CN109934427B - Method and device for generating item distribution scheme - Google Patents
Method and device for generating item distribution scheme Download PDFInfo
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Abstract
The invention discloses a method and a device for generating an article distribution scheme, and relates to the technical field of computers. One embodiment of the method comprises: comparing the total volume of the articles to be distributed with the total volume of the transportation equipment; determining a scheme decision rule according to the comparison result; and generating an item distribution scheme according to the scheme decision rule. According to the implementation method, the big data can be used for building the model so that the decision of the scheme becomes controllable, the optimal decision can be made without depending on the experience of business personnel, the manpower and material resources are saved, and the efficient generation of the goods distribution scheme is realized.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for generating an article distribution scheme.
Background
With the rapid development of the e-commerce industry, online shopping has become a normal state of society, and the development of the logistics transportation industry is greatly promoted. And the cost of logistics transportation directly determines the profit and market competitiveness of the e-commerce enterprise.
At present, the demand of people on logistics time limit is higher and higher, especially for fresh products. Therefore, some large e-commerce enterprises establish warehouses at different levels, and then allocate the commodities layer by layer to achieve faster distribution of the commodities. Such as: the commodities are allocated to the Beijing city warehouse by the North China regional warehouse, and then the commodities can be directly distributed from the Beijing city warehouse, so that the distribution time is saved.
When the objects are allocated and distributed, generally used transportation equipment (such as airplanes, trains, automobiles and the like) has a fixed capacity, and in order to reduce the transportation cost of each object, business personnel need to fully utilize the loading space of the transportation equipment.
The existing implementation scheme for distributing the articles to the loading space of the transportation equipment mostly depends on the experience of business personnel, and how to distribute the articles to the loading space when the articles need to be distributed is determined by a simple rule according to the volume of the transportation equipment which can be distributed every day, the types of the articles which need to be distributed, the quantity of the articles and the like. Currently, when allocating items to a loading space, if there is remaining space, it is generally determined empirically which items should make up the loading space, for example: according to the latest sales volume of the commodities, the commodities with high sales volume are selected to fill the rest of the loading space so as to share the transportation cost.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
1. the decision making through manual experience is unreliable, and all conditions are difficult to consider, so that a comprehensive optimal decision is difficult to obtain;
2. the selection of the items and the number of items to make up the loading space lacks fixed logic, the decision effect is very unstable, and the decision is not the optimal decision in the long term.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for generating an article allocation scheme, which can use big data to establish a model so that a decision of the scheme becomes controllable, and an optimal decision can be made without depending on experience of business personnel, so that human and material resources are saved, and efficient generation of the article allocation scheme is achieved.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of generating an item distribution scheme.
A method of generating an item distribution scheme, comprising: comparing the total volume of the articles to be distributed with the total volume of the transportation equipment; determining a scheme decision rule according to the comparison result; and generating an item distribution scheme according to the scheme decision rule.
Optionally, the step of determining a scheme decision rule according to the comparison result comprises: if the comparison result is that the total volume of the articles to be distributed is larger than or equal to the total volume of the transportation equipment, determining the scheme decision rule as a picking rule; if the comparison result shows that the total volume of the articles to be distributed is smaller than the total volume of the transport equipment, firstly, for each transport equipment combination, if the total volume of the transport equipment combination is smaller than or equal to the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, if the total volume of the transport equipment combination is larger than the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, and then, evaluating the article distribution scheme generated through the picking rule and the article distribution scheme generated through the picking rule according to a preset evaluation rule to determine a scheme decision rule.
Optionally, the culling rule includes: obtaining a transportation equipment identifier corresponding to each article in the article set to be distributed by a method for solving a knapsack problem; the entry rule includes: firstly, obtaining a transportation equipment identifier corresponding to each article in an article set to be distributed through a greedy algorithm, and then obtaining a transportation equipment identifier corresponding to an article selected from the alternative article set through a method for solving a knapsack problem.
Optionally, the transportation device combination is determined by: determining a transport equipment combination i and a transport equipment combination j meeting the following requirements by comparing the total volume of each transport equipment resource set with the total volume of the articles to be distributed: the transporter group i is the transporter resource group with the total volume of all transporter resource groups meeting that the total volume of the transporter resource group is less than or equal to V1 and closest to V1; the transportation equipment combination j is the transportation equipment resource set which has the closest total volume of all transportation equipment resource sets meeting the condition that the total volume of the transportation equipment resource sets is greater than V1 and V1; wherein V1 is the total volume of the articles to be dispensed.
According to another aspect of embodiments of the present invention, an apparatus for generating an item distribution scheme is provided.
An apparatus for generating an item distribution scheme, comprising: the data comparison module is used for comparing the total volume of the articles to be distributed with the total volume of the transportation equipment; the rule determining module is used for determining a scheme decision rule according to the comparison result; and the scheme generating module is used for generating an article distribution scheme according to the scheme decision rule.
