A way of processing information on a waybill, a device, a storage medium and an electronic device

Abstract

The application provides a way and device for processing waybill information, a storage medium and an electronic device, belonging to the technical field of information processing, aiming to optimize the virtual resource allocation scheme so that the number of accepted waybills is the largest under the condition of limited virtual resources. The method comprises: determining the virtual resource influence coefficient and the capacity resource influence coefficient that make the number of accepted waybills in the plurality of historical waybills the largest according to the specified capacity resource quantity of each historical waybill; determining the target virtual resource quantity that makes the to-be-allocated waybill accepted according to the specified capacity resource quantity of the to-be-allocated waybill, the virtual resource influence coefficient and the capacity resource influence coefficient; and sending the to-be-allocated waybill carrying the target virtual resource quantity to a terminal providing capacity.

Description

Technical Field

[0001] This invention belongs to the field of information processing technology, and in particular relates to a method, apparatus, storage medium and electronic device for processing waybill information. Background Technology

[0002] With the rapid development of the internet and logistics industry, more and more merchants and users are conducting transactions online, resulting in a large number of waybills. Delivery personnel, couriers, and individual drivers select and accept these waybills to complete the delivery services specified in them.

[0003] In waybill scheduling systems, when a region experiences severe weather or other unforeseen circumstances, many waybills often remain unaccepted. To attract more capacity, current technologies typically allocate the same amount of virtual resources to all waybills. However, this approach has a problem: waybills with a higher probability of acceptance (e.g., short-distance waybills) are still more likely to be accepted; while waybills with a lower probability of acceptance (e.g., long-distance waybills) and those already experiencing anomalies do not show a significant increase in acceptance probability compared to waybills with a higher probability of acceptance. Therefore, many waybills remain unaccepted, leading to a poor user experience and wasted capacity resources. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a waybill information processing method, apparatus, electronic device and storage medium to overcome the above problems or at least partially solve the above problems.

[0005] A first aspect of the present invention provides a waybill information processing method, the method comprising:

[0006] Based on the specified capacity resources of each of the multiple historical waybills, determine the virtual resource impact coefficient and capacity resource impact coefficient that maximize the number of waybills accepted among the multiple historical waybills;

[0007] Based on the specified quantity of transport capacity resources for the pending waybill, the virtual resource influence coefficient, and the transport capacity resource influence coefficient, determine the target quantity of virtual resources that will enable the pending waybill to be accepted.

[0008] Send a waybill carrying the quantity of the target virtual resources to the terminal providing the transportation capacity.

[0009] Optionally, based on the specified capacity resources of each of the multiple historical waybills, a virtual resource impact coefficient and a capacity resource impact coefficient are determined that maximize the number of waybills accepted among the multiple historical waybills, including:

[0010] For each of the plurality of historical waybills, iterate through the combination of each historical waybill and the amount of virtual resources to determine a target virtual resource allocation scheme that maximizes the number of waybills accepted among the plurality of historical waybills and satisfies the overall constraint condition. The overall constraint condition includes at least the following: the sum of virtual resources allocated to the plurality of historical waybills does not exceed a predetermined total number of virtual resources, and the sum of the specified capacity resources of the plurality of historical waybills does not exceed a predetermined total number of capacity resources.

[0011] Based on the target virtual resource allocation scheme, determine the virtual resource impact coefficient and the transportation capacity resource impact coefficient.

[0012] Optionally, based on the target virtual resource allocation scheme, the virtual resource impact coefficient and the capacity resource impact coefficient are determined, including:

[0013] For each of the multiple historical waybills, based on the multiple virtual resource allocation schemes for that historical waybill, according to the preset virtual resource influence coefficient and the preset capacity resource influence coefficient, and combined with the specified capacity resource quantity for each historical waybill, a virtual resource allocation scheme that maximizes the number of historical waybills to be accepted is obtained.

[0014] When the virtual resource allocation scheme that results in the largest number of historical waybills being accepted does not meet the overall constraint, the preset virtual resource influence coefficient and the preset transportation capacity resource influence coefficient are updated. Based on the updated virtual resource influence coefficient and the transportation capacity resource influence coefficient, the virtual resource allocation scheme that results in the largest number of historical waybills being accepted is updated. The above steps are repeated until the target virtual resource allocation scheme is obtained.

[0015] The preset virtual resource influence coefficient of the target virtual resource allocation scheme is determined as the virtual resource influence coefficient, and the preset capacity resource influence coefficient of the target virtual resource allocation scheme is determined as the capacity resource influence coefficient.

[0016] Optionally, based on the specified capacity resource quantity of the to-be-assigned waybill, the virtual resource influence coefficient, and the capacity resource influence coefficient, the target virtual resource quantity for accepting the to-be-assigned waybill is determined, including:

[0017] By iterating through the combinations of the unassigned waybills and the quantity of virtual resources, multiple virtual resource allocation schemes are obtained;

[0018] Based on the virtual resource impact coefficient and the transportation capacity resource impact coefficient, and combined with the specified transportation capacity resource quantity of the order to be allocated, determine the virtual resource allocation scheme for the accepted order among the multiple virtual resource allocation schemes;

[0019] The number of virtual resources corresponding to the virtual resource allocation scheme of the accepted order is determined as the target number of virtual resources that enables the order to be allocated to be accepted.

[0020] Optionally, the method further includes:

[0021] Every preset period, the virtual resource impact coefficient and the transportation capacity resource impact coefficient are updated based on the specified virtual resource quantity of each of the multiple historical waybills in the most recent period.

[0022] A second aspect of the present invention provides a waybill information processing apparatus, comprising:

[0023] The coefficient determination module is used to determine the virtual resource influence coefficient and the capacity resource influence coefficient that maximize the number of accepted orders among the multiple historical waybills, based on the specified capacity resource quantity of each of the multiple historical waybills.

