Order generation method based on bidding component rule

Abstract

The invention discloses an order generation method based on a bidding component rule, and the method comprises the steps: determining an allocation weight for each supplier according to the location of the supplier and the type of the supplier; adjusting the distribution weight according to a supplier assessment result; obtaining the order distribution quantity of each supplier according to the adjusted distribution weight; wherein the places where the suppliers are located include the places inside and outside the province where the purchasers are located, the supplier types include the production type and the trade type, and the assessment results of the suppliers are the assessment levels of the last assessment period. According to the invention, the weight is dynamically allocated and the order quantity is adjusted by integrating the multi-dimensional factors of the location, the type and the assessment level of the supplier, so that the rights and interests of the provincial production-type supplier are preferentially guaranteed, the logistics cost is reduced, and the quality stability is improved. Meanwhile, historical performance of suppliers is considered, the suppliers are stimulated to improve services so as to obtain more orders, and double improvement of supply chain efficiency and reliability is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of supplier management, and particularly relates to an order generation method based on the rules of bid division and quantity allocation. Background Art

[0002] In modern business operations, supply chain management is one of the key links to ensure the smooth operation of enterprises. As an important part of supply chain management, order allocation directly affects the cost control, efficiency improvement of enterprises, and the cooperation relationship with suppliers. With the intensification of market competition and the diversification of customer demands, how to optimize the order allocation process to improve the overall efficiency and competitiveness of the supply chain has become an important issue faced by enterprises.

[0003] Traditional order allocation methods usually make decisions based on single or simple rules, such as choosing the supplier with the lowest price or determining order allocation according to the historical performance of the supplier. For example, in some practices, purchasers may tend to choose those suppliers with the lowest quotes or make selections based on the satisfaction scores in past cooperation. However, the simple price or historical performance-oriented order allocation methods fail to effectively motivate suppliers to improve their service quality and innovation capabilities, which is not conducive to building long-term stable and mutually beneficial cooperation relationships.

[0004] In addition, these methods often ignore the comprehensive consideration of multi-dimensional factors of suppliers and overlook other important influencing factors, resulting in unreasonable order allocation plans and being unable to fully reflect the true capabilities and potentials of suppliers. Moreover, some existing order allocation methods lack flexibility and intelligence and are difficult to cope with complex market changes and diverse business requirements. For example, although some methods can consider the historical performance of suppliers, they fail to fully consider the differences in logistics costs brought about by the locations of suppliers or do not distinguish the differences in the product and service quality that different types of suppliers can provide. Due to the failure to fully consider the geographical advantages and type characteristics of suppliers, it may lead to an increase in logistics costs and an extension of delivery times, thus affecting the operation efficiency of the entire supply chain.

[0005] Therefore, it is particularly important to design an order generation method based on multi-dimensional bid division and quantity allocation rules to improve the fairness and reasonableness of order allocation, optimize supply chain management, and enhance the competitiveness of suppliers. Summary of the Invention

[0006] The present invention provides an order generation method based on the rules of bid division and quantity allocation to solve the problems of unreasonable order allocation plans caused by traditional methods relying only on single indicators, low supply chain efficiency caused by the failure to fully consider the geographical advantages and type characteristics of suppliers, and the problem that simple price or historical performance-oriented order allocation methods fail to effectively motivate suppliers to improve their service quality and innovation capabilities.

[0007] The technical solution adopted by the present invention is as follows:

[0008] An order generation method based on the rule of dividing labels and components, comprising:

[0009] Determine the allocation weight for each supplier according to the location of the supplier and the type of the supplier;

[0010] Adjust the allocation weight according to the supplier assessment result;

[0011] Obtain the order allocation quantity of each supplier according to the adjusted allocation weight;

[0012] Wherein, the location of the supplier includes within and outside the province where the purchaser is located, the type of the supplier includes production type and trading type, and the supplier assessment result is the assessment grade of the previous assessment period.

[0013] The order generation method based on the rule of dividing labels and components in the present invention further includes the following additional technical features:

[0014] The allocation weight of suppliers within the province is higher than that of suppliers outside the province,

[0015] The allocation weight of production-type suppliers is higher than that of trading-type suppliers,

[0016] The allocation weight of suppliers with a high assessment grade is higher than that of suppliers with a low assessment grade.

[0017] Determine the allocation weight for each supplier according to the location of the supplier and the type of the supplier, specifically:

[0018] Set the first allocation weight coefficient according to suppliers within the province, and set the second allocation weight coefficient according to production-type suppliers,

[0019] Obtain the compensation allocation weight of suppliers within the province according to the first allocation weight coefficient, obtain the compensation allocation weight of production-type suppliers according to the second allocation weight coefficient, and obtain the allocation weight of the supplier according to the compensation allocation weight of suppliers within the province and the compensation allocation weight of production-type suppliers.

[0020] Obtain the allocation weight of the supplier according to the first allocation weight coefficient and the second allocation weight coefficient, specifically:

[0021] If all the suppliers are suppliers within the province,

[0022] When there are production-type suppliers among the suppliers, obtain the compensation allocation weight of production-type suppliers according to the second allocation weight coefficient, and the remaining weight to be allocated is evenly divided among all suppliers;

[0023] When all the suppliers are trading suppliers, the undistributed weight is evenly divided among all the suppliers.

[0024] Obtaining the allocated weight of the supplier according to the first allocation weight coefficient and the second allocation weight coefficient further includes:

[0025] If the suppliers include both in-province suppliers and out-of-province suppliers,

[0026] When all the suppliers are trading suppliers, obtain the compensation allocation weight of in-province suppliers according to the first allocation weight coefficient, and evenly divide the remaining undistributed weight among all the suppliers;

[0027] When there are manufacturing suppliers among the suppliers, obtain the compensation allocation weight of in-province suppliers according to the first allocation weight coefficient, combine the second allocation weight coefficient to obtain the compensation allocation weight of in-province manufacturing suppliers, evenly divide the unallocated weight in the compensation allocation weight of in-province suppliers among in-province suppliers, and evenly divide the remaining unallocated weight among all the suppliers.