Optionally, the rule determining module is further configured to: if the comparison result is that the total volume of the articles to be distributed is larger than or equal to the total volume of the transportation equipment, determining the scheme decision rule as a picking rule; if the comparison result shows that the total volume of the articles to be distributed is smaller than the total volume of the transport equipment, firstly, for each transport equipment combination, if the total volume of the transport equipment combination is smaller than or equal to the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, if the total volume of the transport equipment combination is larger than the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, and then, evaluating the article distribution scheme generated through the picking rule and the article distribution scheme generated through the picking rule according to a preset evaluation rule to determine a scheme decision rule.
Optionally, the culling rule includes: obtaining a transportation equipment identifier corresponding to each article in the article set to be distributed by a method for solving a knapsack problem; the entry rule includes: firstly, obtaining a transportation equipment identifier corresponding to each article in an article set to be distributed through a greedy algorithm, and then obtaining a transportation equipment identifier corresponding to an article selected from the alternative article set through a method for solving a knapsack problem.
Optionally, the transportation device combination is determined by: determining a transport equipment combination i and a transport equipment combination j meeting the following requirements by comparing the total volume of each transport equipment resource set with the total volume of the articles to be distributed: the transporter group i is the transporter resource group with the total volume of all transporter resource groups meeting that the total volume of the transporter resource group is less than or equal to V1 and closest to V1; the transportation equipment combination j is the transportation equipment resource set which has the closest total volume of all transportation equipment resource sets meeting the condition that the total volume of the transportation equipment resource sets is greater than V1 and V1; wherein V1 is the total volume of the articles to be dispensed.
According to yet another aspect of an embodiment of the present invention, an electronic device for generating an item distribution scheme is provided.
An electronic device that generates an item distribution scheme, comprising: one or more processors; a storage device, configured to store one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the method for generating an item allocation plan provided by an embodiment of the present invention.
According to yet another aspect of embodiments of the present invention, a computer-readable medium is provided.
A computer readable medium having stored thereon a computer program which, when executed by a processor, implements a method of generating an item distribution scheme as provided by embodiments of the invention.
One embodiment of the above invention has the following advantages or benefits: the total volume of the articles to be distributed is compared with the total volume of the transportation equipment, the scheme decision rule is determined according to the comparison result, and then the article distribution scheme is generated according to the scheme decision rule, so that the article distribution scheme can be automatically generated according to the made scheme decision rule, the decision of the scheme becomes controllable, the optimal decision can be made without depending on the experience of business personnel, meanwhile, the manpower and material resources are saved, and the efficient generation of the article distribution scheme is realized. By making different scheme decision rules, the generation of article distribution schemes under different conditions can be realized, so that a comprehensive optimal scheme can be obtained; and the actual problem is modeled by using an operational optimization model (such as a greedy algorithm and a knapsack problem), so that the generated article distribution scheme can be optimized. The article distribution scheme generated by the method can effectively reduce the cost of article allocation and distribution.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
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The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of a main flow of a method of generating an item distribution scheme according to an embodiment of the invention;
FIG. 2 is a flow chart of an implementation of one embodiment of the present invention;
FIG. 3 is a schematic diagram of the major modules of an apparatus for generating an item distribution scheme according to an embodiment of the present invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 5 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In order to solve the problems in the prior art, the invention provides an intelligent method for generating an article allocation scheme, a model is established by utilizing big data so that the decision of the scheme becomes controllable, the optimal decision can be made without depending on the experience of business personnel, the manpower and material resources are saved, and the efficient generation of the article allocation scheme is realized.
Fig. 1 is a schematic diagram of a main flow of a method of generating an item allocation plan according to an embodiment of the present invention. As shown in fig. 1, the method for generating an item allocation plan according to an embodiment of the present invention mainly includes steps S101 to S103 as follows.
Step S101: the total volume of the items to be dispensed is compared in size with the total volume of the transport apparatus.
Before step S101, the related information of the currently available transportation device, and the related information of the to-be-distributed item and the related information of the alternative item involved in the present invention may be acquired in advance. The articles to be distributed and the alternative articles are distinguished according to different emergency degrees required to be allocated, the articles to be distributed refer to the articles required to be allocated currently, and the alternative articles refer to the articles to be allocated.
The following describes how to determine the items to be distributed and the alternative items by taking the example of the distribution of the commodities in the electronic commerce industry. If stock is used to represent actual inventory and LOP is used to represent replenishment points, then assume that the screening logic for the items to be dispensed is: when the stock of a certain commodity sku is less than LOP, the commodity sku is the article to be distributed, and when the certain commodity sku needs replenishment, the transfer system is triggered. The allocation system may obtain the current item set to be allocated S1, that is, the item set with stock < LOP; meanwhile, a set of candidate items to be called S2 may also be obtained, where the screening logic of the candidate items is, for example: if the current stock of a certain product sku is less than 1.5 × LOP, the product sku may be used as a candidate. The sku is a Stock Keeping Unit (Stock Keeping Unit), and in the e-commerce industry, sku generally refers to a commodity, and each commodity corresponds to one sku. In a specific implementation, since the urgency levels of allocation of the to-be-allocated item and the alternative item are different, the acquisition of the item data may be performed by two different modules, respectively. Moreover, the screening logic for the items to be distributed and the alternative items may also be flexibly set or manually intervened according to the needs, and is not limited to the screening logic shown in this embodiment.