[0024] The resource determination module is used to determine the target number of virtual resources that will enable the shipment to be accepted, based on the specified quantity of transport capacity resources for the shipment to be assigned, the virtual resource influence coefficient, and the transport capacity resource influence coefficient.

[0025] The waybill sending module is used to send waybills carrying the target number of virtual resources to be allocated to the terminals that provide transportation capacity.

[0026] Optionally, the coefficient determination module includes:

[0027] The scheme determination submodule is used to, for each of the multiple historical waybills, traverse the combination of each historical waybill and the amount of virtual resources, and determine the target virtual resource allocation scheme that maximizes the number of waybills accepted among the multiple historical waybills and satisfies the overall constraint condition, wherein the overall constraint condition includes at least: the sum of virtual resources allocated to the multiple historical waybills does not exceed the predetermined total number of virtual resources, and the sum of the specified capacity resources of the multiple historical waybills does not exceed the predetermined total number of capacity resources;

[0028] The coefficient determination submodule is used to determine the virtual resource impact coefficient and the transportation capacity resource impact coefficient based on the target virtual resource allocation scheme.

[0029] Optionally, the coefficient determination submodule includes:

[0030] The resource determination unit is used to determine, for each of the multiple historical waybills, a virtual resource allocation scheme that maximizes the number of historical waybills to be accepted, based on multiple virtual resource allocation schemes for that historical waybill, according to a preset virtual resource influence coefficient and a preset capacity resource influence coefficient, combined with the specified capacity resource quantity for each historical waybill.

[0031] The scheme update unit is used to update the preset virtual resource influence coefficient and the preset transportation capacity resource influence coefficient when the virtual resource allocation scheme that results in the largest number of historical waybills being accepted does not meet the overall constraint condition. Based on the updated virtual resource influence coefficient and the transportation capacity resource influence coefficient, the virtual resource allocation scheme that results in the largest number of historical waybills being accepted is updated. The above steps are repeated until the target virtual resource allocation scheme is obtained.

[0032] The coefficient determination unit is used to determine the preset virtual resource influence coefficient of the target virtual resource allocation scheme as the virtual resource influence coefficient, and to determine the preset transportation capacity resource influence coefficient of the target virtual resource allocation scheme as the transportation capacity resource influence coefficient.

[0033] Optionally, the resource determination module includes:

[0034] The traversal submodule is used to traverse the combination of the waybill to be allocated and the number of virtual resources to obtain multiple virtual resource allocation schemes;

[0035] The parameter acquisition submodule is used to determine the virtual resource allocation scheme of the accepted order among the multiple virtual resource allocation schemes, based on the virtual resource influence coefficient and the transportation capacity resource influence coefficient, combined with the specified transportation capacity resource quantity of the order to be allocated.

[0036] The resource determination submodule is used to determine the number of virtual resources corresponding to the virtual resource allocation scheme of the accepted order as the target number of virtual resources that will enable the order to be allocated to be accepted.

[0037] Optionally, the device further includes:

[0038] The coefficient update module is used to update the virtual resource influence coefficient and the transportation capacity resource influence coefficient every preset period, based on the specified virtual resource quantity of each of the multiple historical waybills in the most recent period.

[0039] A third aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed, implements the steps of the waybill information processing method disclosed in the embodiments of this application.

[0040] A fourth aspect of the present invention provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the waybill information processing method disclosed in the embodiments of this application.

[0041] The embodiments of the present invention have the following advantages:

[0042] In this embodiment, based on the specified capacity resource quantities of each of the multiple historical waybills, a virtual resource influence coefficient and a capacity resource influence coefficient are determined to maximize the number of accepted orders among the multiple historical waybills. Based on the specified capacity resource quantity of the waybill to be allocated, the virtual resource influence coefficient, and the capacity resource influence coefficient, a target virtual resource quantity for the waybill to be allocated is determined. The waybill to be allocated, carrying the target virtual resource quantity, is then sent to the terminal providing capacity. Thus, by determining the virtual resource influence coefficient and capacity resource influence coefficient through historical orders, the target virtual resource quantity for the waybill to be allocated can be determined. The waybill to be allocated, carrying the target virtual resource quantity, is then sent to the terminal providing capacity, enabling the terminal to accept the waybill. The above technical solution of this application embodiment can determine the target virtual resource quantity for each waybill to be allocated. Therefore, it can maximize the number of accepted orders for all waybills with a limited total virtual resource quantity, thereby improving user experience and avoiding waste of capacity resources. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart of the steps of a waybill information processing method in an embodiment of the present invention;

[0045] Figure 2 This is a flowchart illustrating the steps for determining the virtual resource impact coefficient and the transportation capacity resource impact coefficient in this embodiment of the invention.

[0046] Figure 3 This is a flowchart illustrating the steps for determining the target number of virtual resources in an embodiment of the present invention;

[0047] Figure 4 This is a schematic diagram of the structure of a waybill information processing device according to an embodiment of the present invention. Detailed Implementation

[0048] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, this application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] To address the issue that many waybills remain unaccepted due to relevant waybill scheduling strategies, the applicant proposes the following technical concept: Based on the information of the waybills to be assigned, combined with the total amount of transportation capacity resources and the total amount of allocable virtual resources, the amount of virtual resources allocated to each waybill is calculated to maximize the number of waybills accepted among all the waybills to be assigned.

[0050] The applicant considered that whether a waybill is accepted is influenced not only by the waybill's inherent characteristics (such as the specified amount of transport capacity), but also primarily by the characteristics of transport capacity and virtual resources. Therefore, the applicant proposed determining the quantity of virtual resources required for a waybill to be accepted based on these characteristics, combined with the waybill's features. Specifically, a virtual resource influence coefficient and a transport capacity influence coefficient are constructed to characterize the impact of these characteristics on the waybill; these coefficients are determined based on historical waybills. In this way, the decision-making process fully considers the influence of virtual and transport capacity characteristics, and, combined with the waybill's inherent features, determines the quantity of virtual resources required for a waybill to be accepted. For multiple waybills, a virtual resource allocation scheme that maximizes the number of accepted waybills can be determined. Therefore, allocating virtual resources according to this scheme will maximize the number of accepted waybills.