[0028] Obtaining the allocated weight of the supplier according to the first allocation weight coefficient and the second allocation weight coefficient further includes:

[0029] If all the suppliers are out-of-province suppliers, evenly divide the undistributed weight among all the suppliers.

[0030] Adjust the allocated weight according to the supplier assessment result, specifically:

[0031] The assessment levels include level one, level two, and level three.

[0032] According to the supplier assessment result, set the compensation allocation weight coefficient to obtain the compensation allocation weight, and evenly divide the compensation allocation weight among level-one suppliers; or,

[0033] According to the assessment level difference from level-one suppliers, set the first compensation allocation weight coefficient and the second compensation allocation weight coefficient for level-two suppliers and level-three suppliers respectively to obtain the first compensation allocation weight and the second compensation allocation weight.

[0034] According to the allocated weight of level-two suppliers combined with the first compensation allocation weight, obtain the adjustment weight of level-two suppliers to level-one suppliers, and according to the allocated weight of level-three suppliers combined with the second compensation allocation weight, obtain the adjustment weight of level-three suppliers to level-one suppliers.

[0035] The present invention also provides an order generation system based on the sub-bidding and sub-quantity rules, including:

[0036] A data acquisition module for acquiring data on the location of suppliers, supplier types, and supplier assessment results;

[0037] A weight allocation module, configured to determine an allocation weight for each supplier according to the location of the supplier and the type of the supplier, and adjust the allocation weight according to the supplier assessment result;

[0038] An order allocation module, configured to obtain the order allocation quantity of each supplier according to the adjusted allocation weight.

[0039] The present invention further provides a storage medium,

[0040] wherein a computer program is stored on the storage medium, and when the computer program is executed, the steps of any one of the order generation methods based on the sub - bid component rule are implemented.

[0041] The present invention further provides a processing device, including:

[0042] A memory, configured to store a computer program;

[0043] A processor, configured to implement the steps of the order generation method based on the sub - bid component rule according to any one of claims 1 to 7 when executing the computer program.

[0044] Due to the adoption of the above - mentioned technical solution, the beneficial effects obtained by the present invention are as follows:

[0045] 1. In the present invention, an order generation method based on the sub - bid component rule includes: determining an allocation weight for each supplier according to the location of the supplier and the type of the supplier; adjusting the allocation weight according to the supplier assessment result; obtaining the order allocation quantity of each supplier according to the adjusted allocation weight; wherein, the location of the supplier includes within and outside the province where the purchaser is located, the type of the supplier includes production - type and trading - type, and the supplier assessment result is the assessment grade of the previous assessment period.

[0046] Through a multi - dimensional comprehensive scoring mechanism, the present invention ensures the fairness and rationality of order allocation. Traditional order allocation methods usually rely on single or simple rules (such as the lowest price or the historical performance of the supplier), which may lead to unreasonable results. The present invention introduces multiple factors such as the location of the supplier, the type of the supplier, and the assessment result, and assigns weights to each factor, thereby making the final order allocation more scientific and reasonable.

[0047] In addition, preferring in-province suppliers can effectively reduce logistics costs and time, and improve the overall efficiency of the supply chain. Production suppliers can better ensure product quality and supply stability compared to trading suppliers. Therefore, higher weights are given in order allocation, which helps enhance the stability and reliability of the supply chain. By considering the assessment results of suppliers in the previous quarter, preferentially selecting suppliers with excellent assessment results further improves the overall operation efficiency and service quality of the supply chain.

[0048] At the same time, linking the assessment results with order allocation encourages suppliers to continuously improve their service quality and technical level. This mechanism not only promotes healthy competition among suppliers but also encourages them to continuously improve to obtain more order opportunities, thereby enhancing the overall market competitiveness. By dynamically adjusting the weight coefficients, the importance of different factors can be flexibly adjusted according to actual business needs, ensuring that suppliers can remain competitive in the changing market environment.

[0049] The weight allocation mechanism in the present invention has a high degree of flexibility and can be adjusted according to the specific needs of the enterprise and changes in the market environment. For example, when market demand changes or new business scenarios emerge, the enterprise can quickly respond and optimize the order allocation plan by adjusting the weight coefficients. The systematic method design supports the processing of multiple types of suppliers. Whether they are in-province or out-of-province suppliers, production or trading suppliers, reasonable order allocations can be obtained through this method, greatly improving the applicability and flexibility of the system.

[0050] Moreover, the present invention realizes the intelligentization of the order allocation process, reduces manual intervention, and improves decision-making efficiency. The system automatically collects data, calculates weights, generates scores, and completes order allocation, which not only saves labor costs but also avoids human errors, ensuring the consistency and accuracy of decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings described herein are used to provide a further understanding of the present invention and form a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0052] Figure 1 It is a schematic flow chart of the order generation method based on the sub-bidding and sub-quantity rules under an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0053] In order to more clearly illustrate the overall concept of the present invention, the following will be described in detail by way of examples in combination with the drawings of the specification.

[0054] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present invention is not limited by the specific embodiments disclosed below.

[0055] As Figure 1 shown, an order generation method based on sub - standard component rules includes:

[0056] S100: Determine the allocation weight for each supplier according to the location of the supplier and the type of the supplier.

[0057] The core objective of this step is to allocate initial weights to suppliers through multi - dimensional rules (location of the supplier, type of the supplier) to ensure the rationality and fairness of subsequent order allocation. It directly solves the problem of allocation deviation caused by a single indicator (such as price or historical performance) in traditional order allocation. By comprehensively considering geographical location and supplier type, it optimizes the supply chain efficiency and cost control.

[0058] In this step, according to the location of the supplier, it is distinguished whether the supplier is within (within the province) or outside (outside the province) the province where the purchaser is located. Suppliers within the province usually have lower logistics costs and faster response speeds. Prioritizing order allocation to them can significantly reduce transportation time and warehousing costs.

