CN112884227A

CN112884227A - Sheet splitting supply method for group purchase combination sheet

Info

Publication number: CN112884227A
Application number: CN202110201498.8A
Authority: CN
Inventors: 郑鑫; 霍胜军; 徐楠楠
Original assignee: Qingdao Mengdou Network Technology Co ltd
Current assignee: Qingdao Mengdou Network Technology Co ltd
Priority date: 2021-02-23
Filing date: 2021-02-23
Publication date: 2021-06-01

Abstract

The invention provides a group purchase order splitting supply method, which comprises the following steps: (1) determining group purchase information, including determining purchased products, suppliers and supply amount; (2) determining a buyer participating in purchasing and a purchasing amount; (3) and determining an optimal delivery path, namely confirming the supply and acquisition corresponding relation between the buyer and the supplier and the corresponding supply quantity between the supplier and the buyer. The method for determining the optimal delivery path comprises the following steps: analyzing and listing a balance matrix for mining and a unit freight rate matrix; determining an initial allocation and transportation method by a Voger method; solving the test number by adopting a potential method; judging whether all the check numbers are greater than or equal to 0; if yes, obtaining an optimal scheme; if not, finding out the minimum negative check number, and obtaining a new allocation and transportation scheme by using a closed loop adjustment method. Aiming at the group purchase order combination of the B2B platform, the method can realize automatic supply-acquisition matching and supply quantity confirmation, reduce the transportation cost, reduce the transportation time to a certain extent and improve the working efficiency.

Description

Sheet splitting supply method for group purchase combination sheet

Technical Field

The invention belongs to the technical field of electronic commerce, and particularly relates to a group purchase order splitting supply method for a group purchase order.

Background

In the traditional industry, the situations of various varieties, disordered channels, transverse false goods and the like generally exist in the large-scale enterprises for a long time in the raw material purchasing process, and the pain point of the industry is obvious. In addition, because the traditional industry faces the downward economic pressure, under the 'internet +' hot tide, transformation expansion is sought in a dispute, and in addition to diversification of products and marketing channels, online purchasing by means of B2B is expected to reduce the purchasing cost. In this context, the B2B platform, which enables more vendors to benefit from it and provides industry-depth services, will likely show advantageous effects.

In the last two years, B2B e-commerce has grown rapidly, even leveraging trillion market-scale, but long-term, relatively traditionally closed areas such as steel, machinery, chemical, raw materials, etc. Even so, the class B market is not easy to do, the stock and response speed cannot be kept up with, the matching efficiency is low, the wholesalers and the distributors are reluctant to participate, the resource control is insufficient, and the like, which become a plurality of bottlenecks in the development of the toggle B2B platform.

At present, a B2B e-commerce platform has a new ecological operation mode of group buying, and not only helps a buyer to obtain the optimal quality and the optimal price under the service through the group buying activity, thereby reducing the purchasing cost of an enterprise, but also helps a supplier to obtain the increase of the users with the highest quantity by the cheapest investment, thereby expanding the brand awareness of the enterprise and promoting the enterprise to enter a virtuous circle development track.

However, the prior art is lack of an effective method for the problems of how to organize the delivery of suppliers, how to match the suppliers and how to allocate the quantities of the suppliers and the purchase parties, and the like of the group purchase order sharing on the B2B platform.

Disclosure of Invention

The purpose of the invention is: aiming at the problems described in the background technology, the invention provides a sheet splitting and supplying method for group purchase assembly sheets, aiming at the group purchase assembly sheet activity of a B2B electronic commerce platform, the automatic supply, acquisition, matching and supply quantity confirmation can be realized, the transportation cost can be reduced, the transportation time can be reduced to a certain extent, and the working efficiency is improved.

In order to solve the problems, the technical scheme adopted by the invention is as follows:

a form splitting and supplying method for group purchase combination forms is characterized by comprising the following steps:

(1) determining group purchase information, including determining purchased products, suppliers and supply amount;

(2) determining a buyer participating in purchasing and a purchasing amount;

(3) and determining an optimal delivery path, namely confirming the supply and acquisition corresponding relation between the buyer and the supplier and the corresponding supply quantity between the supplier and the buyer.

Further, determining the group purchase information in the step (1): the method for determining the purchased products can directly adopt the products which are ranked at the top of the frequency of the products which are searched, browsed, added into a shopping cart or bought by placing orders in a platform within a period of time as the group purchase products, thereby determining the supply quantity provided by n suppliers and the group purchase thereof.