The related information of the transportation equipment mainly refers to the identification, volume, transportation cost and other related data of the transportation equipment. The transport device is for example a container vehicle, the transport device identification is for example a vehicle number or license plate number, the volume of the transport device is for example the volume of a container placed on the vehicle, etc. The related information of the to-be-distributed articles comprises related data such as identification, quantity, volume, profit and the like of the to-be-distributed articles; the related information of the alternative item comprises related data such as identification, volume, profit and the like of the alternative item. Meanwhile, the current actual stock of the to-be-distributed item and the alternative item, the point-of-restocking LOP information, the number of days of stock < LOP, the number of days of stock <1.5 × LOP, and the like can be obtained.
From the acquired data, for each item sku in S1, the total volume V1 of all skus in S1 may be calculated from the number and volume that each sku needs to be assigned in S1. The total volume VS of all the transport devices can be calculated according to the volume of each transport device.
The total volume of articles to be dispensed, V1, can then be compared to the total volume of the transport apparatus VS.
Step S102: and determining a scheme decision rule according to the comparison result.
According to the comparison result between V1 and VS in step S101, the scheme decision rule can be determined according to the comparison result.
When executed, step S102 may specifically include the following two cases:
the first condition is as follows: if the comparison result is that the total volume V1 of the articles to be distributed is greater than or equal to the total volume VS of the transportation equipment, determining the scheme decision rule as a picking rule;
case two: if the comparison result shows that the total volume V1 of the articles to be distributed is smaller than the total volume VS of the transport equipment, firstly, for each transport equipment combination, if the total volume of the transport equipment combination is smaller than or equal to the total volume V1 of the articles to be distributed, generating an article distribution scheme through a picking rule, if the total volume of the transport equipment combination is larger than the total volume V1 of the articles to be distributed, generating an article distribution scheme through a picking rule, and then evaluating the article distribution scheme generated through the picking rule and the article distribution scheme generated through the picking rule according to a preset evaluation rule to determine a scheme decision rule.
Wherein, the rules are selected, for example, including: obtaining a transportation equipment identifier corresponding to each article in the article set to be distributed by a method for solving a knapsack problem; the selection rule comprises: firstly, obtaining a transportation equipment identifier corresponding to each article in an article set to be distributed through a greedy algorithm, and then obtaining a transportation equipment identifier corresponding to an article selected from the alternative article set through a method for solving a knapsack problem.
Wherein the transportation device combination in case two can be determined by:
determining a transport equipment combination i and a transport equipment combination j which meet the following requirements by comparing the total volume of each transport equipment resource set with the total volume of the articles to be distributed:
the transportation equipment combination i is the transportation equipment resource set which satisfies that the total volume of the transportation equipment resource sets is less than or equal to V1 and is closest to V1;
the transportation equipment combination j is the transportation equipment resource set which has the closest total volume of the transportation equipment resource sets to V1 and satisfies that the total volume of the transportation equipment resource sets is greater than V1;
wherein V1 is the total volume of the articles to be dispensed.
Here, the transportation device resource set may be made up of one or more of all currently available transportation devices, and then, when there are k available transportation devices, the total number of transportation device resource sets satisfies:
how to determine the scheme decision rule in both cases is described below with reference to a specific embodiment and an implementation flowchart of an embodiment of the present invention shown in fig. 2. The transport device is exemplified by a container vehicle and the item to be distributed and the alternative item are exemplified by the commodity sku.
In case one, if the total volume V1 of the articles to be dispensed is greater than or equal to the total volume VS of the transport apparatus, then it is indicated that the current vehicle cannot accommodate all of the articles to be dispensed. It should be noted that, in the case of loading an article, it is not always possible to achieve a perfect match between the loaded article and the loading space, and there is always a partial wasted space, so that when V1 is VS, it is not possible for the current vehicle to completely accommodate all the articles to be dispensed. In this case, part of the items in the item set S1 to be allocated need to be picked out, and allocation is not performed this time, so the scheme decision rule is determined to be a picking rule.
The step of picking out the rule refers to obtaining the transportation equipment identifier corresponding to each article in the article set to be distributed by a method of solving a knapsack problem. For the articles that are picked out and not allocated for the transfer, the corresponding transportation equipment does not exist, and when the program is implemented, the corresponding transportation equipment identifier can be set to be null.
In a case one, assuming that there are k vehicles available at present, the process of generating the item allocation plan by picking out the rule specifically means that the information of the vehicles to which all skus in the item set S1 to be allocated are allocated can be obtained by sequentially solving k knapsack problems for the k vehicles. In particular implementations, this may be performed as follows.
Step 11: sorting vehicles in order of size increases, and the smaller the vehicle size, the more items it can carry, and therefore the better the selection from the more items to be dispensed. Assume that the volumes of the ranked vehicles are:
VC＝(VC1,VC2,…,VCk)，
wherein VC denotes the vehicle volume, VC1I.e. the volume, VC, of the vehicle 12I.e. the volume, VC, of the vehicle 2kI.e. the volume of the vehicle k.