[0051] In view of this, the applicant proposes a waybill information processing method to solve the above-mentioned technical problems. This waybill information processing method can be applied to logistics and distribution, as well as to ride-hailing scenarios.

[0052] Reference Figure 1 The diagram illustrates a flowchart of a waybill information processing method according to an embodiment of this application. Figure 1 As shown, the method can be performed by a server or terminal device using the following steps:

[0053] Step S110: Based on the specified capacity resources of each of the multiple historical waybills, determine the virtual resource influence coefficient and the capacity resource influence coefficient that maximize the number of waybills accepted among the multiple historical waybills.

[0054] The virtual resource impact coefficient characterizes the impact of virtual resource characteristics on a waybill. These virtual resource characteristics include the amount of virtual resources allocated to the waybill, the total planned amount of virtual resources, and the amount of virtual resources allocated to other waybills.

[0055] The capacity resource impact coefficient characterizes how a waybill is affected by capacity resource characteristics, which include the amount of total capacity resources allocated to the order and the amount of capacity resources allocated to other waybills.

[0056] The characteristics of a waybill include the amount of transportation resources required to complete the waybill (the specified amount of transportation resources for the waybill) and the amount of original virtual resources for the waybill.

[0057] Based on the specified capacity resources of multiple historical waybills, and combined with other information about these waybills, including the total number of waybills, the capacity resources occupied by each waybill, the total capacity resources, the minimum virtual resource quantity for each waybill, and the total virtual resource quantity, a training neural network or a preset virtual resource calculation formula, incorporating preset virtual resource influence coefficients and preset capacity resource influence coefficients, iterates through each historical waybill and virtual resource quantity combination. This yields the probability that a waybill will be accepted when allocated a preset number of virtual resources. Each waybill has only two possibilities: accepted or not accepted. The preset virtual resource quantity that can be allocated to a single waybill has multiple values. These values ​​are then combined with each waybill to obtain the combination of waybill and virtual resource quantity.

[0058] By continuously optimizing the preset virtual resource influence coefficient and the preset capacity resource influence coefficient, the virtual resource allocation schemes of multiple historical waybills can meet the overall constraints while ensuring the maximum number of historical waybills that are accepted, thereby determining the virtual resource influence coefficient and the capacity resource influence coefficient.

[0059] Therefore, we can determine the virtual resource impact coefficient and the capacity resource impact coefficient that, under the overall constraint, result in the largest number of historical waybills being accepted among multiple historical waybills.

[0060] Step S120: Determine the target virtual resource quantity that will allow the pending waybill to be accepted, based on the specified capacity resource quantity of the waybill to be assigned, the virtual resource influence coefficient, and the capacity resource influence coefficient.

[0061] Based on the specified capacity resources of the pending waybill, by using a neural network or target virtual resource calculation formula to determine the influence coefficient of virtual resources and the influence coefficient of capacity resources, and by iterating through the combinations of the pending waybill and the virtual resource quantity, the target virtual resource quantity that will enable the pending waybill to be accepted can be determined.

[0062] When allocating virtual resources according to the target virtual resource quantity determined by each of the multiple pending waybills, it can be guaranteed that the number of waybills accepted among the multiple pending waybills is the maximum, and the sum of the capacity resources occupied by the multiple pending waybills and the sum of the allocated virtual resources both satisfy the overall constraint condition, that is, the sum of the virtual resources occupied by the multiple pending waybills does not exceed the predetermined total virtual resource quantity, and the sum of the specified capacity resources of the multiple historical waybills does not exceed the predetermined total capacity resource quantity.

[0063] Step S130: Send a waybill carrying the target virtual resource quantity to the terminal providing the transportation capacity.

[0064] Send a pending waybill carrying the target number of virtual resources to multiple terminals that provide transportation capacity, so that any terminal user providing transportation capacity can accept the pending waybill.

[0065] Because the number of target virtual resources is the number of target virtual resources that will enable the pending waybills to be accepted, when all pending waybills and their corresponding target virtual resource quantities are sent to multiple terminals providing transportation capacity, the number of waybills accepted will be the highest among all pending waybills.

[0066] By adopting the technical solution of the above embodiments of this application, based on the information contained in historical waybills and the specified amount of transportation capacity resources, and using a neural network to be trained or a preset virtual resource calculation formula containing preset virtual resource influence coefficients and preset transportation capacity resource influence coefficients, the virtual resource influence coefficients and transportation capacity resource influence coefficients are determined by traversing each combination of historical waybills and virtual resource quantities. Then, by combining the determined virtual resource influence coefficients and transportation capacity resource influence coefficients with the specified transportation capacity resources of the waybill to be allocated, the target amount of virtual resources for the waybill to be allocated can be determined. For multiple waybills to be allocated, a target virtual resource allocation scheme can be determined that maximizes the number of waybills accepted among the multiple waybills to be allocated and satisfies the overall constraint conditions, thereby improving user experience and avoiding waste of transportation capacity resources.

[0067] Optionally, as an embodiment, based on the specified capacity resources of each of the multiple historical waybills, a virtual resource impact coefficient and a capacity resource impact coefficient are determined to maximize the number of waybills accepted among the multiple historical waybills, such as... Figure 2 The steps shown are as follows:

[0068] Step S210: For each historical waybill among the plurality of historical waybills, iterate through the combination of each historical waybill and the amount of virtual resources to determine a target virtual resource allocation scheme that maximizes the number of waybills accepted among the plurality of historical waybills and satisfies the overall constraint condition, wherein the overall constraint condition includes at least: the sum of virtual resources allocated to the plurality of historical waybills does not exceed a predetermined total number of virtual resources, and the sum of the specified capacity resources of the plurality of historical waybills does not exceed a predetermined total number of capacity resources.