[0059] According to the type of the supplier, the supplier is distinguished as a production - type or trading - type. Production - type suppliers have their own production lines and directly produce products (such as electronic component manufacturers). Trading - type suppliers provide products through procurement, distribution, etc. (such as electronic product distributors). Since production - type suppliers directly control the production process, the product quality and supply stability are higher. Prioritizing order allocation to them can improve the reliability of the supply chain.

[0060] Suppose the purchaser is located in Guangdong Province, and the existing supplier information is as follows:

[0061] Supplier A: Production - type within Guangdong Province; Supplier B: Trading - type within Guangdong Province; Supplier C: Production - type outside Hunan Province; Supplier D: Trading - type outside Hunan Province.

[0062] According to the preset rules, weights are allocated to "location of the supplier" and "type of the supplier" to form the initial allocation weights. Supplier A (production - type within the province) obtains the highest order volume because it has both geographical and type advantages, which can ensure fast delivery and stable quality. Supplier D (trading - type outside the province) is allocated the least number of orders due to its dual disadvantages, avoiding affecting the overall supply chain efficiency due to logistics delays or quality risks.

[0063] Generally speaking, in this step, through multi-dimensional weight allocation, by quantifying geographical and type factors, the subjectivity of traditional methods is avoided. Prioritizing in-province suppliers reduces logistics costs, and prioritizing production-type suppliers reduces quality risks. Comprehensively determining the weight mechanism ensures that suppliers with obvious comprehensive advantages obtain higher priorities, motivating suppliers to improve their own conditions.

[0064] S200: Adjust the allocated weights according to the supplier assessment results.

[0065] The core objective of this step is to dynamically adjust the determined allocated weights by introducing the supplier assessment results, so as to further optimize the fairness and incentive of order allocation. Traditional methods often lack quantitative consideration of the historical performance of suppliers, resulting in insufficient motivation for high-quality suppliers. In this step, by combining the assessment results with weight adjustment, "matching high performance with high rewards" is achieved, thereby improving the overall efficiency of the supply chain and the long-term cooperation willingness of suppliers.

[0066] Set corresponding adjustment rules according to the assessment levels (such as first level, second level, third level) of suppliers in the previous assessment cycle. For example, adjust part of the allocated weights of second-level and third-level suppliers to first-level suppliers. Through differential adjustment coefficients, directly quantify the impact of the historical performance of suppliers on order allocation, ensure that high-performance suppliers obtain more order opportunities, and form a positive incentive.

[0067] Specifically, adjust the allocated weights according to the assessment levels (such as first level, second level, third level) of suppliers in the previous assessment cycle.

[0068] Suppose the initial weights of suppliers have been determined (for example, Supplier A is 0.6, Supplier B is 0.2, Supplier C is 0.1, Supplier D is 0.1), and adjust in combination with the assessment results:

[0069] Supplier A: Assessment level first level; Supplier B: Assessment level second level; Supplier C: Assessment level third level; Supplier D: Assessment level third level.

[0070] Adjust 10% of the allocated weight of Supplier B and 20% of the allocated weights of Supplier C and Supplier D to Supplier A.

[0071] The adjusted allocated weight of Supplier A is 0.66, the adjusted allocated weight of Supplier B is 0.18, the adjusted allocated weight of Supplier C is 0.08, and the adjusted allocated weight of Supplier D is 0.08.

[0072] It is understandable that the supplier assessment result refers to the comprehensive performance evaluation of the supplier in the previous assessment cycle, usually including indicators such as on-time delivery rate, product quality pass rate, service response speed, etc. The assessment level is the level divided according to the assessment result (such as level one, level two, level three), and the higher the level, the better the performance of the supplier. It can also be evaluated as level A, level B, level C, or a comprehensive score can be given. 80 to 100 points is level one, 60 to 80 points is level two, and below 60 points is level three. It only needs to reflect the difference in the assessment levels among suppliers, and the present invention does not limit this.

[0073] In this step, Supplier A (with excellent assessment) obtains a significantly higher order volume due to the assessment result, which motivates it to continuously optimize its service. The order volumes of Suppliers C and D (with assessment needing improvement) decrease, forcing them to improve their performance to avoid being marginalized in the long run. High-performance suppliers undertake more orders, reducing the risk of delivery delays or quality problems caused by low-efficiency suppliers, so as to improve the overall supply chain efficiency.

[0074] S300: Obtain the order allocation quantity of each said supplier according to the adjusted said allocation weight.

[0075] The core objective of this step is to convert the adjusted weight into a specific order allocation quantity, ensuring the accuracy and operability of order allocation. By combining the weight ratio with the total order volume, an accurate mapping from "weight value" to "actual order volume" is achieved, and at the same time, the fairness problem caused by weight decimals or remaining quantity allocation is solved, and finally an executable order allocation plan is formed.

[0076] It is understandable that the sum of the adjusted allocation weights is generally 1. When the sum is not 1, normalization processing needs to be carried out to obtain the normalized weight (with a sum of 1), and combined with the total order volume, the orders are allocated proportionally. Ensure that the order allocation quantity corresponds exactly to the weight, and avoid unfair allocation caused by weight calculation deviation.

[0077] It should be noted that since the order allocation quantity may be a decimal (such as 0.45×1000 = 450, but if the total order volume is odd or the weight is a decimal), integerization processing needs to be carried out:

[0078] Rounding first: Convert the decimal part to an integer according to the conventional rule (such as rounding up when it is 0.5 or more, and rounding down when it is less than 0.5); or,

[0079] Remaining quantity allocation rule: If there is a difference between the sum after rounding and the total order volume, then allocate the remaining quantity to the supplier with the highest adjusted weight (or allocate it in order according to the weight ranking).