Step 12: and acquiring the information of the articles to be distributed and the value weight of each sku. Assuming that the number of skus included in the to-be-distributed item set is m, the to-be-distributed item set is: s1 ═ (sku)1,sku2,sku3,…,skum) (ii) a Number to be dialed corresponding to sku in S1: d ═ d (d)1,d2,…,dm) (ii) a Sku-corresponding volume in S1: v0 ═ (V0)1,V02,…,V0m). The value weight is used to describe the item skuiThe price, the volume and the urgency of the call, in one embodiment of the present invention, the item sku in S1iCorresponding value weight ciThe calculation formula of (a) is as follows:
wherein, the daysstocki<LOPi"is a commercial product skuiThe current inventory amount of the terminal is less than the number of days of the replenishment point, the number of daysstocki<1.5×LOPi"is a commercial product skuiThe current inventory amount of (1.5) times the number of days of the replenishment point, the unit of the price of sku is Yuan, and the unit of the volume of sku is cm3。
When the commodities are allocated, sku with higher price per unit volume is allocated by priority allocation, so that the allocation and transportation cost of the commodities is the lowest. Meanwhile, in order to avoid the problem that some skus with large volume and low unit price are always shipped from an area warehouse, and therefore the user experience is poor due to long delivery time, the number of days that the inventory of the skus is less than 1.5 times of the number of days of the replenishment point and the number of days that the inventory of the skus is less than the number of days of the replenishment point are comprehensively considered when the value weight of the commodity sku is calculated, so that skus with severe shortage can be considered, and the average delivery timeliness is guaranteed.
Step 13: for vehicle 1, the distribution scheme for the items in S1 is derived by calculating the following knapsack problem:
xi≤di i＝1,2,3,…,m
where x is a vector of length m, for example: x is the number ofi3 denotes that 3 skus are to be removed from S1iLoaded into the vehicle 1; c. CiIs skuiThe corresponding value weight.
Step 14: updating the vector d, and adding d in the vector diIs updated to "di-xi”，i＝1,2,3,…,m。
Step 15: according to the sequence in step 11, for the next vehicle of the vehicles in step 12, i.e. vehicle 2, step 13 and step 14 are executed, and the solution of the backpack is continuedProblem is only to use the volume VC of the vehicle 1 in the above formula1By substitution into VC2。
Step 16: step 15 is repeatedly performed until the distribution of the items to all vehicles is completed.
According to the above steps 11 to 16, the information of the vehicles to which all skus in the to-be-assigned item set S1 are assigned can be obtained by sequentially solving k knapsack problems for k vehicles.
For case two, if the total volume V1 of the items to be dispensed is less than the total volume VS of the transport device, then the current vehicle is said to be sufficient to contain all of the items to be dispensed. Also, there may be a remaining loading space or a remaining vehicle after all the items to be allocated in S1 are allocated to the vehicle. At this time, it is necessary to first determine a transportation apparatus combination that satisfies the requirements. Assuming that the number of available vehicles is k, the number of all vehicle resource sets satisfies:
by comparing the total volume of each transportation device resource set with the total volume V1 of the items to be distributed, a transportation device combination i and a transportation device combination j meeting the following requirements can be determined:
the transportation equipment combination i is the transportation equipment resource set which satisfies that the total volume of the transportation equipment resource sets is less than or equal to V1 and is closest to V1; the transportation equipment combination j is the transportation equipment resource set which has the closest total volume of the transportation equipment resource sets to V1 and satisfies that the total volume of the transportation equipment resource sets is greater than V1; wherein V1 is the total volume of the articles to be dispensed.
It should be noted that: although the volume of each transportation device is not exactly the same, the total volume of the transportation device resource set may be the same, and therefore, the transportation device combination i or the transportation device combination j screened out according to the comparison between the total volume of the transportation device resource set and the total volume V1 of the items to be distributed may not be unique.
For each combination of transport equipment, if the total volume of the combination of transport equipment is less than or equal to V1, generating an item allocation plan through picking rules; if the total volume of the transport equipment assembly is greater than V1, an item allocation plan is generated by the pick-in rule. That is, for the transportation equipment combination i, an item allocation scheme is generated through picking out rules; and for the transport equipment combination j, generating an item distribution scheme through a pick-in rule.
The process of generating the item distribution plan by picking up the rule is as described in the first case, namely, step 11 to step 16. The following is a general description of the process of generating an item allocation plan by entering rules. According to the technical scheme of the embodiment of the invention, firstly, the transportation equipment identifier corresponding to each article in the article set S1 to be distributed is obtained through a greedy algorithm, and then the transportation equipment identifier corresponding to the article selected from the alternative article set S2 is obtained through a method for solving a knapsack problem.