[0069] The overall constraints include at least the following: the sum of virtual resources allocated to multiple historical waybills does not exceed the predetermined total number of virtual resources, and the sum of designated capacity resources for multiple historical waybills does not exceed the predetermined total number of capacity resources. The predetermined total number of virtual resources refers to the total number of virtual resources that can be provided for the multiple historical waybills; the predetermined total number of capacity resources refers to the sum of capacity resources that can be provided by personnel who can accept the multiple historical waybills.

[0070] The system acquires information from multiple historical waybills, including the total number of waybills, the amount of transportation resources used by each waybill, the total amount of transportation resources, the minimum amount of virtual resources per waybill, and the total amount of virtual resources. Using this information, a neural network or a preset virtual resource calculation formula is used to iterate through each combination of historical waybill and virtual resource quantity to determine the probability of a waybill being accepted when a preset amount of virtual resources is allocated to it.

[0071] By continuously optimizing the preset virtual resource influence coefficient and the preset capacity resource influence coefficient, the virtual resource allocation schemes of multiple historical waybills satisfy the overall constraint conditions while ensuring the maximum number of historical waybills that are accepted, thereby determining the virtual resource influence coefficient and the capacity resource influence coefficient.

[0072] By iterating through each combination of historical waybills and virtual resource quantities, a target virtual resource allocation scheme is determined that maximizes the number of waybills accepted among the multiple historical waybills and satisfies the overall constraint condition. Specifically, multiple values ​​for the number of virtual resources that can be allocated to a single waybill are preset. Then, these multiple values ​​are combined with each waybill. Using a neural network to be trained containing preset virtual resource influence coefficients and preset transportation capacity resource influence coefficients, or a preset virtual resource calculation formula, it can be determined whether the waybill is accepted under different combinations. Thus, a target virtual resource allocation scheme is obtained that maximizes the number of waybills accepted among the multiple historical waybills, ensures that the sum of the virtual resource quantities allocated to the multiple historical waybills does not exceed the predetermined total virtual resource quantity, and ensures that the sum of the specified transportation capacity resources of the multiple historical waybills does not exceed the predetermined total transportation capacity resource quantity.

[0073] For example, there are 50 waybills with a total planned virtual resource quantity of 170 and a total planned transportation capacity quantity of 110. If all 50 waybills are accepted, it will require 120 transportation capacity resources. The preset virtual resource quantity allocated to each waybill is an integer value ranging from 1 to 5, specifically 1, 2, 3, 4, and 5. Therefore, each of these 50 waybills can have 5 combinations of waybill and virtual resource quantities, resulting in a total of 50 × 5 combinations. Using a trained neural network or a preset virtual resource calculation formula that includes preset virtual resource influence coefficients and preset transportation capacity resource influence coefficients, it can be determined whether each waybill in these 250 combinations will be accepted. For each waybill, one combination with virtual resource quantities is selected, thus allowing for the selection of 50 target combinations. Allocating virtual resources to waybills based on the selected 50 target combinations maximizes the number of waybills accepted, while ensuring the total virtual resource expenditure of these 50 waybills does not exceed 170, and the total capacity resource expenditure of the accepted waybills does not exceed 110. The virtual resource allocation for each waybill within these 50 target combinations represents the virtual resource allocation scheme for each waybill within these 50 waybill allocation plans. Determining the virtual resource allocation scheme for a waybill refers to determining the amount of virtual resources allocated to that waybill.

[0074] In practice, the sum of the transportation resources required to accept all multiple waybills usually does not exceed the total planned transportation resources for those multiple waybills.

[0075] Step S220: Determine the virtual resource impact coefficient and the transportation capacity resource impact coefficient according to the target virtual resource allocation scheme.

[0076] In determining the target virtual resource allocation scheme, the preset virtual resource influence coefficient and preset transportation capacity resource influence coefficient are directly used for calculation. When the number of accepted orders among multiple historical waybills is the largest, the sum of the virtual resources allocated to these multiple historical waybills usually exceeds the predetermined number of virtual resources for these multiple historical waybills.

[0077] Using the excess amount of pre-defined virtual resources, update the preset virtual resource impact coefficient and the preset capacity resource impact coefficient. Based on the updated virtual resource impact coefficient and capacity resource impact coefficient, repeat the steps to determine the target virtual resource allocation scheme until the obtained virtual resource allocation scheme satisfies the overall constraint condition. The virtual resource allocation scheme that maximizes the number of accepted orders among multiple historical waybills and satisfies the overall constraint condition is determined as the target virtual resource allocation scheme. The preset virtual resource impact coefficient and preset capacity resource impact coefficient corresponding to the target virtual resource allocation scheme are used as the virtual resource impact coefficient and capacity resource impact coefficient, respectively.

[0078] Optionally, as an embodiment, determining the virtual resource impact coefficient and the transportation capacity resource impact coefficient according to the target virtual resource allocation scheme includes the following steps:

[0079] Step S310: For each of the multiple historical waybills, according to the multiple virtual resource allocation schemes of the historical waybill, and based on the preset virtual resource influence coefficient and the preset transportation capacity resource influence coefficient, combined with the specified transportation capacity resource quantity of each historical waybill, a virtual resource allocation scheme that maximizes the number of historical waybills to be accepted is obtained.

[0080] By iterating through each combination of historical waybill and virtual resource quantity, multiple virtual resource allocation schemes for historical waybills can be obtained. According to the preset virtual resource influence coefficient and preset capacity resource influence coefficient, the virtual resource allocation scheme that maximizes the number of historical waybills accepted can be obtained.