[0080] Specifically, assume that the total order volume is 1000 pieces, and the normalized weights of the suppliers are as follows:

[0081] Supplier A: 0.45, getting an initial allocation of 450 pieces (with no remainder); Supplier B: 0.25, getting an initial allocation of 250 pieces; Supplier C: 0.20, getting an initial allocation of 200 pieces; Supplier D: 0.10, getting an initial allocation of 100 pieces;

[0082] The total is 1000 pieces, and no surplus allocation is required.

[0083] Suppose the total order quantity is 1001 pieces:

[0084] Supplier A: 0.45 × 1001 ≈ 450.45, getting an initial allocation of 450 pieces; Supplier B: 0.25 × 1001 ≈ 250.25, getting an initial allocation of 250 pieces; Supplier C: 0.20 × 1001 ≈ 200.2, getting an initial allocation of 200 pieces; Supplier D: 0.10 × 1001 ≈ 100.1, getting an initial allocation of 100 pieces;

[0085] The total allocated quantity = 450 + 250 + 200 + 100 = 1000 pieces, and the surplus of 1 piece is allocated to Supplier A with the highest weight (451 pieces).

[0086] The surplus allocation rule ensures fairness and avoids allocation deviations caused by calculation errors.

[0087] In addition, the present invention also needs to perform capacity constraints and feasibility verification. If the allocated quantity of a certain supplier exceeds its maximum production capacity, it will be allocated according to its production capacity limit, and the remaining orders will be reallocated. If the maximum production capacity of Supplier A is 400 pieces, but the allocated quantity is 450 pieces, then: Supplier A is actually allocated 400 pieces, and the remaining 50 pieces are reallocated to other suppliers according to the weight ratio. This avoids the risk of delivery failure caused by the order quantity exceeding the supplier's capacity and improves the feasibility of the solution.

[0088] Generally speaking, the order allocation quantity calculation and optimization strategy in this step ensure that the allocation result is exactly corresponding to the weight through the direct mapping of the weight ratio and the total order quantity. The surplus allocation rule avoids allocation deviations caused by calculation errors and preferentially allocates to suppliers with high weights. Introducing capacity constraint verification ensures that the order allocation plan can be implemented in actual execution, reduces the delivery risk, and flexibly handles different total order quantities (such as even or odd) and supplier capacity limitations, improving the universality of the solution.

[0089] As a preferred implementation manner under the present invention, the allocation weight of in-province suppliers is higher than that of out-of-province suppliers, the allocation weight of production-type suppliers is higher than that of trading-type suppliers, and the allocation weight of suppliers with a high assessment level is higher than that of suppliers with a low assessment level.

[0090] The core objective of this preferred embodiment is to construct a differentiated weight allocation mechanism by quantifying the geographical advantages, type characteristics, and performance of suppliers, so as to achieve precision and intelligence in order allocation. Specifically,

[0091] Preferential treatment for in-province suppliers: Reduce logistics costs and improve delivery efficiency; Preferential treatment for production-type suppliers: Ensure product quality and supply stability; Preferential treatment for assessment grades: Motivate high-performance suppliers and optimize the long-term cooperation quality of the supply chain.

[0092] Through this strategy, the present invention reduces the enterprise operation cost while significantly enhancing the reliability and competitiveness of the supply chain.

[0093] Specifically, set the superimposed weight priority. If a supplier meets the in-province, production-type, and assessment grade I conditions at the same time, the weights will be superimposed and orders will be preferentially allocated. To maximize the utilization of the comprehensive advantages of suppliers and avoid allocation deviations in a single dimension.

[0094] When the weights of multiple suppliers are the same, allocate in the following order preferentially:

[0095] In-province production-type suppliers (dual advantages of geography + type), in-province trading-type suppliers (only geographical advantages), out-of-province production-type suppliers (only type advantages), out-of-province trading-type suppliers (no advantages). Then adjust the allocated weights through the supplier assessment results. This ensures fairness while preferentially guaranteeing the core efficiency and stability of the supply chain.

[0096] Generally speaking, through this preferred embodiment, the high weight allocation for in-province suppliers significantly reduces logistics costs (such as transportation costs and warehousing costs). The weight advantage of production-type suppliers ensures order quality and reduces delivery problems caused by supplier types. The assessment grade is directly linked to the weight, and high-performance suppliers obtain more orders, forming a virtuous competition environment. Preferential treatment for in-province and production-type suppliers reduces the risk of supply chain interruption caused by geographical location or type defects of suppliers.

[0097] As a preferred embodiment of the present invention, determine the allocated weight for each supplier according to the location of the supplier and the type of the supplier. Specifically:

[0098] Set the first allocated weight coefficient according to in-province suppliers, and set the second allocated weight coefficient according to production-type suppliers.

[0099] Obtain the compensated allocated weight for in-province suppliers according to the first allocated weight coefficient, obtain the compensated allocated weight for production-type suppliers according to the second allocated weight coefficient, and obtain the allocated weight of the supplier according to the compensated allocated weight for in-province suppliers and the compensated allocated weight for production-type suppliers.

[0100] The core objective of this embodiment is to assign initial weights to suppliers by quantifying their geographical advantages (within the province / outside the province) and type advantages (production type / trade type), so as to achieve the scientificity and fairness of order allocation. Specifically:

[0101] Geographical weight takes precedence. Suppliers within the province are assigned higher weights due to lower logistics costs and faster response speeds; type weight takes precedence. Production-type suppliers are assigned higher weights due to stronger quality controllability; weight superposition mechanism: combining geographical and type weights, giving priority to production-type suppliers within the province to ensure the rationality of order allocation.

[0102] Specifically, the first allocation weight coefficient (geographical weight) is 0.1. Suppliers within the province obtain higher weights due to geographical advantages, reducing logistics costs.

[0103] The second allocation weight coefficient (type weight) is 0.15. Production-type suppliers obtain higher weights due to quality controllability, reducing delivery risks.