Greedy algorithm (also known as greedy algorithm) means that when solving a problem, the choice that seems best at the present time is always made. That is, rather than being considered globally optimal, he makes a locally optimal solution in some sense. The greedy algorithm can not obtain an overall optimal solution for all problems, and the key is selection of a greedy strategy, and the selected greedy strategy has no after effect, namely, the previous process of a certain state cannot influence the later state and is only related to the current state.
In the embodiment of the present invention, the process of assigning vehicles to all skus in S1 by the greedy algorithm mainly includes the following steps:
step 21: assuming that the number of vehicles is k, the remaining volumes of the vehicles are ranked from small to large. Assuming that the remaining volumes of the ranked vehicles are:
VCL＝(VCL1,VCL2,…,VCLk)，
where VCL represents the vehicle residual volume, VCL1I.e. the residual volume, VCL, of the vehicle 12I.e. the residual volume, VCL, of the vehicle 2kI.e. the remaining volume of the vehicle k. The initial value of the remaining volume of the vehicle is the volume of the vehicle and the remaining volume reduces the volume of the inserted items after each insertion.
Step 22: obtaining information of the item and a value weight c of each sku in S1i. Assuming that the number of skus included in the to-be-distributed item set is m, the to-be-distributed item set is: s1 ═ (sku)1,sku2,sku3,…,skum) (ii) a Number to be dialed corresponding to sku in S1: d ═ d (d)1,d2,…,dm) (ii) a Sku-corresponding volume in S1: v0 ═ (V0)1,V02,…,V0m)。
Step 23: selecting sku with the highest bid value weight from S1: skujJ is 1,2, …, m. Wherein, the comparison can be performed according to the value weight of each sku in step 22.
Step 24: starting from the first vehicle, the remaining volume VCL of the current vehicle is judged1Whether or not it is greater than skujVolume V0jIf yes, go to step 25; if not, step 26 is performed.
Step 25: one sku is heldjPut into the current vehicle and update the VCL1And skujNumber d ofj: will VCL1Is updated to (VCL)1–V0j) D is mixingjIs updated to (d)j-1); then, step 28 is performed.
Step 26: the current vehicle is pointed to the next vehicle, and whether the residual volume of the next vehicle is more than sku or not is judgedjVolume V0jIf yes, go to step 25; if not, step 26 is repeated until all vehicles are traversed, and then step 27 is performed.
Step 27: direct handle skujDelete from S1 set (corresponding d)jAnd V0jAll deleted), which means the remaining skujThis call is no longer made. Then, the process returns to step 23 until all the items in S1 are dispensed.
Step 28: judging updated djWhether or not it is equal to 0, if djIf 0, step 29 is executed, otherwise, step 26 is executed.
Step 29: handle skujDelete from S1, and correspondingly, put skujNumber of dialsQuantity djAnd volume V0jDeleted from vector d and vector V0, respectively, and then returned to step 23 until all items in S1 have been assigned.
According to the above steps 21 to 29, the vehicles assigned to all skus in S1 can be obtained by a greedy algorithm. Then, the transportation device identifier corresponding to the item picked from the alternative item set S2 is obtained by solving the knapsack problem.
Since the total volume V1 of articles to be dispensed is less than the total volume of the combination of transport apparatus j, the sum of the remaining volumes of each vehicle must be greater than zero after all the articles in S1 have been dispensed. Assuming that the remaining volumes of the k vehicles at this time are respectively: vclr ═ vclr1,vclr2,…,vclrk}. Then some sku may be found from the alternative item set S2 to fill the remaining space at this point.
When the remaining space is filled with the items from S2, an accurate global optimization algorithm can be used to solve this problem: selecting a few skus from S2 maximizes the overall profitability of the call while not exceeding the capacity limit of the vehicle. In embodiments of the present invention, this problem may be solved by a method of solving a knapsack problem.
In general, at this time, the remaining space of each vehicle is limited, and therefore the number of candidate skus that can be selected is not large, so that when solving the knapsack problem, the number of candidate skus does not need to be considered, and only the value weight can be considered. And the knapsack problem can be solved for k vehicles with residual space at the same time. In specific implementation, it can also be set according to needs whether to solve k vehicles sequentially, or solve k vehicles simultaneously in parallel, and whether to need sorting, etc.
In the embodiment of the present invention, it is assumed that the number of skus included in the candidate item set is m, and the candidate item set S2 is (sku)21,sku22,sku23,…,sku2m) And volumes corresponding to all skus in S2: v2 ═ (V2)1,V22,…,V2m). For the first vehicle, the assignment of the alternative sku is obtained by solving the following knapsack problem:
where x is a vector of length m, for example: x is the number ofi3 denotes that 3 skus are to be removed from S22iLoaded into the vehicle 1; c. CiIs sku2iThe corresponding value weight.
For other vehicles, all skus and their corresponding assignments chosen from S2 can be obtained by continuing to solve the knapsack problem, except that the remaining volume vclr of the vehicle 1 in the above formula is used to solve the knapsack problem1Accordingly replaced by vclr2、vclr3、…vclrkAnd (4) finishing.
According to the above description, first, all the vehicles assigned to sku in S1 are obtained by a greedy algorithm; then, the vehicles correspondingly allocated to the articles picked from the alternative article set S2 are obtained by solving the knapsack problem, that is, the article allocation scheme can be generated according to the picking rule.
And finally, evaluating the article distribution scheme generated by the picking-out rule and the article distribution scheme generated by the picking-in rule according to a preset evaluation rule so as to determine a scheme decision rule.
According to the item allocation plan generated by the picking rule, the information about the items picked from S1 and not participating in the allocation of the current call can be obtained, for example: item identification, item quantity, profit, and the like. The vector composed of these picked skus is denoted as S3.
According to the item allocation plan generated by the pick-in rule, the information on the items to be picked from S2 and to be allocated in the current allocation can be obtained, for example: item identification, item quantity, profit, and the like. The vector composed of these picked skus is denoted as S4.
The specific logic for evaluating the item allocation plan generated by the pick-out rule and the item allocation plan generated by the pick-in rule according to the evaluation rule is as follows:
the profit margin and profit margin m3 of all skus in S3 and profit margin m4 of all skus in S4 are calculated, respectively, and then the total transportation cost p1 of the transportation equipment combination i (the item allocation plan is generated by the pick-out rule) and the total transportation cost p2 of the transportation equipment combination j (the item allocation plan is generated by the pick-in rule) are calculated, respectively. If m3+ m4 is more than or equal to p2-p1, selecting a transport equipment combination j, and generating an article distribution scheme through a picking rule; otherwise, selecting the transport equipment combination i, and generating an item distribution scheme through the picking rule.
And determining whether the scheme decision rule in the second case is a picking rule or a picking rule according to the evaluation rule.
According to step S102, a decision rule of the scheme may be determined according to a comparison of the total volume of the items to be dispensed and the total volume of the transport device.
Step S103: and generating an item distribution scheme according to the scheme decision rule, wherein the item distribution scheme comprises the association relationship among the transportation equipment, the items and the quantity of the items.
According to the scheme decision rule determined in step S102, a corresponding article distribution scheme can be obtained. The item allocation scheme mainly refers to the association relationship among the transportation equipment, the items and the quantity of the items. And according to the item distribution scheme, the interface allocates the items.
According to the steps S101 to S103, the total volume of the articles to be distributed can be compared with the total volume of the transportation equipment, the scheme decision rule is determined according to the comparison result, then the article distribution scheme is generated according to the scheme decision rule, the article distribution scheme can be automatically generated according to the formulated scheme decision rule, the decision of the scheme is controllable, the optimal decision can be made without depending on the experience of business personnel, meanwhile, the manpower and material resources are saved, and the efficient generation of the article distribution scheme is realized. By making different scheme decision rules, the generation of article distribution schemes under different conditions can be realized, so that a comprehensive optimal scheme can be obtained; and the actual problem is modeled by using an operational optimization model (such as a greedy algorithm and a knapsack problem), so that the generated article distribution scheme can be optimized. The article distribution scheme generated by the method can effectively reduce the cost of article allocation and distribution.
FIG. 3 is a schematic diagram of the major modules of an apparatus for generating an item distribution scheme according to an embodiment of the present invention. As shown in fig. 3, an apparatus 300 for generating an item allocation plan according to an embodiment of the present invention mainly includes a data comparison module 301, a rule determination module 302, and a plan generation module 303.
The data comparison module 301 is used for comparing the total volume of the articles to be distributed with the total volume of the transportation equipment;
the rule determining module 302 is configured to determine a scheme decision rule according to the comparison result;
the scenario generation module 303 is configured to generate an item allocation scenario according to the scenario decision rule.
According to the technical solution of the present invention, the rule determining module 302 may further be configured to:
if the comparison result is that the total volume of the articles to be distributed is larger than or equal to the total volume of the transportation equipment, determining the scheme decision rule as a picking rule;
if the comparison result shows that the total volume of the articles to be distributed is smaller than the total volume of the transport equipment, firstly, for each transport equipment combination, if the total volume of the transport equipment combination is smaller than or equal to the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, if the total volume of the transport equipment combination is larger than the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, and then, evaluating the article distribution scheme generated through the picking rule and the article distribution scheme generated through the picking rule according to a preset evaluation rule to determine a scheme decision rule.
Wherein the culling rule comprises: obtaining a transportation equipment identifier corresponding to each article in the article set to be distributed by a method for solving a knapsack problem;
the entry rule includes: firstly, obtaining a transportation equipment identifier corresponding to each article in an article set to be distributed through a greedy algorithm, and then obtaining a transportation equipment identifier corresponding to an article selected from the alternative article set through a method for solving a knapsack problem.
According to the technical scheme of the embodiment of the invention, the transportation equipment combination is determined by the following steps:
determining a transport equipment combination i and a transport equipment combination j which meet the following requirements by comparing the total volume of each transport equipment resource set with the total volume of the articles to be distributed:
the transporter group i is the closest transporter resource group to V1 in all transporter resource groups satisfying that the total volume of the transporter resource group is not more than V1;
the transportation equipment combination j is the transportation equipment resource set which is closest to the V1 in all transportation equipment resource sets which meet the condition that the total volume of the transportation equipment resource sets is larger than V1;
wherein V1 is the total volume of the articles to be dispensed.
According to the technical scheme of the embodiment of the invention, the total volume of the articles to be distributed is compared with the total volume of the transportation equipment, the scheme decision rule is determined according to the comparison result, and then the article distribution scheme is generated according to the scheme decision rule, so that the article distribution scheme can be automatically generated according to the formulated scheme decision rule, the decision of the scheme becomes controllable, the optimal decision can be made without depending on the experience of business personnel, meanwhile, the manpower and material resources are saved, and the efficient generation of the article distribution scheme is realized. By making different scheme decision rules, the generation of article distribution schemes under different conditions can be realized, so that a comprehensive optimal scheme can be obtained; and the actual problem is modeled by using an operational optimization model (such as a greedy algorithm and a knapsack problem), so that the generated article distribution scheme can be optimized. The article distribution scheme generated by the method can effectively reduce the cost of article allocation and distribution.
Fig. 4 illustrates an exemplary system architecture 400 to which the method of generating an item allocation plan or the apparatus for generating an item allocation plan of embodiments of the present invention may be applied.
As shown in fig. 4, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405. The network 404 serves as a medium for providing communication links between the terminal devices 401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal devices 401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The terminal devices 401, 402, 403 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 401, 402, 403. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the method for generating an item allocation plan provided by the embodiment of the present invention is generally executed by the server 405, and accordingly, an apparatus for generating an item allocation plan is generally disposed in the server 405.
It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, a block diagram of a computer system 500 suitable for use with a terminal device or server implementing an embodiment of the invention is shown. The terminal device or the server shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU)501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 501.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present invention may be implemented by software, or may be implemented by hardware. The described units or modules may also be provided in a processor, and may be described as: a processor includes a data comparison module, a rule determination module, and a schema generation module. Where the names of these units or modules do not in some way constitute a limitation on the units or modules themselves, for example, the data comparison module may also be described as a "module for comparing the total volume of articles to be dispensed with the total volume of the transport equipment.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: comparing the total volume of the articles to be distributed with the total volume of the transportation equipment; determining a scheme decision rule according to the comparison result; and generating an item distribution scheme according to the scheme decision rule.
According to the technical scheme of the embodiment of the invention, the total volume of the articles to be distributed is compared with the total volume of the transportation equipment, the scheme decision rule is determined according to the comparison result, and then the article distribution scheme is generated according to the scheme decision rule, so that the article distribution scheme can be automatically generated according to the formulated scheme decision rule, the decision of the scheme becomes controllable, the optimal decision can be made without depending on the experience of business personnel, meanwhile, the manpower and material resources are saved, and the efficient generation of the article distribution scheme is realized. By making different scheme decision rules, the generation of article distribution schemes under different conditions can be realized, so that a comprehensive optimal scheme can be obtained; and the actual problem is modeled by using an operational optimization model (such as a greedy algorithm and a knapsack problem), so that the generated article distribution scheme can be optimized. The article distribution scheme generated by the method can effectively reduce the cost of article allocation and distribution.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A method of generating an item distribution scheme, comprising:
comparing the total volume of the articles to be distributed with the total volume of the transportation equipment;
determining a scheme decision rule according to the comparison result;
generating an item distribution scheme according to the scheme decision rule;
the step of determining a scheme decision rule based on the comparison comprises:
if the comparison result is that the total volume of the articles to be distributed is larger than or equal to the total volume of the transportation equipment, determining the scheme decision rule as a picking rule;
if the comparison result is that the total volume of the articles to be distributed is smaller than the total volume of the transport equipment, firstly, for each transport equipment combination, if the total volume of the transport equipment combination is smaller than or equal to the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, if the total volume of the transport equipment combination is larger than the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, and then, evaluating the article distribution scheme generated through the picking rule and the article distribution scheme generated through the picking rule according to a preset evaluation rule to determine a scheme decision rule;
the picking rule comprises the following steps: the method for solving the knapsack problem is used for obtaining the transportation equipment identifier corresponding to each article in the article set to be distributed, and comprises the following steps:
sorting the transportation equipment from small to large according to the volume, and acquiring information of the articles to be distributed and a value weight of each article, wherein the value weight is used for describing the relationship between the price and the volume of the articles and the emergency degree of allocation;
for each transport facility, an item allocation plan is derived by calculating the following knapsack problem until the item allocation is completed for all transport facilities:
max:
xi≤di i＝1,2,3,…,m
where x is a vector of length m, xiIndicating that sku is to be removed from the collection of items to be dispensediLoading the distribution equipment into the transportation equipment, wherein i is 1,2,3, …, m is the number of the items sku in the item set to be distributed; c. CiIs an article skuiA corresponding value weight; v0iGathering sku for items to be distributediA corresponding volume; VC (vitamin C)kThe volume of the current transportation equipment; diGathering sku for items to be distributediThe corresponding number to be dialed;
then d in the vector d is updatedi；
The entry rule includes: firstly, obtaining a transportation equipment identifier corresponding to each article in an article set to be distributed through a greedy algorithm, and then obtaining a transportation equipment identifier corresponding to an article selected from an alternative article set through a method for solving a knapsack problem;
evaluating the article distribution scheme generated by the picking-out rule and the article distribution scheme generated by the picking-in rule according to a preset evaluation rule to determine a scheme decision rule, wherein the scheme decision rule comprises the following steps:
calculating profit sum m3 of all items in the item distribution plan generated by the pick-out rule, profit sum m4 of all items in the item distribution plan generated by the pick-in rule, total transportation cost p1 of the item distribution plan generated by the pick-out rule and total transportation cost p2 of the item distribution plan generated by the pick-in rule, respectively;
if m3+ m4 is more than or equal to p2-p1, determining the scheme decision rule as a pick-in rule; otherwise, determining the scheme decision rule as a picking rule.