Further, the determining of the group purchase information in the step (1) includes:

step (1.1): obtaining the times of products which are inquired, browsed, added into a shopping cart and purchased by a platform in a period of time;

step (1.2): calculating a matrix T: t ═ T₁，t₂，t₃，…，t_i，…]

Wherein t is_iAnd (3) representing the specifically calculated t value of the product i, wherein the calculation formula of t is as follows: t is t_q+t_g+t_s-t_b；

Wherein, t_qRepresenting number of platform queries, t_gIndicates the number of times of browsing of the platform, t_sIndicating the number of times the platform has joined the shopping cart, t_bIndicating the number of purchases;

step (1.3): calculating the sales volume of the products in the time period of the last year, and checking the sales peaks of the products, namely the products with larger increase of the sales of the products in the time period; the calculation method comprises the following steps: determining the time in the time period by taking the time for starting calculation as the starting point of the time period, determining other time periods forwards and backwards by the time period, and checking whether the sales condition of the product is at the peak position of the bulge or not; if so, the current product is the peak value sale product in the period of time;

step (1.4): confirming the product: sorting the values of the matrix T from large to small, and selecting a product i which has a larger value T and is sold at the peak value as the group purchase product at the time; when products are confirmed, whether the products are peak value sales products or not is searched downwards according to the sequence of the products in the T by taking the sorted matrix T as a reference until the peak value sales products are found; if no peak value sale product is found finally, taking the product with the maximum T value in the matrix T as a final group purchase product;

step (1.5): confirming the product supplier: and confirming the corresponding inventory of the supplier of the product on the platform, and confirming the n suppliers and the supply amount provided by the group buying party.

Further, the step (2) of determining the buyer and the amount of the purchase participating in the purchase includes the specific steps of:

step (2.1): starting group buying and grouping, and participating in and determining the purchasing quantity by a buyer;

step (2.2): confirming the number of the purchasers and the corresponding purchase amount of each purchaser, and reminding the purchasers of the current residual supply amount and the residual grouping time in real time, wherein the time is adjusted according to the products participating in grouping and the number of the products;

step (2.3): confirming whether the grouping is successful or not, if the total purchasing quantity of the buyer is larger than or equal to the minimum grouping purchasing quantity, successfully grouping and finishing, wherein the minimum grouping purchasing quantity needs to be set in advance when grouping is initiated, and the minimum grouping purchasing quantity is smaller than or equal to the total supply quantity; if the total purchase amount is less than the minimum conglomeration purchase amount within the specified time, conglomeration cannot be achieved;

step (2.4): confirming the grouped buyers and the corresponding purchase amounts.

Further, the optimal delivery path is determined in the step (3), and the method comprises the following steps:

record the set of suppliers as: a ═ A₁，A₂，A₃，…，A_i，…，A_n]

The set of supply quantities corresponding to the suppliers is recorded as: a ═ a₁，a₂，a₃，…，a_i，…，a_n]

Record the set of buyers as: b ═[B₁，B₂，B₃，…，B_j，…,B_m]

The corresponding purchase amount set of the buyer is recorded as: b ═ b₁，b₂，b₃,…,b_j,…,b_m]

The transportation cost is defined as:

wherein W (A, B) represents the total transportation cost of the supplier to the supplier, c_ijIndicates supplier A_iTransporting to buyer B_jTransporting unit price of f_ijIndicates supplier A_iTransporting to buyer B_jThe supply amount of (c);

constraint conditions are as follows:

wherein f is_ijThe direction and the quantity of purchase are described, 1- (1) the direction of element movement in the characteristic distribution is described, the product can be supplied to B only from A and cannot be reversed; 1- (2) description of_iThe total number of supplies must not exceed a_iA total supply amount; 1- (3), description b_jTotal number of purchases must not exceed b_jTotal purchase amount of;

an objective function:

further, the method for determining the optimal delivery path in the step (3) comprises:

analyzing actual problems, and listing a balance matrix for mining and a unit freight rate matrix;

determining an initial allocation and transportation method by a Voger method;

solving the test number by adopting a potential method;

judging whether all the check numbers are greater than or equal to 0; if yes, obtaining an optimal scheme; if not, finding out the minimum negative check number, and obtaining a new allocation and transportation scheme by using a closed loop adjustment method.

Further, the determining the optimal delivery path in the step (3) specifically includes:

and (3.1) giving an initial supply and mining scheme, wherein an initial feasible solution is as follows: that is, a (m + n-1) specific digital value is given on a balance matrix for acquisition with (m × n) spaces, that is, n rows and m columns;

the method comprises the following steps: selecting a position; calculating the penalty number of each row and each column for the transportation unit price matrix C with n rows and m columns, wherein the penalty number is the difference between the minimum transportation cost and the second minimum transportation cost in each column or each row, namely the penalty number is the second minimum transportation cost-the minimum transportation cost; selecting the corresponding row or column where the maximum penalty number is located, and selecting the minimum freight on the corresponding row or column, wherein the corresponding position is the position of the next step; if two or more rows and columns with the maximum penalty number and the same penalty number occur, selecting the row or column corresponding to the minimum freight in the rows and columns as the row or column of the operation, wherein the position of the minimum freight is the position of the next step;

step two: determining a fill-in value f_ijRepresenting the amount of supply from the supplier to the buyer; filling the corresponding position of the minimum element in the corresponding position obtained in the last step in the equilibrium supply matrix according to the Voger method, namely the corresponding position of the maximum penalty number in the row or the column corresponding to the minimum element, wherein the value which enables the row or the column of the position to reach the upper limit is the smaller value of the rest values of the row or the column, namely the upper limit of at least one rest value of the row or the column can be reached, and the purchase amount or the supply amount is updated; when the corresponding row or column reaches the upper limit of the residual value, the residual quantity of the corresponding row or column is updated;

step three: drawing out the supply or purchase amount in the transportation unit price matrix, namely, the corresponding row or column which reaches the upper limit is no longer supplied with supply or purchase, wherein, the row corresponds to the supply condition, and the column corresponds to the purchase condition;

step four: and calculating the penalty number corresponding to each row or each column in the rest transportation unit price matrixes until all elements in the transportation unit price matrixes are scratched out, namely all supply quantities and purchase quantities are met or all purchase quantities are met.