[0104] Generally speaking, first, according to the first allocation weight coefficient, 10% of the order volume to be allocated is assigned to suppliers within the province as the geographical weight compensation for suppliers within the province, and the remaining order volume to be allocated is evenly divided among suppliers inside and outside the province.

[0105] According to the second allocation weight coefficient, 15% of the order volume to be allocated is assigned to production-type suppliers as the type weight compensation for production-type suppliers, and the remaining order volume to be allocated is evenly divided among production-type suppliers and trade-type suppliers.

[0106] Suppliers within the province obtain higher weights due to geographical advantages, reducing logistics costs (such as transportation costs and warehousing costs). Production-type suppliers obtain higher weights due to type advantages, reducing quality problems caused by supplier type defects.

[0107] Production-type suppliers within the province have the highest weights, and trade-type suppliers outside the province have the lowest weights, forming a clear priority system. It should be noted that by adjusting the coefficient values (such as changing the first allocation weight coefficient from 0.1 to 0.15), it can flexibly adapt to the geographical and type preferences of different enterprises.

[0108] As an embodiment of this embodiment, the allocation weight of the supplier is obtained according to the first allocation weight coefficient and the second allocation weight coefficient, specifically:

[0109] If all the suppliers are suppliers within the province,

[0110] When there are production-type suppliers among the suppliers, the compensation allocation weight of the production-type suppliers is obtained according to the second allocation weight coefficient, and the remaining allocation weight is evenly divided among all suppliers;

[0111] When all the suppliers are trading suppliers, the weight to be allocated is evenly distributed among all suppliers.

[0112] The main purpose of this embodiment is to allocate orders according to the supplier type (production type or trading type) when all suppliers are in-province suppliers. The specific goal is to give priority to ensuring the order volume of production-type suppliers while ensuring that trading-type suppliers can also receive fair distribution.

[0113] First, confirm whether all suppliers are in-province suppliers. If all suppliers are in-province suppliers, further determine whether there are production-type suppliers.

[0114] Calculate the allocation weight of production-type suppliers: Calculate the allocation weight of production-type suppliers according to the second allocation weight coefficient. Assume the second allocation weight coefficient is W 生产 , then the allocation weight of production-type suppliers is W 生产 × total order volume.

[0115] Evenly distribute the remaining weight to be allocated: Evenly distribute the remaining weight to be allocated among all suppliers. The remaining weight to be allocated = total order volume - the allocation weight of production-type suppliers. The allocation weight of each supplier = the remaining weight to be allocated / the number of all suppliers.

[0116] If all suppliers are trading suppliers, directly distribute evenly: Distribute the total order volume evenly among all suppliers. The allocation weight of each supplier = total order volume / the number of all suppliers.

[0117] Specifically, Case 1: There are production-type suppliers. Total order volume: 1000 pieces. Supplier list: Supplier A, in-province production type; Supplier B, in-province trading type; Supplier C, in-province production type; Supplier D, in-province trading type.

[0118] When allocating orders, confirm the supplier type: All suppliers are in-province suppliers. There are production-type suppliers (A and C).

[0119] Calculate the allocation weight of production-type suppliers: Assume the second allocation weight coefficient W 生产 = 0.15 The allocation weight of production-type suppliers = 0.15 × 1000 = 150 pieces, and the remaining weight to be allocated = 1000 - 150 = 850 pieces.

[0120] Evenly distribute the remaining weight to be allocated:

[0121] The allocation weight of each supplier = 850 / 4 = 212.5 pieces.

[0122] Therefore, for production-type suppliers (A and C): 150 (type compensation) + 212.5 = 362.5 pieces (rounded to 363 pieces).

[0123] Trading suppliers (B and D): 212.5 pieces (only the evenly divided part).

[0124] The allocation weight coefficient is used to calculate the proportion of the order volume that a specific type of supplier should receive. The second allocation weight coefficient W 生产 is for manufacturing suppliers. After compensating for a specific type of supplier, the remaining order volume needs to be finally allocated through equal division or other rules.

[0125] In this embodiment, the manufacturing suppliers obtain a higher share through type compensation, ensuring that their production capacity is fully utilized. For example, in Case 1, the allocation volume of manufacturing supplier A (363 pieces) is significantly higher than that of trading supplier B (212 pieces). The equal division of the remaining order volume ensures that all suppliers receive at least a basic share, avoiding extreme allocation deviations caused by the compensation mechanism. Geographic compensation reduces logistics costs, and type compensation guarantees quality stability, forming a "cost + quality" dual-optimal order allocation.

[0126] As an embodiment under this implementation manner, obtaining the allocation weight of the supplier according to the first allocation weight coefficient and the second allocation weight coefficient further includes:

[0127] If the supplier includes both in-province suppliers and out-of-province suppliers,

[0128] when all the suppliers are trading suppliers, obtain the compensation allocation weight of in-province suppliers according to the first allocation weight coefficient, and evenly divide the remaining to-be-allocated weight among all suppliers;

[0129] when there are manufacturing suppliers among the suppliers, obtain the compensation allocation weight of in-province suppliers according to the first allocation weight coefficient, combine it with the second allocation weight coefficient to obtain the compensation allocation weight of in-province manufacturing suppliers, evenly divide the unallocated weight in the in-province supplier compensation allocation weight among in-province suppliers, and evenly divide the remaining unallocated weight among all suppliers.

[0130] The core objective of this embodiment is to ensure priority for in-province suppliers, especially manufacturing suppliers, through dual-priority allocation of geography (the first allocation weight coefficient) and type (the second allocation weight coefficient) when the supplier includes both in-province and out-of-province.

[0131] Among them, in-province has priority. In-province suppliers obtain a basic weight (0.1) due to geographical advantages. Manufacturing has priority. Manufacturing suppliers obtain an additional weight (0.15) due to type advantages. The hierarchical equal division mechanism balances the fairness between in-province and out-of-province suppliers by stepwise allocating the remaining weight.

[0132] First, confirm the supplier type and determine whether the supplier includes in-province and out-of-province. If both in-province and out-of-province suppliers exist, enter the subsequent allocation process.