[0081] Step S320: When the virtual resource allocation scheme that maximizes the number of historical waybills accepted does not meet the overall constraint condition, update the preset virtual resource influence coefficient and the preset transportation capacity resource influence coefficient, and based on the updated virtual resource influence coefficient and the transportation capacity resource influence coefficient, update the virtual resource allocation scheme that maximizes the number of historical waybills accepted. Repeat the above steps until the target virtual resource allocation scheme is obtained.

[0082] The virtual resource allocation scheme that maximizes the number of historical waybills accepted by the preset virtual resource influence coefficient and preset transportation capacity resource influence coefficient usually does not meet the overall constraints, especially the sum of the virtual resource quantities, which often exceeds the predetermined virtual resource quantity.

[0083] When the overall constraint is not met, the preset virtual resource influence coefficient and preset capacity resource influence coefficient are updated using the excess virtual resource quantity. Specifically: the value exceeding the predetermined virtual resource quantity is calculated, and the corresponding sub-gradient is calculated using this excess value; the preset virtual resource influence coefficient and preset capacity resource influence coefficient are updated based on the sub-gradient; based on the updated preset virtual resource influence coefficient and preset capacity resource influence coefficient, the steps of determining the virtual resource allocation scheme are repeated until the obtained virtual resource allocation scheme satisfies the overall constraint. The virtual resource allocation scheme that maximizes the number of historical orders accepted and satisfies the overall constraint is determined as the target virtual resource allocation scheme, and the preset virtual resource influence coefficient and preset capacity resource influence coefficient corresponding to the target virtual resource allocation scheme are used as the virtual resource influence coefficient and capacity resource influence coefficient, respectively.

[0084] Optionally, if the virtual resource allocation scheme obtained after repeating the steps of determining the virtual resource allocation scheme a preset number of times still does not meet the overall constraint conditions, the minimum value exceeding the predetermined number of virtual resources obtained during the repetition process can be used to approximate the cost based on the overall constraint conditions, thereby determining the target virtual resource allocation scheme. The preset virtual resource influence coefficient and preset transportation capacity resource influence coefficient corresponding to the target virtual resource allocation scheme are used as the virtual resource influence coefficient and transportation capacity resource influence coefficient, respectively.

[0085] Step S330: Determine the preset virtual resource influence coefficient of the target virtual resource allocation scheme as the virtual resource influence coefficient, and determine the preset transportation capacity resource influence coefficient of the target virtual resource allocation scheme as the transportation capacity resource influence coefficient.

[0086] Based on the preset virtual resource influence coefficient and preset capacity resource influence coefficient obtained from the last update, the target virtual resource allocation scheme is obtained. The steps of stopping the repeated updates of the preset virtual resource influence coefficient and preset capacity resource influence coefficient and determining the target virtual resource allocation scheme are then followed. The preset virtual resource influence coefficient and preset capacity resource influence coefficient obtained from the last update are respectively determined as the virtual resource influence coefficient and the capacity resource influence coefficient.

[0087] The preset virtual resource influence coefficient corresponding to the obtained target virtual resource allocation scheme is determined as the virtual resource influence coefficient, and the preset transportation capacity resource influence coefficient corresponding to the obtained target virtual resource allocation scheme is determined as the transportation capacity resource influence coefficient.

[0088] By employing the technical solution of the above embodiments of this application, based on the information contained in historical waybills, a virtual resource allocation scheme that maximizes the number of historical waybills to be accepted can be obtained through a trained neural network containing preset virtual resource influence coefficients and preset capacity resource influence coefficients, and a preset virtual resource calculation formula. The preset virtual resource influence coefficients and preset capacity resource influence coefficients are then updated based on the value by which the virtual resource allocation scheme exceeds a predetermined number of virtual resources. The updated neural network or virtual resource calculation formula, based on the updated preset virtual resource influence coefficients and preset capacity resource influence coefficients, further updates the virtual resource allocation scheme that maximizes the number of historical waybills to be accepted. This process of obtaining the virtual resource allocation scheme is repeated until a target virtual resource allocation scheme that satisfies the overall constraints is obtained, thereby determining the virtual resource influence coefficients and capacity resource influence coefficients. Thus, based on historical waybills, the virtual resource influence coefficients and capacity resource influence coefficients can be determined, thereby obtaining a trained neural network or a target virtual resource calculation formula.

[0089] Optionally, as an embodiment, the target virtual resource quantity for accepting the waybill is determined based on the specified capacity resource quantity of the waybill to be assigned, the virtual resource influence coefficient, and the capacity resource influence coefficient. Figure 3 As shown, it includes:

[0090] Step S410: Iterate through the combinations of the order to be allocated and the number of virtual resources to obtain multiple virtual resource allocation schemes.

[0091] The system iterates through the combinations of unassigned waybills and virtual resource quantities to obtain multiple virtual resource allocation schemes. Specifically, it presets multiple values ​​for the number of virtual resources that can be allocated to each unassigned waybill, and then combines these values ​​with the unassigned waybill. For example, if the number of virtual resources that can be allocated to each unassigned waybill can be 1, 2, 3, 4, or 5, then five combinations of unassigned waybills and virtual resource quantities can be obtained, resulting in five virtual resource allocation schemes for that waybill.

[0092] Step S420: Based on the virtual resource impact coefficient and the transportation capacity resource impact coefficient, and in combination with the specified transportation capacity resource quantity of the order to be allocated, determine the virtual resource allocation scheme of the accepted order among the multiple virtual resource allocation schemes.

[0093] By determining the neural network or target virtual resource calculation formula based on the virtual resource influence coefficient and the capacity resource influence coefficient, and combining it with the specified capacity resource quantity of the waybill to be allocated, it is possible to calculate whether the waybill will be accepted under different combinations. Thus, it is possible to determine the virtual resource allocation scheme corresponding to the combination that is accepted among multiple combinations.

[0094] Step S430: Determine the number of virtual resources corresponding to the virtual resource allocation scheme of the accepted order as the target number of virtual resources that will enable the order to be allocated to be accepted.