Further, the determining the optimal delivery path in the step (3) specifically includes: step (3.2) optimality judgment:

the method comprises the following steps: determining a group of potential of each row and column according to the condition that the check number of the base variable is 0: c. C_ij＝u_i+v_j(ii) a Wherein c is_ijIs represented by (A)_i,B_j) Unit price of transport of u_iIndicating the row bit potential, v, of row i_jColumn potentials, each for v, representing the j-th column₁Setting an initial value as 1, and calculating corresponding row potential and column potential; wherein the base variable is a position with a value in the initial feeding scheme; non-base variables, i.e., positions in the initial solution where there is no corresponding value;

step two: calculating the check number of any non-base variable, wherein the check number of the base variable is 0; the check number calculation formula is as follows: sigma_ij＝c_ij-(u_i+v_j)，σ_ijRepresenting the corresponding check number at the ith row and j column position;

step three: if the check number of the non-basic variable in the check number matrix satisfies sigma_ijIf the rate is more than or equal to 0, the scheme is the optimal mining scheme; and if not, entering a scheme adjusting stage to adjust the scheme.

Further, the determining the optimal delivery path in the step (3) specifically includes: step (3.3) adjustment of the mining scheme: if the value less than 0 exists in the check number matrix, entering the step to carry out scheme adjustment;

the method comprises the following steps: determining a base variable, wherein the base variable is a position corresponding to the minimum negative test number; determining the minimum check number in the non-base variables, namely, enabling the non-base variable corresponding to the position with the minimum check number to enter the base, and changing the non-base variable into the base variable; when a plurality of non-base variables are less than 0 and equal, any one non-base variable can be used as a base variable;

step two: determining an adjusted closed loop; starting from the position of the minimum negative test number, advancing along the horizontal direction or the vertical direction, rotating by 90 degrees when encountering the position of a basic variable, continuing to advance until returning to the position of the minimum negative test number, wherein when the position of the matrix is exceeded in the horizontal direction or the vertical direction, different directions are selected again to start, and a closed broken line path consisting of a horizontal line segment and a vertical line segment is formed, namely a closed loop; on a closed loop where the minimum negative test number is located, taking the minimum value of the element as the minimum adjustment amount to ensure that each component is still a positive value after adjustment, namely the scheme is still a basic feasible solution;

step three: and (3) scheme adjustment: the adjustment quantity is the value of the minimum element on the closed loop, the adjustment quantity is added to the odd point, and the adjustment quantity is subtracted from the even point, so that the adjusted scheme is obtained; the position of the minimum negative test number is taken as the first odd vertex, which is called odd point for short, the next vertex is taken as the even vertex, which is called even point for short, and the parity points and the even points are analogized downwards, and the odd points and the even points alternately appear;

step four: judging whether the supply mining scheme is the optimal supply mining scheme; and entering optimality judgment until the current scheme is the optimal supply and mining scheme, finishing scheme adjustment and outputting the optimal supply and mining scheme.

Further, the determining the optimal delivery path in the step (3) specifically includes: step (3.4) confirming the optimal delivery path and supply amount; determining a delivery path, namely the corresponding relation between a supplier and a buyer and the corresponding supply quantity thereof according to the determined optimal supply and collection scheme by optimality judgment, and delivering according to the optimal supply and collection scheme by the system; the minimum transportation cost at this time is calculated as:

the technical scheme provided by the embodiment of the invention has the beneficial effects that at least: the form splitting supply method for the group purchase combination form has the advantages that:

(1) the automatic bill removing function can be realized, the supplier can be automatically matched with a buyer, and the specific supply amount is determined;

(2) the transportation cost can be reduced on the basis of ensuring complete supply, and the transportation time can be reduced to a certain extent (the general transportation cost reflects the transportation time);

(3) manual intervention is reduced, and full process automation of group purchase order splitting is realized.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:

fig. 1 is a flowchart of a group purchase order splitting and supplying method according to an embodiment of the present invention.

Fig. 2 is a flowchart for determining an optimal delivery path according to an embodiment of the present invention.

DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

As shown in fig. 1, an embodiment of the present invention provides a group buying and assembling method. Aiming at the group purchase order combining activity of the B2B e-commerce platform, the method can realize automatic supply and acquisition matching and supply quantity confirmation, and realize the full process automation of group purchase order splitting. The method comprises the following steps: firstly, determining group purchase information, including determination of purchased products, determination of suppliers and supply quantity; secondly, determining the purchasing suppliers and purchasing amount participating in purchasing; and thirdly, determining an optimal delivery path, namely confirming the supply and acquisition corresponding relation between the buyer and the supplier and the corresponding supply amount between the supplier and the buyer. The process of the present invention is described in detail below.

Firstly, determining group purchase information, including determining purchased products, determining suppliers and supply amount.

Determining group purchase information: the method for determining the purchased products can directly adopt the products which are subjected to platform query, browsing and adding in a shopping cart or are purchased by placing an order and have the highest frequency as group purchase products within a period of time. Thereby determining the supply amounts provided by the n suppliers and the group buying party.

Or by the following method:

the method comprises the following steps: the times of products which are inquired, browsed, added into a shopping cart and purchased after ordering by the platform within a period of time (the period of time is temporarily specified to be 15 days and can be adjusted according to later use and is called as a time period hereinafter) are obtained.

Step two: the matrix T is calculated.

T＝[t₁,t₂,t₃,…,t_i,…]

Wherein t is_iAnd (3) representing the specifically calculated t value of the product i, wherein the calculation formula of t is as follows:

t＝t_q+t_g+t_s-t_b

wherein, t_qRepresenting number of platform queries, t_gIndicates the number of times of browsing of the platform, t_sIndicating the number of times the platform has joined the shopping cart, t_bIndicating the number of purchases.

Step three: calculating the sales volume of the product in the time period of the last year and checking the sales peak of the product. I.e., products whose sales have increased significantly over this period of time. The calculation method comprises the following steps: the time of the start of the calculation is taken as the start of the time period, thereby determining the time within the time period. The other time periods are determined forwards and backwards by the time period, and whether the sales condition of the product is at the peak position of the bulge or not is checked. If so, the current product is the peak sales product in the period of time.

Step four: and (5) confirming the product. And sorting the values of the matrix T from large to small. The product i which has a larger value t and is sold at the peak is selected as the group purchase product of the time. And when products are confirmed, whether the products are peak sale products is searched downwards according to the sequence of the products in the T by taking the sorted matrix T as a reference until the peak sale products are found. And if the peak value sale product is not found finally, taking the product with the maximum T value in the matrix T as the final group purchase product.

Step five: the product supplier is confirmed. The corresponding inventory of the supplier of the product is confirmed on the platform. The supply quantity provided by the n suppliers and the group buying party is confirmed.

The set of suppliers is noted as:

A＝[A₁，A₂,A₃,…,A_i,…，A_n]

the set of supply quantities corresponding to the suppliers is recorded as:

a＝[a₁,a₂,a₃,…,a_i,…,a_n]

and secondly, determining the buyer participating in the purchasing and the purchasing amount.

The method comprises the following steps: and starting group buying and grouping, and participating in and determining the purchasing amount by a buyer.

Step two: and confirming the number of the purchasers and the corresponding purchase amount of each purchaser, and reminding the purchasers of the current residual supply amount and the residual grouping time in real time (the time can be adjusted according to the products participating in grouping and the number of the products).

Step three: and confirming whether the grouping is successful. And if the total purchasing quantity of the buyer is greater than or equal to the minimum clustering purchasing quantity (the minimum clustering purchasing quantity needs to be set in advance when the clustering is initiated, and the minimum clustering purchasing quantity is less than or equal to the total supply quantity), successfully clustering and finishing. If the total purchase quantity is less than the minimum group purchase quantity in the specified time, the grouping can not be achieved.

Step four: confirming the grouped buyers and the corresponding purchase amounts.

The set of buyers is recorded as:

B＝[B₁,B₂，B₃,…,B_j,…,B_m]

the corresponding purchase amount set of the buyer is recorded as:

b＝[b₁,b₂,b₃,…,b_j,…,b_m]

and thirdly, determining an optimal delivery path, namely confirming the supply and acquisition corresponding relation between the buyer and the supplier and the corresponding supply amount between the supplier and the buyer.

Since the supplier and supply quantity are already determined, i.e. the purchase price is fixed. But the buyer object and the corresponding supply quantity delivered by the supplier are changed, in order to reduce the transportation cost, a corresponding transportation purchasing model is established, so that the smaller transportation cost is ensured, and meanwhile, in most cases, the transportation speed can also be improved to a certain extent because the transportation cost and the transportation time are in a negative correlation trend. The supply scheme is determined on the basis of reducing the transportation cost, namely the optimal delivery path between the supplier and the buyer and the supply quantity between different suppliers corresponding to the supplier.

The transportation cost may be defined as:

wherein W (A, B) represents the total transportation cost of the supplier to the supplier, c_ijIndicates supplier A_iTransporting to buyer B_jTransporting unit price of f_ijIndicates the supplier a_iTransporting to buyer B_jThe supply amount of (c).