[0133] When all are trading suppliers, set the basic weight allocation for in-province suppliers, and allocate the initial weights of in-province suppliers according to the first allocation weight coefficient (0.1).

[0134] Total in-province weight = 0.1 × total order volume

[0135] Execute the equal distribution of the remaining weights. The remaining weight = total order volume - in-province trading weight. The remaining weight is evenly distributed among all suppliers (in-province + out-of-province).

[0136] In-province trading suppliers obtain priority through basic weights, and out-of-province suppliers obtain a basic share through equal distribution.

[0137] When there are manufacturing suppliers, conduct basic weight allocation for in-province suppliers, and allocate the initial weights of in-province suppliers according to the first allocation weight coefficient (0.1).

[0138] Total in-province weight = 0.1 × total order volume

[0139] Execute additional weight allocation for manufacturing suppliers, and allocate the additional weights of in-province manufacturing suppliers according to the second allocation weight coefficient (0.15).

[0140] In-province manufacturing weight = 0.15 × total in-province weight

[0141] Equalize the unallocated weights in the province. The unallocated weight in the province = total in-province weight - in-province manufacturing weight. The unallocated weight in the province is evenly distributed among all in-province suppliers (including in-province manufacturing and trading).

[0142] Equalize the remaining unallocated weights. The remaining unallocated weight = total order volume - total in-province weight. The remaining weight is evenly distributed among all suppliers (in-province + out-of-province).

[0143] Manufacturing suppliers obtain the highest priority through superimposed weights, followed by in-province trading suppliers, and out-of-province suppliers obtain a basic share through equal distribution.

[0144] Specifically, there is a mixture of in-province and out-of-province, and there are manufacturing suppliers. The total order volume is 1000 pieces. The supplier list: In-province supplier A (manufacturing), B (trading); Out-of-province supplier C (manufacturing), D (trading).

[0145] First, execute the total in-province weight allocation. Total in-province weight = 0.1 × 1000 = 100 pieces.

[0146] Second, execute the additional weight allocation for in-province manufacturing. In-province manufacturing weight = 0.15 × 100 = 15 pieces (only allocated to A).

[0147] Next, perform the equal distribution of the unallocated weights within the province. The unallocated weight within the province = 100 - 15 = 85 pieces. The unallocated weight within the province is evenly divided between A and B: 85 / 2 = 42.5 pieces.

[0148] Perform the equal distribution of the remaining unallocated weights. The remaining unallocated weight = 1000 - 100 = 900 pieces. It is evenly distributed among all suppliers, 900 / 4 = 225 pieces.

[0149] The final distribution result is:

[0150] A (domestic production type): 15 (extra for production type) + 42.5 (equal distribution within the province) + 225 (total equal distribution) = 282.5 pieces;

[0151] B (domestic trading type): 42.5 (equal distribution within the province) + 225 (total equal distribution) = 267.5 pieces;

[0152] C (foreign production type): 225 pieces;

[0153] D (foreign trading type): 225 pieces.

[0154] Through the hierarchical distribution mechanism of this embodiment, the priorities within the province are clarified. Domestic suppliers (regardless of type) obtain preferential distribution through the basic weight (10%). This enables domestic production-type suppliers to exert double advantages, and domestic production-type suppliers can stack geographical and type weights.

[0155] In addition, the equal distribution of the remaining weights ensures that foreign suppliers receive at least the basic share, avoiding being completely excluded. Geographical weights reduce logistics costs, and type weights guarantee quality stability, forming a "domestic + production type" double-optimal order distribution system.

[0156] As an embodiment under this implementation manner, obtaining the distribution weights of the suppliers according to the first distribution weight coefficient and the second distribution weight coefficient further includes:

[0157] If all the suppliers are foreign suppliers, evenly divide the weight to be distributed among all the suppliers.

[0158] The core objective of this embodiment is to ensure fairness through the equal distribution strategy when all suppliers are foreign, while promoting competition and cost control among suppliers. First, it avoids unfair distribution due to all suppliers being foreign and eliminates geographical discrimination. The equal distribution mechanism encourages suppliers to optimize prices, quality, or services to win more orders, thus motivating supplier competition. At the same time, the process is simplified. When there are no geographical or type differences, a simple and transparent distribution rule is adopted to reduce management complexity.

[0159] If all the suppliers are foreign suppliers, enter the equal distribution process. Directly divide the total order quantity evenly among all foreign suppliers.

[0160]

[0161] Out-of-province suppliers are given equal opportunities to avoid unfair distribution caused by decision-making biases.

[0162] Specifically, out-of-province suppliers include production-type and trading-type ones. The total order quantity is 2,000 pieces. The supplier list is: Supplier X (production-type), Y (trading-type), Z (production-type), all of which are out-of-province.

[0163] Evenly divide the total order quantity:

[0164]

[0165] The final distribution result is that X, Y, and Z are each allocated 667 pieces (the sum is 2,001 pieces after rounding, and it needs to be adjusted to 666 or 667 pieces to ensure the sum is 2,000 pieces).

[0166] Even if there are production-type and trading-type suppliers, the equal distribution strategy still ensures fairness and avoids weight biases caused by type differences.

[0167] In this embodiment, through the equal distribution strategy, all out-of-province suppliers obtain equal shares, avoiding distribution biases caused by human preferences or interest relationships, and ensuring fairness. It prompts suppliers to strive for more orders by optimizing price, quality, or service, achieving cost and quality optimization. At the same time, without complex weight calculations or evaluations, only simple equal distribution is required, reducing internal control risks. Moreover, evenly dividing the order quantity can avoid relying on a single supplier and reduce the risk of supply chain interruption.

[0168] As a preferred embodiment of the present invention, according to the supplier assessment results, the distribution weights are adjusted, specifically:

[0169] The assessment levels include first-level, second-level, and third-level.