[0095] The virtual resource allocation scheme and the corresponding number of virtual resources for the combination of orders to be accepted are determined as the target number of virtual resources to ensure that the order to be allocated is accepted.

[0096] When allocating virtual resources according to the target virtual resource quantity determined for each of the multiple pending waybills, it can be guaranteed that the number of waybills accepted among the multiple pending waybills is the maximum, and the sum of the transportation capacity resources occupied by the multiple pending waybills and the sum of the allocated virtual resources both satisfy the overall constraint conditions.

[0097] By adopting the technical solution of the above embodiments of this application, since the virtual resource influence coefficient and the capacity resource influence coefficient are obtained through historical waybills, they can reflect the situation where most waybills are affected by virtual resource characteristics and capacity resource characteristics. Therefore, for multiple waybills to be allocated, by determining the neural network or target virtual resource calculation formula of the virtual resource influence coefficient and the capacity resource influence coefficient, the target virtual resource quantity of each waybill to be allocated can meet the overall constraint conditions.

[0098] Optionally, as an embodiment, every preset period, the virtual resource influence coefficient and the transportation capacity resource influence coefficient are updated based on the specified virtual resource quantity of each of the multiple historical waybills in the most recent period.

[0099] Every preset period, based on the specified virtual resource quantity of each of the multiple historical waybills in the most recent period, the virtual resource influence coefficient and the capacity resource influence coefficient are updated according to the method of the above embodiment.

[0100] By employing the technical solution of the above embodiments of this application, the virtual resource influence coefficient and the capacity resource influence coefficient can be updated based on information from recent historical orders. Over time, changes in the total capacity resource quantity, the ratio between waybills and capacity resources, and the total virtual resource quantity can alter the impact of virtual resource characteristics and capacity resource characteristics on whether a waybill is accepted. This can cause the original virtual resource coefficient and capacity resource coefficient to no longer meet current needs. Therefore, updating the virtual resource influence coefficient and capacity resource influence coefficient based on information from recent historical orders ensures that the updated coefficients better meet current practical requirements.

[0101] As mentioned earlier, whether a waybill is accepted is influenced by numerous conditions. Calculating the amount of virtual resources allocated to each waybill under these constraints requires significant computational resources. Therefore, this applicant proposes using the Lagrange relaxation decomposition method to integrate the various constraints on the waybills into the calculation of virtual resource allocation. This allows for the easy determination of the target amount of virtual resources that maximizes the number of accepted waybills under each constraint.

[0102] Optionally, as an embodiment, the preset virtual resource calculation formula can be determined through the following steps:

[0103] Step S510: Construct the original virtual resource calculation formula.

[0104] The original virtual resource calculation formula is as follows:

[0105]

[0106]

[0107]

[0108] for all n:C wi +O wi ≥upmoney

[0109] In this formula: n represents the number of waybills; G(W i C wi The probability of a call being answered after virtual resources are allocated to a waybill is represented, with a value of 1 or 0; C wi The virtual resource allocation for each waybill is represented by ; subsidy represents the total virtual resource allocation for n waybills; Tr wi Represents the specified amount of transport capacity resources for the i-th waybill; Tr all Represents the total amount of transport capacity resources; O wi The initial virtual resource quantity represents the waybill; upmoney represents the minimum virtual resource quantity.

[0110] The first line of the formula represents the solution to allocate the amount of virtual resources to each waybill in order to maximize the number of waybills accepted among all waybills.

[0111] The second line of the formula represents the virtual resource quantity constraint: the sum of the virtual resource quantities allocated to each waybill equals the total virtual resource quantity.

[0112] The third line of the formula represents the constraint on the quantity of transport capacity resources: the sum of the specified transport capacity resources for each waybill is not greater than the total quantity of transport capacity resources.

[0113] The fourth line of the formula represents the minimum virtual resource quantity constraint: for each waybill, the sum of the virtual resource quantity allocated to it and the virtual resource quantity it currently carries is not less than the minimum virtual resource quantity of the waybill.

[0114] Step S520: Construct the converted virtual resource calculation formula.

[0115] By performing an equivalent transformation on the original virtual resource calculation formula, we can obtain the transformed virtual resource calculation formula. The transformed virtual resource calculation formula is as follows:

[0116]

[0117]

[0118]

[0119] for all n:Cwi +O wi ≥upmoney

[0120] In this formula: λ is the intermediate coefficient, MP2 refers to the first row of the formula, ▽ is the gradient operator; the meanings of the remaining letters and symbols are as described above.

[0121] Step S530: Obtain the preset virtual resource calculation formula.

[0122] Both the original and converted virtual resource calculation formulas are applied to all waybills simultaneously. However, considering that in practical applications, there is usually only one waybill to be allocated at any given moment, and the amount of virtual resources to be allocated to this single waybill needs to be calculated only for that one waybill, the applicant proposes using the Lagrange relaxation decomposition method to break down the converted virtual resource calculation formula into a preset virtual resource calculation formula. This preset virtual resource calculation formula can be used to calculate the amount of virtual resources allocated to the single waybill to be allocated. The preset virtual resource calculation formula is as follows:

[0123]

[0124]

[0125] In this formula: λ1 is the virtual resource impact coefficient; λ2 is the transportation capacity resource impact coefficient; MP2 i This refers to the first line of the formula; the meanings of the remaining letters and symbols are as described above.

[0126] This formula is obtained by performing a Lagrange relaxation decomposition on the transformed virtual resource calculation formula. In this way, the transformed virtual resource calculation formula is broken down into several corresponding subproblems.

[0127] After obtaining the preset virtual resource calculation formula, the preset virtual resource influence coefficient and preset transportation capacity resource influence coefficient in the formula are optimized through historical orders to obtain the target virtual resource calculation formula. Based on the target virtual resource calculation formula, the quantity of target virtual resources that should be allocated to the current unassigned waybill can be determined.

[0128] Optionally, the virtual resource influence coefficient and the capacity resource influence coefficient in the neural network to be trained can be determined by using historical order information. The neural network to be trained can be trained using historical order information as training samples to obtain the virtual resource influence coefficient and the capacity resource influence coefficient. For details, please refer to the relevant introduction in related technologies.

[0129] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0130] Figure 4 This is a structural block diagram of a waybill information processing device according to an embodiment of the present invention, as shown below. Figure 4 As shown, the waybill information processing device may include: a coefficient determination module, a resource determination module, and a waybill sending module, wherein:

[0131] The coefficient determination module is used to determine the virtual resource influence coefficient and the capacity resource influence coefficient that maximize the number of accepted orders among the multiple historical waybills, based on the specified capacity resource quantity of each of the multiple historical waybills.

[0132] The resource determination module is used to determine the target number of virtual resources that will enable the shipment to be accepted, based on the specified quantity of transport capacity resources for the shipment to be assigned, the virtual resource influence coefficient, and the transport capacity resource influence coefficient.

[0133] The waybill sending module is used to send waybills carrying the target number of virtual resources to be allocated to the terminals that provide transportation capacity.

[0134] Optionally, as one embodiment, the coefficient determination module includes:

[0135] The scheme determination submodule is used to, for each of the multiple historical waybills, traverse the combination of each historical waybill and the amount of virtual resources, and determine the target virtual resource allocation scheme that maximizes the number of waybills accepted among the multiple historical waybills and satisfies the overall constraint condition, wherein the overall constraint condition includes at least: the sum of virtual resources allocated to the multiple historical waybills does not exceed the predetermined total number of virtual resources, and the sum of the specified capacity resources of the multiple historical waybills does not exceed the predetermined total number of capacity resources;

[0136] The coefficient determination submodule is used to determine the virtual resource impact coefficient and the transportation capacity resource impact coefficient based on the target virtual resource allocation scheme.

[0137] Optionally, as an embodiment, the coefficient determination submodule includes:

[0138] The resource determination unit is used to determine, for each of the multiple historical waybills, a virtual resource allocation scheme that maximizes the number of historical waybills to be accepted, based on multiple virtual resource allocation schemes for that historical waybill, according to a preset virtual resource influence coefficient and a preset capacity resource influence coefficient, combined with the specified capacity resource quantity for each historical waybill.

[0139] The scheme update unit is used to update the preset virtual resource influence coefficient and the preset transportation capacity resource influence coefficient when the virtual resource allocation scheme that results in the largest number of historical waybills being accepted does not meet the overall constraint condition. Based on the updated virtual resource influence coefficient and the transportation capacity resource influence coefficient, the virtual resource allocation scheme that results in the largest number of historical waybills being accepted is updated. The above steps are repeated until the target virtual resource allocation scheme is obtained.

[0140] The coefficient determination unit is used to determine the preset virtual resource influence coefficient of the target virtual resource allocation scheme as the virtual resource influence coefficient, and to determine the preset transportation capacity resource influence coefficient of the target virtual resource allocation scheme as the transportation capacity resource influence coefficient.

[0141] Optionally, as one embodiment, the resource determination module includes:

[0142] The traversal submodule is used to traverse the combination of the waybill to be allocated and the number of virtual resources to obtain multiple virtual resource allocation schemes;

[0143] The parameter acquisition submodule is used to determine the virtual resource allocation scheme of the accepted order among the multiple virtual resource allocation schemes, based on the virtual resource influence coefficient and the transportation capacity resource influence coefficient, combined with the specified transportation capacity resource quantity of the order to be allocated.

[0144] The resource determination submodule is used to determine the number of virtual resources corresponding to the virtual resource allocation scheme of the accepted order as the target number of virtual resources that will enable the order to be allocated to be accepted.

[0145] Optionally, as an embodiment, the waybill information processing device further includes:

[0146] The coefficient update module is used to update the virtual resource influence coefficient and the transportation capacity resource influence coefficient every preset period, based on the specified virtual resource quantity of each of the multiple historical waybills in the most recent period.

[0147] The waybill information processing device disclosed in this application can determine the virtual resource influence coefficient and the transportation capacity resource influence coefficient through historical orders. This allows it to determine the target number of virtual resources required for a waybill to be accepted. The waybill carrying the target number of virtual resources is then sent to the terminal providing the transportation capacity, enabling the terminal to accept the waybill. The above technical solution of this application can determine the target number of virtual resources required for each waybill to be accepted. Therefore, with a limited total number of virtual resources, the number of waybills accepted is maximized, thereby improving user experience and preventing the waste of transportation capacity resources.

[0148] It should be noted that the device embodiments are similar to the method embodiments, so the description is relatively simple. For relevant details, please refer to the method embodiments.

[0149] This invention also provides a computer-readable storage medium storing a computer program, which, when executed, implements the steps of the waybill information processing method disclosed in this application.

[0150] This invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the waybill information processing method disclosed in this application.

[0151] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus embodiments, since they are substantially similar to the method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0152] The foregoing has provided a detailed description of a waybill information processing method, apparatus, storage medium, and electronic device provided by this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

[0153] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

Claims

1. A method for processing waybill information, characterized in that, include: Based on the specified capacity resources of each of the multiple historical waybills, determine the virtual resource impact coefficient and capacity resource impact coefficient that maximize the number of waybills accepted among the multiple historical waybills, including: For each of the multiple historical waybills, iterate through the combinations of each historical waybill and the amount of virtual resources to determine a target virtual resource allocation scheme that maximizes the number of accepted waybills among the multiple historical waybills and satisfies the overall constraint condition, wherein the overall constraint condition includes at least: The sum of virtual resources allocated to the plurality of historical waybills shall not exceed the predetermined total number of virtual resources, and the sum of the designated capacity resources of the plurality of historical waybills shall not exceed the predetermined total number of capacity resources. For each of the multiple historical waybills, based on the multiple virtual resource allocation schemes for that historical waybill, according to the preset virtual resource influence coefficient and the preset capacity resource influence coefficient, and combined with the specified capacity resource quantity for each historical waybill, a virtual resource allocation scheme that maximizes the number of historical waybills to be accepted is obtained. When the virtual resource allocation scheme that maximizes the number of historical waybills accepted does not meet the overall constraint, the preset virtual resource influence coefficient and the preset transportation capacity resource influence coefficient are updated. Based on the updated virtual resource influence coefficient and the transportation capacity resource influence coefficient, the virtual resource allocation scheme that maximizes the number of historical waybills accepted is updated. The above steps are repeated until the target virtual resource allocation scheme is obtained. The preset virtual resource influence coefficient of the target virtual resource allocation scheme is determined as the virtual resource influence coefficient, and the preset capacity resource influence coefficient of the target virtual resource allocation scheme is determined as the capacity resource influence coefficient; Based on the specified quantity of transport capacity resources for the pending waybill, the virtual resource influence coefficient, and the transport capacity resource influence coefficient, determine the target quantity of virtual resources that will enable the pending waybill to be accepted. Send a waybill carrying the quantity of the target virtual resources to the terminal providing the transportation capacity.

2. The method according to claim 1, characterized in that, Based on the specified capacity resource quantity of the pending waybill, the virtual resource influence coefficient, and the capacity resource influence coefficient, determine the target virtual resource quantity for the pending waybill to be accepted, including: By iterating through the combinations of the unassigned waybills and the number of virtual resources, multiple virtual resource allocation schemes are obtained; Based on the virtual resource impact coefficient and the transportation capacity resource impact coefficient, and combined with the specified transportation capacity resource quantity of the order to be allocated, determine the virtual resource allocation scheme for the accepted order among the multiple virtual resource allocation schemes; The number of virtual resources corresponding to the virtual resource allocation scheme of the accepted order is determined as the target number of virtual resources that enables the order to be allocated to be accepted.

3. The method according to any one of claims 1-2, characterized in that, The method further includes: Every preset period, the virtual resource impact coefficient and the transportation capacity resource impact coefficient are updated based on the specified virtual resource quantity of each of the multiple historical waybills in the most recent period.

4. A waybill information processing device, characterized in that, include: The coefficient determination module is used to determine the virtual resource influence coefficient and the capacity resource influence coefficient that maximize the number of accepted orders among the multiple historical waybills, based on the specified capacity resource quantity of each of the multiple historical waybills. The coefficient determination module includes: The scheme determination submodule is used to, for each of the multiple historical waybills, iterate through the combination of each historical waybill and the amount of virtual resources, and determine the target virtual resource allocation scheme that maximizes the number of accepted waybills among the multiple historical waybills and satisfies the overall constraint condition, wherein the overall constraint condition includes at least: The sum of virtual resources allocated to the plurality of historical waybills shall not exceed the predetermined total number of virtual resources, and the sum of the designated capacity resources of the plurality of historical waybills shall not exceed the predetermined total number of capacity resources. The coefficient determination submodule is used to determine the virtual resource impact coefficient and the transportation capacity resource impact coefficient based on the target virtual resource allocation scheme. The coefficient determination submodule includes: The resource determination unit is used to determine, for each of the multiple historical waybills, a virtual resource allocation scheme that maximizes the number of historical waybills to be accepted, based on multiple virtual resource allocation schemes for that historical waybill, according to a preset virtual resource influence coefficient and a preset capacity resource influence coefficient, combined with the specified capacity resource quantity for each historical waybill. The scheme update unit is used to update the preset virtual resource influence coefficient and the preset transportation capacity resource influence coefficient when the virtual resource allocation scheme that results in the largest number of historical waybills being accepted does not meet the overall constraint condition. Based on the updated virtual resource influence coefficient and the transportation capacity resource influence coefficient, the virtual resource allocation scheme that results in the largest number of historical waybills being accepted is updated. The above steps are repeated until the target virtual resource allocation scheme is obtained. The coefficient determination unit is used to determine the preset virtual resource influence coefficient of the target virtual resource allocation scheme as the virtual resource influence coefficient, and to determine the preset capacity resource influence coefficient of the target virtual resource allocation scheme as the capacity resource influence coefficient; The resource determination module is used to determine the target number of virtual resources that will enable the shipment to be accepted, based on the specified quantity of transport capacity resources for the shipment to be assigned, the virtual resource influence coefficient, and the transport capacity resource influence coefficient. The waybill sending module is used to send waybills carrying the target number of virtual resources to be allocated to the terminals that provide transportation capacity.

5. The apparatus according to claim 4, characterized in that, The resource determination module includes: The traversal submodule is used to traverse the combination of the waybill to be allocated and the number of virtual resources to obtain multiple virtual resource allocation schemes; The parameter acquisition submodule is used to determine the virtual resource allocation scheme of the accepted order among the multiple virtual resource allocation schemes, based on the virtual resource influence coefficient and the transportation capacity resource influence coefficient, combined with the specified transportation capacity resource quantity of the order to be allocated. The resource determination submodule is used to determine the number of virtual resources corresponding to the virtual resource allocation scheme of the accepted order as the target number of virtual resources that will enable the order to be allocated to be accepted.

6. The apparatus according to any one of claims 4-5, characterized in that, The device further includes: The coefficient update module is used to update the virtual resource influence coefficient and the transportation capacity resource influence coefficient every preset period, based on the specified virtual resource quantity of each of the multiple historical waybills in the most recent period.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed, implements the waybill information processing method as described in any one of claims 1-3.

8. An electronic device, characterized in that, include: A processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the program, it implements the waybill information processing method as described in any one of claims 1-3.

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