Constraint conditions are as follows:

wherein f is_ijThe direction and the quantity of purchase are described, 1- (1) the direction of element movement in the characteristic distribution is described, the product can be supplied to B only from A and cannot be reversed; 1- (2) description of_iThe total number of supplies must not exceed a_iA total supply amount; 1- (3), description b_jTotal number of purchases must not exceed b_jTotal purchase amount of (c).

An objective function:

referring to fig. 2, a method of determining an optimal shipping path, comprising:

determining an initial allocation and transportation method by a Voger method;

solving the test number by adopting a potential method;

judging whether all the check numbers are greater than or equal to 0; if yes, obtaining an optimal scheme; if not, finding out the minimum negative check number, and obtaining a new allocation and transportation scheme by using a closed loop adjustment method. The specific calculation process is as follows:

1. giving an initial feeding scheme. -initial feasible solution: that is, a specific digital value of (m + n-1) is given on the acquisition balance matrix having (m × n) spaces, i.e., n rows and m columns.

The method comprises the following steps: a location is selected. The penalty number (the penalty number is the difference between the minimum freight and the next minimum freight in each column or each row, that is, the penalty number is the next minimum freight-the minimum freight) is determined for each row and each column in the transportation unit price matrix C (transportation unit price matrix of n rows and m columns). And selecting the corresponding row or column where the maximum penalty number is located, and selecting the minimum freight on the corresponding row or column, wherein the corresponding position is the position of the next step. And if two or more rows and columns with the maximum penalty number and the same penalty number exist, selecting the row or column corresponding to the minimum freight in the rows and columns as the row or column of the operation, wherein the position of the minimum freight is the position of the next step.

Step two: determining a fill-in value f_ijAnd represents the number of supplies from the supplier to the buyer. At the corresponding position (n rows and m columns of the mining balance matrix) obtained in the previous step in the mining balance matrix, filling the position of the matrix with the row or column where the position is located according to the Vogel method (also called Vogel method, namely, the corresponding position of the minimum element in the row or column corresponding to the maximum penalty number), reaching the upper limit value, namely, the lower value of the remaining values of the row or column (namely, the upper limit of at least one remaining value of the row or column can be reached), and updating the purchase amount or supply amount (when the corresponding row or column reaches the upper limit of the remaining values, updating the remaining amount or supply amount thereofThe balance).

Step three: the supply or purchase amount is scratched out of the shipping unit price matrix, and the corresponding row or column that has reached the upper limit, i.e., the row or column is no longer given supply or purchase (where the row corresponds to the supply case and the column corresponds to the purchase case).

Example 1: assume that there is a supplier A₁，A₂，A₃The supply amount is a ═ a₁，a₂，a₃]＝[7，4，9](ii) a Presence buyer B₁，B₂，B₃，B₄The procurement amount is b ═ b₁，b₂，b₃，b₄]＝[3，6，5，6]. The transportation unit price table (transportation unit matrix is 3 rows and 4 columns) corresponds to:

table 1 unit price table for transportation

	B₁	B₂	B₃	B₄
					A₁	3	11	3	10
A₂	1	9	2	8
					A₃	7	4	10	5

The steps for giving the initial feeding scheme are:

(1) calculating penalty number

TABLE 2 penalty calculation Table

The row with the largest penalty number corresponds to: b is₂And (4) columns.

(2) The positions to be filled in the mining balance table (the mining balance matrix is a matrix with 3 rows and 4 columns), B₂The position corresponding to the minimum element in the column correspondence is (A)₃，B₂)。

TABLE 3 balance table for mining

f_ij	B₁	B₂	B₃	B₄	Amount of supply
						A₁		7
A₂					4
						A₃	6(1)	9
Purchase amount	3	6	5	6

Wherein A is₃Is 9, B₂If the purchase amount of (A) is 6, then (A)₃，B₂) Fill in 6, i.e. f₃₂＝6。

(3) Updating penalty table, buyer B₂The purchase amount of (B) is completed, and the section B is drawn₂And (4) columns.

TABLE 4 penalty calculation Table

The row with the largest penalty number corresponds to: b is₄And (4) columns.

(4) The position to be filled in the mining balance table, B₄The position corresponding to the minimum element in the column correspondence is (A)₃，B₄)。

TABLE 5 balance table for mining

f_ij	B₁	B₂	B₃	B₄	Amount of supply
						A₁			7
A₂					4
						A₃	6(1)	3(2)	9
Purchase amount	3	6	5	6	20

Wherein A is₃With a residual supply of 9-6-3, B₄If the purchase amount of (A) is 6, then (A)₃，B₄) Filling in 3, i.e. f₃₄＝3。

(5) Update penalty table, supplier A₃The supply amount of (A) is completed, and (A) is cut off₃And (6) rows.

TABLE 6 penalty calculation Table

The row with the largest penalty number corresponds to: b is₁Columns and B₄Column in which B₁The minimum element per unit price of the column is smaller, so this choice is B₁And (4) columns.