[0170] According to the supplier assessment results, a compensation distribution weight coefficient is set to obtain the compensation distribution weight, and the compensation distribution weight is evenly divided among the first-level suppliers; or,

[0171] According to the assessment level difference from the first-level suppliers, a first compensation distribution weight coefficient and a second compensation distribution weight coefficient are respectively set for the second-level suppliers and the third-level suppliers to obtain the first compensation distribution weight and the second compensation distribution weight.

[0172] According to the distribution weight of the second-level suppliers combined with the first compensation distribution weight, the adjustment weight of the second-level suppliers to the first-level suppliers is obtained, and according to the distribution weight of the third-level suppliers combined with the second compensation distribution weight, the adjustment weight of the third-level suppliers to the first-level suppliers is obtained.

[0173] The core objective of this embodiment is to dynamically adjust the allocation weights based on the supplier assessment results, ensuring that high-performance suppliers receive more orders while motivating low-performance suppliers to improve service quality. Among them, orders are preferentially allocated to high-performance suppliers (first-level suppliers) to ensure order quality and delivery efficiency. Through the weight adjustment mechanism, second-level and third-level suppliers are promoted to improve their performance, forming a virtuous competition. This avoids over-reliance on low-performance suppliers and reduces the risk of supply chain disruptions.

[0174] In this embodiment, suppliers are classified into first-level suppliers with the best performance (such as assessment score ≥ 80 points), second-level suppliers with good performance (such as assessment score 60 - 80 points), and third-level suppliers that need improvement (such as assessment score < 60 points) according to the performance of the suppliers (such as delivery on-time rate, quality pass rate, service response speed, etc.).

[0175] This embodiment does not limit the method of adjusting the allocation weights and can adopt any one of the following embodiments.

[0176] Embodiment 1: Directly compensate first-level suppliers.

[0177] Set the compensation allocation weight coefficient. According to the assessment results, determine the compensation allocation weight coefficient (for example: compensation coefficient = 0.1, that is, 10% of the total order volume). It should be noted that for the order volume outside the compensated order volume (that is, 90% of the total order volume), according to the aforementioned steps, the allocation weights are determined for each supplier based on the supplier's location and supplier type. 10% of the total order volume is reserved for directly compensating first-level suppliers.

[0178] Calculate the compensation allocation weight:

[0179] Compensation allocation weight = compensation allocation weight coefficient × total order volume

[0180] Equally distribute it among first-level suppliers, and the compensation allocation weight is evenly distributed among all first-level suppliers.

[0181] This embodiment directly increases the order share of first-level suppliers and strengthens their market position.

[0182] Embodiment 2: Stepwise compensation based on the assessment grade difference.

[0183] Set the compensation coefficient. According to the assessment grade difference (the gap between the first level and the second and third levels), set the compensation coefficients for second-level and third-level suppliers. Among them, the first compensation allocation weight coefficient (for second-level suppliers) is 10% (that is, second-level suppliers need to transfer 10% of their own allocation weight to first-level suppliers). The second compensation allocation weight coefficient (for third-level suppliers) is 20% (that is, third-level suppliers need to transfer 20% of their own allocation weight to first-level suppliers).

[0184] Compensation allocation weight of secondary suppliers:

[0185] The first compensation allocation weight = secondary supplier allocation weight × first compensation coefficient

[0186] Compensation allocation weight of tertiary suppliers:

[0187] The second compensation allocation weight = tertiary supplier allocation weight × second compensation coefficient

[0188] Part of the weight of secondary suppliers is transferred to primary suppliers, and part of the weight of tertiary suppliers is transferred to primary suppliers.

[0189] New weight of primary suppliers:

[0190] New weight of primary suppliers = ∑(adjusted weights of all secondary suppliers) + ∑(adjusted weights of all tertiary suppliers)

[0191] In this embodiment, through stepped compensation, the weights of low-performance suppliers are directly proportionally transferred to primary suppliers, more accurately reflecting their performance differences. For example, in Case 2, tertiary supplier C transfers 20% of its weight, and primary supplier A receives all of the transferred share.

[0192] Specifically, the total order quantity is 2,000 pieces; the supplier list and assessment grades are: primary supplier X, secondary supplier Y, and tertiary supplier Z.

[0193] Initial allocation weights (assuming equal distribution), X, Y, and Z are each allocated approximately 667 pieces.

[0194] Set compensation coefficients:

[0195] The first compensation coefficient (transfer ratio of secondary suppliers) = 10%

[0196] The second compensation coefficient (transfer ratio of tertiary suppliers) = 20%

[0197] For secondary supplier Y:

[0198] Adjusted weight = 667 × 10% = 66.7 pieces

[0199] Therefore, the final weight of Y = 667 - 66.7 ≈ 600.3 pieces.

[0200] For tertiary supplier Z:

[0201] Adjusted weight = 667 × 20% = 133.4 pieces

[0202] Therefore, the final weight of Z = 667 - 133.4 ≈ 533.6 pieces.

[0203] For primary supplier X:

[0204] New weight = 66.7 (Y transfer) + 133.4 (Z transfer) = 200.1 pieces

[0205] Therefore, the final weight of X = 667 + 200.1 ≈ 867.1 pieces.

[0206] In this embodiment, the share of the first-level supplier X is increased to 43%, the second-level Y is reduced by 10%, and the third-level Z is reduced by 20%, forming an incentive mechanism of survival of the fittest. Moreover, the weight transfer is directly based on its own share, and the logic is more intuitive.

[0207] In addition, the weight transfer of low-performance suppliers is directly linked to their own shares, more directly reflecting their performance gaps. Moreover, the weight transfer ratios (10% and 20%) are linked to the difference in assessment levels, ensuring that the gains of high-performance suppliers are proportional to the losses of low-performance suppliers. At the same time, the share of low-performance suppliers is reduced, reducing the risk of supply chain dependence.

