to the ex-warehouse method when the size of the area combination is equal to 1 in the step S53; if the size of the area combination under the last selected warehouse is larger than 1, the warehouse entering position is selected according to the method of warehouse exiting when the size of the area combination is larger than 1 in step S54.
S6, library position combination screening: calculating the ex-warehouse cost of each warehouse location, the warehouse location type score and the temporary storage rate of goods in the order placed by the warehouse location (if a plurality of temporary storage rates exist, the highest value is taken), and then weighting and summing each characteristic to obtain a warehouse location performance score; sequentially selecting the bin positions from high to low according to bin position performance scores, and taking out the bin positions, wherein in the selection process, adjacent bin positions are preferentially selected, namely when one bin position is selected, if the adjacent bin positions can be selected, the adjacent bin positions are directly selected and sequentially returned until no adjacent bin positions are selected; then selecting a library position with a lower performance score by one level;
s7, judging whether only one candidate ex-warehouse result screened out through the steps S3-S6 exists, if yes, executing the step S8, otherwise, respectively calculating the performance score of each candidate ex-warehouse result, then selecting the ex-warehouse result with the highest performance score as a final recommendation result, and executing the step S8;
and S8, returning the selected ex-warehouse scheme to the calling layer, wherein the data comprises recommended parcel, warehouse and warehouse ex-warehouse sequence, region and region ex-warehouse sequence (if the region is at the stage), ex-warehouse position and the like, and returning the data to the calling layer.
There are three important factors that affect the ex-warehouse location performance:
A. outbound cost (c'): the cost of moving goods from the depot to the warehouse door can be measured in terms of time or distance and normalized. The normalization method is as follows: and if the region level exists, performing library level warehouse-out cost normalization under one region, and if the region level does not exist, performing library level warehouse-out cost normalization under one warehouse. Let C be the warehouse-out cost of a certain warehouse location before normalization, C' be the warehouse-out cost after normalization, and C be the maximum value of the warehouse-out cost of the warehouse location (or region) belowmaxMinimum value of CminThen, there are:
B. bin type score (S)lt): in a warehouse, an enterprise usually does not have only one type of storage space for storing different goods or other requirements, but has a mixture of multiple types of storage spaces, such as a cross beam type, a shuttle type, a flat warehouse and the like. The priority of each type of bin ex-warehouse will also be different, and to take this into account, we introduce a bin type score (S)lt) The calculation mode of the bin type score is simple, the bin types are sorted from low to high according to the priority, the basic score corresponding to each level is divided into a priority order (calculated from 1), and then the basic score is normalized to obtain the bin type score.
C. Critical rate (R)expir): when the goods are delivered from the warehouse, the goods with the production date being earlier are preferred by the enterprise to keep the goods fresh, so that the degree of the goods approaching the expiration date is represented by the temporary guarantee rate. In general, if the shelf life is 12 months and the production date is one or two months apart, the consumer will not feel any difference, but if the production date is 6 months apart, the consumer will certainly choose to be fresh, so the preservation rate is shown in table one.
Watch 1
| (expiration date-present date)/shelf life | Score value |
| 1-0.76 | 0.25 |
| 0.75-0.51- | 0.5 |
| 0.50-0.26 | 0.75 |
| 0.25-0 | 1 |
The calculation method of the library position performance score comprises the following steps: calculating the ex-warehouse cost of each warehouse location, the warehouse location type score and the temporary protection rate of goods in the order under the warehouse location, and then weighting and summing all the characteristics to obtain a warehouse location performance score: let the weight of the ex-warehouse cost be WcoutThe weight of the bin type score is WsltThe weight of the temporary protection rate is Wrexpr(if there are multiple guaranties, the highest value is taken), the bin performance score SlpThe formula is as follows:
Slp＝Wcout*Cout+Wslt*Slt+Wrexpr*Rexpir。
regional performance score (S)region) The calculation method comprises the following steps: n library positions belonging to the region in the screened library position combination are set as { L }1,L2,..,LnThe corresponding library bit performance score is Slp1,Slp2,...,SlpnAnd then:
warehouse Performance score(s)warehouse) The calculation method comprises the following steps: defining a cross-region penalty cost (C)crossRegion) Comprises the following steps: in the region combination under the warehouse, the penalty cost from the last region to the region is in the range of 0,1]. The penalty cost across the area of the first selected area in the area combination is 0, because it is the starting point, the penalty cost of other areas is defined by the service personnel in the value range, and in principle, the more areas are crossed to reach the area, the greater the penalty cost should be.