(6) The position to be filled in the mining balance table, B₁The position corresponding to the minimum element in the column correspondence is (A)₂，B₁)。

TABLE 7 balance table for mining

f_ij	B₁	B₂	B₃	B₄	Amount of supply
						A₁			7
A₂	3(3)				4
						A₃	6(1)	3(2)	9
Purchase amount	3	6	5	6

Wherein A is₂Is supplied in an amount of 4, B₁If the purchase amount of (A) is 3, then₂，B₁) Filling in 3, i.e. f₂₁＝3。

(7) Update penalty table, supplier B₁The purchase amount of (B) is completed, and the section B is drawn₁And (4) columns.

TABLE 8 penalty calculation Table

The row with the largest penalty number corresponds to: a. the₁And (6) rows.

(8) The position to be filled in the mining balance table, A₁The position corresponding to the minimum element in the row correspondence is (A)₁，B₃)。

TABLE 9 balance table for mining

f_ij	B₁	B₂	B₃	B₄	Amount of supply
						A₁		5(4)		7
A₂	3(3)				4
						A₃	6(1)		3(2)	9
Purchase amount	3	6	5	6

Wherein A is₁Is supplied in an amount of 7, B₃If the purchase amount of (A) is 5, then₁，B₃) Filling in 5, i.e. f₁₃＝5。

(9) Update penalty table, supplier B₃The purchase amount of (B) is completed, and the section B is drawn₃And (4) columns.

TABLE 10 penalty calculation Table

The row with the largest penalty number corresponds to: a. the₁And (6) rows.

(10) The position to be filled in the mining balance table, A₁The position corresponding to the minimum element in the row correspondence is (A)₁，B₄)。

TABLE 11 balance table for mining

f_ij	B₁	B₂	B₃	B₄	Amount of supply
						A₁		5(4)	2(5)	7
A₂	3(3)				4
						A₃	6(1)		3(2)	9
Purchase amount	3	6	5	6

Wherein A is₁With a residual supply of 7-5-2, B₄If the remaining purchase amount is 6-3 ═ 3, (A) is₁，B₄) Filling in 2, i.e. f₁₄＝2。

(11) Update penalty table, supplier A₁The supply amount of (A) is completed, and (A) is cut off₁And (6) rows.

TABLE 12 penalty calculation Table

The row with the largest penalty number corresponds to: a. the₂Rows and B₄Columns, whose corresponding minimum elements are in the same position, are selected from A₂Line or B₄All columns, where A is selected₂And (6) rows.

(12) At the locations in the mining balance table that need to be filled,A₂the position corresponding to the minimum element in the row correspondence is (A)₂，B₄)。

Table 13 balance table for mining

f_ij	B₁	B₂	B₃	B₄	Amount of supply
						A₁		5(4)	2(5)	7
A₂	3(3)			1(6)	4
						A₃	6(1)		3(2)	9
Purchase amount	3	6	5	6

Wherein A is₂Is 4-3 ═ 1, B₄The remaining purchase amount of (A) is 6-3-2 ═ 1₂，B₄) Filling in 1, i.e. f₂₄＝1。

(13) Update penalty table, supplier A₂The supply amount of (A) is completed, and the buyer B₄The purchase amount of (A) is completed, and the line A is drawn₂Rows and B₄And (4) columns.

Table 14 penalty calculation table

And (5) scratching all elements in the transportation unit price table, and ending the circulation to obtain an initial mining supply scheme.

TABLE 15 initial feed recovery scheme

f_ij	B₁	B₂	B₃	B₄	Amount of supply
						A₁		5	2	7
A₂	3			1	4
						A₃	6		3	9
Purchase amount	3	6	5	6

2. And (6) judging optimality.

The method comprises the following steps: determining a group of potential of each row and column according to the condition that the check number of the base variable is 0: c. C_ij＝u_i+v_j. Wherein c is_ijIs represented by (A)_i，B_j) Unit price of transport of u_iIndicating the row bit potential, v, of row i_jColumn potentials (all vs v) of j-th column₁Setting the initial value to be 1), and calculating corresponding row potential and column potential. (base variable, which is the position in the initial feed solution where there is a value. non-base variable, which is the position in the initial solution where there is no corresponding value)

Step two: the trial number of any non-base variable is calculated (the trial number of the base variable is 0). The check number calculation formula is as follows: sigma_ij＝c_ij-(u_i+v_j)，σ_ijIndicating the corresponding check number at the ith row and j column position.

Step three: if the check number matrix (n rows and m columns of the check number matrix) satisfies sigma_ijIf the rate is more than or equal to 0, the scheme is the optimal mining scheme; and if not, entering a scheme adjusting stage to adjust the scheme.

Example 2: the assumed sampling scheme is:

TABLE 16 feed and recovery schemes

f_ij	B₁	B₂	B₃	B₄
					A₁		5	2
A₂	3			1
					A₃	6		3

TABLE 17 unit price for transportation

(1) Calculating row and column potentials

From c₂₁＝u₂+v₁＝1，c₂₄＝u₂+v₄＝8，c₃₂＝u₃+v₂＝4，c₁₃＝u₁+v₃＝3，c₁₄＝u₁+v₄＝10，c₃₄＝u₃+v₄＝5。

By v₁When 1, then v₂＝7，v₃＝1，v₄＝8，u₁＝2，u₂＝0，u₃＝-3。

(2) The check number for the non-base variable was calculated as shown in table 18.