[0208] The present invention also provides an order generation system based on the rule of dividing bids and allocating quantities, including:

[0209] A data collection module for obtaining data on the location of the supplier, the type of the supplier, and the supplier assessment results;

[0210] A weight allocation module for determining the allocated weight for each supplier according to the location of the supplier and the type of the supplier, and adjusting the allocated weight according to the supplier assessment results;

[0211] An order allocation module for obtaining the order allocation quantity of each supplier according to the adjusted allocated weight.

[0212] This system can achieve any effect of the order generation method based on the rule of dividing bids and allocating quantities, which will not be elaborated here.

[0213] The present invention also provides a storage medium, on which a computer program is stored. When the computer program is executed, the steps of the order generation method based on the rule of dividing bids and allocating quantities are implemented. Therefore, any effect of the order generation method based on the rule of dividing bids and allocating quantities can be achieved, which will not be elaborated here.

[0214] The present invention further provides a processing device, including:

[0215] A memory for storing a computer program;

[0216] A processor for implementing the steps of the order generation method based on the rule of dividing bids and allocating quantities when executing the computer program. Therefore, any effect of the order generation method based on the rule of dividing bids and allocating quantities can be achieved, which will not be elaborated here.

[0217] What is not described in the present invention can be achieved by adopting or referring to the prior art.

[0218] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

[0219] The above are only the embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, various modifications and changes can be made to the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. A method for generating orders based on the rule of sub-standard and quantity, characterized in that: include: Determine the allocation weight for each supplier based on the supplier's location and supplier type; Adjust the allocation weights according to the supplier assessment results; According to the adjusted allocation weight, the order allocation quantity of each supplier is obtained; Among them, the supplier's location includes within the province or outside the province where the purchaser is located, the supplier type includes production type and trading type, and the supplier assessment result is the assessment level of the previous assessment cycle.

2. The order generation method based on the rule of sub-label and component according to claim 1 is characterized in that: The allocation weight of suppliers within the province is higher than that of suppliers outside the province. The allocation weight of production-oriented suppliers is higher than that of trading-oriented suppliers. The allocation weight of suppliers with higher assessment grades is higher than that of suppliers with lower assessment grades.

3. The order generation method based on the rule of sub-label and component according to claim 1 is characterized in that: Determine the weight for each supplier based on the supplier's location and type, as follows: The first allocation weight coefficient is set according to the suppliers in the province, and the second allocation weight coefficient is set according to the production-type suppliers. The compensation allocation weight of the supplier within the province is obtained according to the first allocation weight coefficient, the compensation allocation weight of the production-type supplier is obtained according to the second allocation weight coefficient, and the allocation weight of the supplier is obtained according to the compensation allocation weight of the supplier within the province and the compensation allocation weight of the production-type supplier.

4. The order generation method based on the rule of sub-label and component according to claim 3 is characterized in that: The allocation weight of the supplier is obtained according to the first allocation weight coefficient and the second allocation weight coefficient, specifically: If the suppliers mentioned are all suppliers within the province, When there is a production-type supplier among the suppliers, the compensation allocation weight of the production-type supplier is obtained according to the second allocation weight coefficient, and the remaining weight to be allocated is equally divided among all suppliers; When all the suppliers are trading suppliers, the weights to be allocated are equally divided among all the suppliers.

5. The order generation method based on the rule of sub-label and component according to claim 3 is characterized in that: Obtaining the allocation weight of the supplier according to the first allocation weight coefficient and the second allocation weight coefficient also includes: If the suppliers include both suppliers within the province and suppliers outside the province, When all the suppliers are trading suppliers, the compensation allocation weights of suppliers within the province are obtained according to the first allocation weight coefficient, and the remaining weights to be allocated are equally divided among all suppliers; When there are production-type suppliers among the suppliers, the compensation distribution weight of the suppliers within the province is obtained according to the first distribution weight coefficient, and the compensation distribution weight of the production-type suppliers within the province is obtained by combining the second distribution weight coefficient. The undistributed weight in the compensation distribution weight of the suppliers within the province is equally divided among the suppliers within the province, and the remaining undistributed weight is equally divided among all suppliers.

6. The order generation method based on the rule of sub-label and component according to claim 3 is characterized in that: Obtaining the allocation weight of the supplier according to the first allocation weight coefficient and the second allocation weight coefficient also includes: If the suppliers mentioned are all from outside the province, the weights to be allocated will be equally divided among all suppliers.

7. The order generation method based on the rule of sub-label and component according to claim 1 is characterized in that: According to the supplier assessment results, the allocation weights are adjusted as follows: The assessment levels include level one, level two and level three. According to the supplier assessment results, a compensation allocation weight coefficient is set to obtain a compensation allocation weight, and the compensation allocation weight is evenly distributed among the first-tier suppliers; or, According to the difference in assessment level between the first-tier suppliers and the second-tier suppliers, the first compensation allocation weight coefficient and the second compensation allocation weight coefficient are set for the second-tier suppliers and the third-tier suppliers respectively, and the first compensation allocation weight and the second compensation allocation weight are obtained. The adjustment weight of the second-tier supplier to the first-tier supplier is obtained based on the allocation weight of the second-tier supplier combined with the first compensation allocation weight, and the adjustment weight of the third-tier supplier to the first-tier supplier is obtained based on the allocation weight of the third-tier supplier combined with the second compensation allocation weight.

8. An order generation system based on the rule of sub-label and quantity, characterized in that: include: Data collection module, used to obtain data on supplier location, supplier type, and supplier assessment results; A weight allocation module is used to determine the allocation weight for each supplier according to the supplier's location and supplier type, and to adjust the allocation weight according to the supplier assessment results; The order allocation module is used to obtain the order allocation quantity of each supplier according to the adjusted allocation weight.

9. A storage medium, characterized in that: The storage medium stores a computer program, which, when executed, implements the steps of the order generation method based on the rule of sub-standard components as described in any one of claims 1 to 7.

10. A processing device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the order generation method based on the sub-standard component rule as described in any one of claims 1 to 7 when executing the computer program.

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