2. The method of claim 1, wherein the transportation device combination is determined by:
determining a transportation equipment combination a and a transportation equipment combination j meeting the following requirements by comparing the total volume of each transportation equipment resource set with the total volume of the articles to be distributed:
the transporter group a is the transporter resource group with the total volume of all transporter resource groups meeting that the total volume of the transporter resource group is less than or equal to V1 and closest to V1;
the transportation equipment combination j is the transportation equipment resource set which has the closest total volume of all transportation equipment resource sets meeting the condition that the total volume of the transportation equipment resource sets is greater than V1 and V1;
wherein V1 is the total volume of the articles to be dispensed.
3. An apparatus for generating an item distribution scheme, comprising:
the data comparison module is used for comparing the total volume of the articles to be distributed with the total volume of the transportation equipment;
the rule determining module is used for determining a scheme decision rule according to the comparison result;
the scheme generation module is used for generating an article distribution scheme according to the scheme decision rule;
the rule determination module is further to:
if the comparison result is that the total volume of the articles to be distributed is larger than or equal to the total volume of the transportation equipment, determining the scheme decision rule as a picking rule;
if the comparison result is that the total volume of the articles to be distributed is smaller than the total volume of the transport equipment, firstly, for each transport equipment combination, if the total volume of the transport equipment combination is smaller than or equal to the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, if the total volume of the transport equipment combination is larger than the total volume of the articles to be distributed, generating an article distribution scheme through a picking rule, and then, evaluating the article distribution scheme generated through the picking rule and the article distribution scheme generated through the picking rule according to a preset evaluation rule to determine a scheme decision rule;
the picking rule comprises the following steps: the method for solving the knapsack problem is used for obtaining the transportation equipment identifier corresponding to each article in the article set to be distributed, and comprises the following steps:
sorting the transportation equipment from small to large according to the volume, and acquiring information of the articles to be distributed and a value weight of each article, wherein the value weight is used for describing the relationship between the price and the volume of the articles and the emergency degree of allocation;
for each transport facility, an item allocation plan is derived by calculating the following knapsack problem until the item allocation is completed for all transport facilities:
max:
xi≤di i＝1,2,3,…,m
where x is a vector of length m, xiIndicating that sku is to be removed from the collection of items to be dispensediLoading into the transportation equipment, i is 1,2,3, …, m is mDistributing the number of the objects sku included in the object set; c. CiIs an article skuiA corresponding value weight; v0iGathering sku for items to be distributediA corresponding volume; VC (vitamin C)kThe volume of the current transportation equipment; diGathering sku for items to be distributediThe corresponding number to be dialed;
then d in the vector d is updatedi；
The entry rule includes: firstly, obtaining a transportation equipment identifier corresponding to each article in an article set to be distributed through a greedy algorithm, and then obtaining a transportation equipment identifier corresponding to an article selected from an alternative article set through a method for solving a knapsack problem;
the rule determination module is further to:
calculating profit sum m3 of all items in the item distribution plan generated by the pick-out rule, profit sum m4 of all items in the item distribution plan generated by the pick-in rule, total transportation cost p1 of the item distribution plan generated by the pick-out rule and total transportation cost p2 of the item distribution plan generated by the pick-in rule, respectively;
if m3+ m4 is more than or equal to p2-p1, determining the scheme decision rule as a pick-in rule; otherwise, determining the scheme decision rule as a picking rule.
4. The apparatus of claim 3, wherein the combination of transport devices is determined by:
determining a transportation equipment combination a and a transportation equipment combination j meeting the following requirements by comparing the total volume of each transportation equipment resource set with the total volume of the articles to be distributed:
the transporter group a is the transporter resource group with the total volume of all transporter resource groups meeting that the total volume of the transporter resource group is less than or equal to V1 and closest to V1;
the transportation equipment combination j is the transportation equipment resource set which has the closest total volume of all transportation equipment resource sets meeting the condition that the total volume of the transportation equipment resource sets is greater than V1 and V1;
wherein V1 is the total volume of the articles to be dispensed.
5. An electronic device that generates an item distribution scheme, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-2.
6. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-2.
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