TABLE 18 test numbers

σ_ij	B₁	B₂	B₃	B₄	u_i
						A₁	0	2	0	0	2
A₂	0	2	1	0	0
						A₃	9	0	12	0	-3
v_j	1	7	1	8

(3) The inspection numbers all satisfy the sigma_ijAnd the feeding scheme is more than or equal to 0, so the feeding scheme is the optimal feeding scheme.

Example 3: the assumed sampling scheme is:

TABLE 19 feed and recovery schemes

f_ij	B₁	B₂	B₃	B₄
					A₁		4	3
A₂	3		1
					A₃	6		3

TABLE 20 transportation unit price table

c_ij	B₁	B₂	B₃	B₄
					A₁		3	10
A₂	1		2
					A₃	4		5

(1) The row potential, column position and the number of tests are calculated.

Table 21 column potential and test number

σ_ij	B₁	B₂	B₃	B₄	u_i
						A₁	1	2	0	0	1
A₂	0	1	0	-1	0
						A₃	10	0	12	0	-4
v_j	1	8	2	9

(2) Test number sigma₂₄Does not satisfy the condition σ_ijAnd if the current sampling rate is more than or equal to 0, the sampling scheme is not the optimal sampling scheme. And entering a scheme adjusting stage for adjusting the mining scheme.

3. Feed and production scheme adjustment

If the check number matrix has a value less than 0, then the step is entered for scheme adjustment.

The method comprises the following steps: the carry over variable (carry over variable, position corresponding to minimum negative number of tests) is determined. The smallest number of tests in the non-base variables is determined. That is, the non-base variable corresponding to the position where the trial number is the smallest is taken as the base (the non-base variable becomes the base variable). When the plurality of non-base variables are less than 0 and equal, then any one of the non-base variables may be taken as the base variable.

Step two: a closed loop of the adjustment is determined. Starting from the position of the minimum negative test number, advancing along the horizontal direction or the vertical direction, when encountering the position of a basic variable, rotating by 90 degrees and continuing to advance until returning to the position of the minimum negative test number (starting from a new direction when exceeding the position of the matrix in the horizontal direction or the vertical direction), and forming a closed broken line path consisting of a horizontal line segment and a vertical line segment, namely a closed loop. And taking the minimum value of the element on the closed loop where the minimum negative check number is positioned as the minimum adjustment amount (so as to ensure that each component is still a positive value after adjustment, namely the scheme is still a feasible solution).

Step three: and (5) adjusting the scheme. The adjustment amount is the minimum element (the value of the minimum element on the closed loop), and on the closed loop, the adjustment amount is added to the odd point, and the adjustment amount is subtracted from the even point, so that the adjusted scheme is obtained. The position of the minimum negative test number is the first odd vertex (odd point for short), the next vertex is the even vertex (even point for short), and the odd point and the even point appear alternately by analogy downwards.

Step four: and judging whether the supply and mining scheme is the optimal supply and mining scheme. And entering optimality judgment until the current scheme is the optimal supply and mining scheme, finishing scheme adjustment and outputting the optimal supply and mining scheme.

Example 4: the example of example 3 is followed. The case of the scheme and the check number is (the numerical value in the bracket is the value of the corresponding position in the corresponding balance matrix for sampling, and the check number matrix is a matrix with 3 rows and 4 columns):

table 22 check number table

σ_ij(f_ij)	B₁	B₂	B₃	B₄
					A₁	1	2	0(4)	0(3)
A₂	0(3)	1	0(1)	-1
					A₃	10	0(6)	12	0(3)

(1) And determining a carry-in variable. The minimum negative detection number corresponds to the position (A)₂，B₄) Then the position is the carry variable.

(2) The closed loop of the adjustment is determined (the position of the black frame is the closed loop).

TABLE 23 closed-loop determination table

(3) And (5) adjusting the scheme. The adjustment amount is that the minimum element value is 1, and the specific adjustment is as follows:

table 24 protocol adjustment table

The adjusting scheme is as follows:

table 25 adjusted project correspondence table

f_ij	B₁	B₂	B₃	B₄
					A₁		5	2
A₂	3			1
					A₃	6		3

(4) And (6) judging optimality. The adjusted feeding scheme is the same as the feeding scheme of example 2, and is an optimal scheme.

4. Confirming optimal delivery path and supply amount

And determining a delivery path, namely the corresponding relation between a supplier and a buyer and the corresponding supply quantity thereof according to the determined optimal supply and collection scheme by optimality judgment. And the system delivers the goods according to the optimal supply and extraction scheme. The minimum transportation cost at this time is calculated as:

example 5: assuming the plan is the optimal supply plan shown in table 25, the transportation unit price is shown in table 1.