Set the screened area groupThe number of the regions belonging to the warehouse is m, and is respectively { Re1，Re2，…，RemThe corresponding regional performance score is { S }region1,Sregion2,…,SregionmGet the penalty of { C across regions }crossRegion1,CcrossRegion2,…,CcrossRegionmW is the cross-region penalty cost weightcostCRAnd then:
exit result performance scoring (S)result): defining a Cross-warehouse penalty cost (C)crossWare) Comprises the following steps: in a warehouse portfolio, the penalty cost for crossing from the last warehouse to the next warehouse is in the range of 0,1]. The penalty cost of the first selected warehouse in the warehouse combination is 0, because the penalty cost is the starting point, the penalty costs of other warehouses are defined by business personnel in the range of value range, and in principle, the farther the spanning distance is, the greater the penalty cost is.
Let n regions under the warehouse in the screened region combination be respectively { Wh1,Wh2,…,WhnThe corresponding regional performance score is { S }warehouse1,Swarehouse2,…,SwarehousenGet the penalty of { C across regions }crossWh1，CcrossWh2，…，CcrossWhnW is the cross-region penalty cost weightcostCWAnd then:
the data source of the invention does not directly originate from the production library of the enterprise, but through an intermediate database, i.e. a so-called calculation database. The calculation database only stores data required by the algorithm, and the following advantages are achieved:
A. making the ex-warehouse algorithm easier to adapt. If the intermediate calculation database is adopted, the method can be adapted to any enterprise needing service only by modifying the data synchronization program and not modifying the ex-warehouse recommendation algorithm.
B. And (4) an acceleration algorithm. Generally, a production library often has a lot of data which are not concerned by the algorithm, and if the data are directly taken from the production library, extra time is consumed, so that the algorithm speed is influenced. If an intermediate calculation database is used, no useless data exists, and the time for taking data from the database is greatly reduced.
C. The algorithm structure is optimized, and the algorithm complexity is reduced. In the production warehouse, many direct results are not stored in the database, for example, whether the warehouse is full of goods or not, whether a certain batch of goods can be directly delivered from the warehouse or not (in a shuttle type shelf, if other goods are stored in front of the shuttle type shelf, the goods cannot be directly delivered from the warehouse), and if the indexes are handed over to the algorithm program for statistics, the algorithm operation speed is slowed, and the complexity of the algorithm program structure is increased. Therefore, if the intermediate calculation database is adopted, the data synchronization program counts indexes required by the algorithm, and the burden of the algorithm program is greatly reduced.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.
Claims (4)
1. An intelligent ex-warehouse method integrating multiple factors is characterized by comprising the following steps:
s1, establishing an intermediate calculation database, and synchronizing data from the enterprise production library to the intermediate calculation database;
s2, obtaining goods information according to the delivery order, and obtaining all candidate areas in the city where the driver is located according to the driver positioning;
s3, according to the order information and all candidate areas, area level screening is carried out; counting the quantity of various goods stored in the order placed in each candidate parcel, then comparing whether the quantity of the goods stored in the candidate parcel is greater than or equal to the quantity of the goods required in the order, and if so, executing the step S4; otherwise, the calling layer is informed through a feedback interface that the stock can not meet the order requirement;
s4, performing warehouse combination level screening; the method comprises the following substeps:
s41, counting the quantity of various goods in the order stored in each warehouse under the candidate area;
s42, removing warehouses without any order goods, taking the rest warehouses as a set, and solving all proper subsets of the set, wherein each proper subset is a warehouse combination;
s43, screening according to the sizes of the warehouse combinations from small to large, if a certain warehouse combination meets the types and the quantity of the order goods, no longer screening the warehouse combinations larger than the certain warehouse combination, and taking the warehouse combination as the optimal warehouse combination;
s44, judging whether the size of the warehouse combination is equal to 1, and if the size of the warehouse combination is equal to 1, taking goods across warehouses is not needed;
sequentially selecting the library positions from high to low according to the library position performance score, taking out the library positions, preferentially selecting the adjacent library positions in the selection process, namely when one library position is selected, finding that the adjacent library positions can be selected, directly selecting the adjacent library positions, and sequentially recursing until no adjacent library positions are selected; then selecting a library position with a lower library position performance score by one level;
s45, if the warehouse combination size is larger than 1, cross-warehouse goods taking is needed, and the warehouse selection sequence needs to be determined;
summing the warehouse location performance scores under each warehouse and taking an average value to obtain a warehouse performance score;
selecting the warehouse from high to low according to the warehouse performance score, and if the warehouse is not the last selected warehouse, taking all goods in all stored orders in the warehouse out of the warehouse; if the warehouse is the last warehouse, the warehouse does not need to take all the stored goods out of the warehouse, but only needs to meet the order requirement, and the method of the step S44 is adopted for selecting the position of the warehouse for the last area;
s5, judging whether the warehouse is divided into a plurality of areas by the firewall, if so, carrying out area combination level screening, otherwise, not carrying out area combination level screening; the region combination level screening comprises the following sub-steps:
s51, counting the quantity of various goods in the order of each region of each warehouse in the warehouse combination according to the warehouse combination obtained in the step S4; then removing the areas without any order goods, taking the rest areas as a large set, and solving all proper subsets of the set, wherein each proper subset is an area combination;
screening according to the area combinations from small to large, if a certain area combination meets the requirements of the types and the quantity of the order goods, further judging whether all the areas in the area combination are continuously adjacent, if so, taking the area combination as the optimal area combination, otherwise, continuously screening the next area combination; if all the areas in the area combination meeting the requirements of the type and the quantity of the order goods do not meet the continuous adjacency, taking the minimum area combination meeting the conditions as the optimal area combination;
s52, judging whether the size of the area combination obtained in the step S51 is equal to 1: if the area combination size is equal to 1, go to step S53; if the area combination size is larger than 1 but the warehouse combination size is equal to 1, go to step S54; if the area combination size is larger than 1 and the warehouse combination size is also larger than 1, the step S55 is entered;
s53, the size of the area combination is equal to 1, which indicates that cross-warehouse and cross-area goods taking are not needed;
sequentially selecting the positions from large to small according to the position performance score until the order requirement is met;
in the selection process, the adjacent library positions are preferentially selected, namely when one library position is selected, if the adjacent library positions can be selected, the adjacent library positions are directly selected and recursion is carried out in sequence until no adjacent library positions are selected; then selecting a library position with a lower library position performance score by one level;
s54, the size of the area combination is larger than 1, the warehouse combination is equal to 1, and the situation that goods do not need to be taken across warehouses and goods need to be taken across areas is indicated;
for each region in the region combination, summing all the bin performance scores and taking the average value to obtain a region score;
sequentially selecting areas from large to small according to the area scores, and if the areas are not the areas selected at last, taking all goods in all stored orders in the areas out of the warehouse; if the area is the last area, the area does not need to discharge all the stored goods, but only needs to meet the order requirement, and for the last area, the warehouse location is screened and selected by adopting the warehouse location combination;
s55, the size of the area combination is larger than 1, the size of the warehouse combination is larger than 1, and the situation that goods are required to be taken across warehouses and across areas is indicated;
calculating the scores of the regions according to the method for calculating the scores of the regions in the step S54, summing the scores of the regions, averaging the scores, and adding a cross-region penalty cost to obtain a warehouse score;
sequentially selecting warehouses from top to bottom according to the warehouse scores, and if the warehouses are not the last warehouse selected, taking all goods in all stored orders in the warehouse out of the warehouse; if the warehouse is the last selected warehouse and the size of the area combination under the warehouse is equal to 1, performing ex-warehouse position combination selection according to the ex-warehouse method when the size of the area combination is equal to 1 in the step S53; if the size of the area combination under the last selected warehouse is larger than 1, selecting the warehouse location according to the method for delivering the warehouse when the size of the area combination is larger than 1 in the step S54;
s6, library position combination screening is carried out;
s7, judging whether only one candidate ex-warehouse result screened out through the steps S3-S6 exists, if yes, executing the step S8, otherwise, respectively calculating the performance score of each candidate ex-warehouse result, then selecting the candidate ex-warehouse result with the highest performance score of the candidate ex-warehouse results as a final recommendation result, and executing the step S8;
and S8, returning the selected ex-warehouse scheme to the calling layer.
2. The integrated multi-factor intelligent ex-warehouse method according to claim 1, wherein the method comprisesThe calculation method of the library position performance score comprises the following steps: calculating the ex-warehouse cost of each warehouse location, the warehouse location type score and the temporary storage rate of goods in the order placed by the warehouse location, and then weighting and summing all the characteristics to obtain a warehouse location performance score: let the weight of the ex-warehouse cost be WcoutThe weight of the bin type score is WsltThe weight of the temporary protection rate is WrexprThen the bin performance score SlpThe formula is as follows:
Slp＝Wcout*Cout+Wslt*Slt+Wrexpr*Rexpir
Coutrepresents the outbound cost, SltIndicates the bin type score, RexpirRepresenting the clinical rate.
3. The method as claimed in claim 1, wherein the warehouse score s is a multi-factor intelligent warehouse-out methodwarehouseThe calculation method comprises the following steps: let m regions under the warehouse in the screened region combination be { Re }1，Re2，...，RemThe corresponding region is scored as { S }region1,Sregion2,…,SregionmGet the penalty of { C across regions }crossRegion1,CcrossRegion2,…,CcrossRegionmW is the cross-region penalty cost weightcostCRAnd then:
4. the method of claim 1, wherein the performance score of the candidate ex-warehouse result is SresultThe calculation method comprises the following steps: let n regions under the warehouse in the screened region combination be respectively { Wh1,Wh2,…,WhnThe corresponding region is scored as { S }warehouse1,Swarehouse2,…,SwarehousenGet the penalty of { C across regions }crossWh1，CcrossWh2，…，CcrossWhnW is the cross-region penalty cost weightcostCWAnd then:
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