The optimal delivery path in the optimal supply and sampling scheme includes the corresponding relationship between the suppliers and the sampling suppliers and the supply amount between the suppliers and the corresponding suppliers.

This optimal feed scheme (the optimal feed scheme shown in table 25):

f_ij	B₁	B₂	B₃	B₄
					A₁		5	2
A₂	3			1
					A₃	6		3

the corresponding delivery route and the corresponding supply amount are:

supplier A₁Is a buyer B₃Supplying with supply quantity of 5; for buyer B₄Supply with a supply quantity of 2.

Supplier A₂Is a buyer B₁Supplying, the supply quantity is 3; for buyer B₄Supply with a supply quantity of 1.

Supplier A₃Is a buyer B₂Supplying materials with the supply quantity of 6; for buyer B₄Supply, supply quantity is 3.

It should be understood that the specific order or hierarchy of steps in the processes disclosed is an example of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not intended to be limited to the specific order or hierarchy presented.

In the foregoing detailed description, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the subject matter require more features than are expressly recited in each claim. Rather, as the following claims reflect, invention lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. Of course, the processor and the storage medium may reside as discrete components in a user terminal.

For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in memory units and executed by processors. The memory unit may be implemented within the processor or external to the processor, in which case it can be communicatively coupled to the processor via various means as is known in the art.

What has been described above includes examples of one or more embodiments. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the aforementioned embodiments, but one of ordinary skill in the art may recognize that many further combinations and permutations of various embodiments are possible. Accordingly, the embodiments described herein are intended to embrace all such alterations, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent that the term "includes" is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term "comprising" as "comprising" is interpreted when employed as a transitional word in a claim. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or".

Claims

1. A form splitting and supplying method for group purchase combination forms is characterized by comprising the following steps:

(2) determining a buyer participating in purchasing and a purchasing amount;

2. The group buying party splitting and supplying method as claimed in claim 1, wherein said determining of the group buying information in step (1): the method for determining the purchased products adopts the products which are ranked at the top in the frequency of inquiring, browsing and adding in a shopping cart or placing a purchase order on a platform within a period of time as the group purchase products, thereby determining n suppliers and the supply quantity provided by the group purchase group.

3. The group buying and assembling splitting supply method as claimed in claim 1, wherein said determining group buying information in step (1) comprises the specific steps of:

step (1.2): calculating a matrix T: t ═ T₁，t₂，t₃，…，t_i，…]

4. The splitting and supplying method of group purchase order sharing as claimed in claim 1, wherein the step (2) of determining the buyer and the amount of the purchase to be participated in the purchase comprises the following specific steps:

5. The splitting and supplying method of group purchase orders as claimed in claim 1, wherein the optimal delivery route is determined in the step (3), and the method comprises:

Record the set of buyers as: b ═ B₁，B₂，B₃，…，B_j，…，B_m]

The corresponding purchase amount set of the buyer is recorded as: b ═ b₁，b₂，b₃，…，b_j，…，b_m]

The transportation cost is defined as:

constraint conditions are as follows:

an objective function:

6. the splitting and supplying method of group purchase orders as claimed in claim 1, wherein the method of determining the optimal delivery route in the step (3) comprises:

determining an initial allocation and transportation method by a Voger method;

solving the test number by adopting a potential method;

7. The group purchase order splitting and supplying method of claim 6, wherein the determining of the optimal delivery route in the step (3) specifically comprises:

8. The group purchase order splitting and supplying method of claim 6, wherein the determining of the optimal delivery route in the step (3) specifically comprises: step (3.2) optimality judgment:

the method comprises the following steps: determining a group of potential of each row and column according to the condition that the check number of the base variable is 0: c. C_ij＝u_i+v_j(ii) a Wherein c is_ijIs represented by (A)_i，B_j) Unit price of transport of u_iIndicating the row bit potential, v, of row i_jColumn potentials, each for v, representing the j-th column₁Setting an initial value as 1, and calculating corresponding row potential and column potential; wherein the base variable is a position with a value in the initial feeding scheme; non-base variables, i.e., positions in the initial solution where there is no corresponding value;

step two:calculating the check number of any non-base variable, wherein the check number of the base variable is 0; the check number calculation formula is as follows: sigma_ij＝c_ij-(u_i+v_j)，σ_ijRepresenting the corresponding check number at the ith row and j column position;

9. The group purchase order splitting and supplying method of claim 6, wherein the determining of the optimal delivery route in the step (3) specifically comprises: step (3.3) adjustment of the mining scheme: if the value less than 0 exists in the check number matrix, entering the step to carry out scheme adjustment;

10. The group purchase order splitting and supplying method of claim 6, wherein the determining of the optimal delivery route in the step (3) specifically comprises: step (3.4) confirming the optimal delivery path and supply amount; determining a delivery path, namely the corresponding relation between a supplier and a buyer and the corresponding supply quantity thereof according to the determined optimal supply and collection scheme by optimality judgment, and delivering according to the optimal supply and collection scheme by the system; the minimum transportation cost at this time is calculated as: