A method and system for collaborative dispatching of logistics materials based on big data analysis

Abstract

The present invention provides a method and system for coordinated dispatching of logistic materials based on big data analysis, which belongs to the field of big data technology, and specifically comprises: acquiring historical consumption data of different types of logistic materials of a target unit, and determining historical consumption fluctuation coefficients of different types of logistic materials and fluctuation types of logistic materials based on the historical consumption data, determining safety margins of different logistic materials through fluctuation types and historical consumption data, and determining an optimal mobilization strategy based on the deviation between the remaining amount of logistic materials of different fluctuation types after mobilization and the safety margin with storage space as a constraint condition, thereby ensuring the reliability of the guarantee of logistic materials.

Description

Technical Field

[0001] The present invention belongs to the field of big data technology, and in particular relates to a method for coordinated dispatching of logistics materials based on big data analysis. Background Art

[0002] In order to ensure the reliability of logistics supply of enterprises and institutions, the logistics management systems of more and more enterprises and institutions are gradually transforming towards informatization and digitalization. However, due to the differences in the consumption of different logistics materials in different enterprises and institutions, how to achieve the optimal scheduling of logistics materials and ensure the reliability of logistics supply has become a technical problem that needs to be solved urgently.

[0003] In order to solve the above technical problems, the invention patent CN202410036359.8 "An Optimized Collaborative Dispatch System for Health Emergency Equipment" solves the problem of multi-task and multi-target equipment configuration and deployment in the process of health emergency response, provides the optimal configuration and dispatching plan of equipment for the on-site command of prevention and control, and realizes the reasonable configuration and coordinated guarantee of rescue resources. However, it is not difficult to find the following technical problems through analysis:

[0004] The existing technical solutions ignore the consumption of different types of logistical materials when generating scheduling strategies. The consumption of different types of logistical materials is not consistent. Therefore, if the historical consumption data of logistical materials is ignored, the reliability of the supply of logistical materials cannot be guaranteed.

[0005] In response to the above technical problems, the present invention provides a method for coordinated scheduling of logistics materials based on big data analysis. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a method for coordinated scheduling of logistics materials based on big data analysis is provided.

[0008] A method for coordinated dispatching of logistics materials based on big data analysis, characterized by specifically including:

[0009] S1 obtains historical consumption data of different types of logistical materials of the target unit, and determines historical consumption fluctuation coefficients of different types of logistical materials and fluctuation types of logistical materials based on the historical consumption data, and determines safety margins of different logistical materials through the fluctuation types and historical consumption data;

[0010] S2 determines the shortage risk of different types of logistic materials based on the remaining quantity and safety margin of different types of logistic materials. When it is determined through the shortage risk of different types of logistic materials that the overall shortage risk of the logistic materials of the target unit does not meet the requirements, proceed to the next step;

[0011] S3 determines whether the fluctuation type of the logistics materials is a preset fluctuation type. If so, a mobilization strategy of the logistics materials of the preset fluctuation type is determined based on the historical consumption data and the remaining quantity of the logistics materials. If not, proceed to the next step.

[0012] S4 takes the storage space as a constraint condition and determines the optimal mobilization strategy based on the deviation between the remaining quantity of logistics materials with different fluctuation types after mobilization and the safety margin according to different mobilization strategies.

[0013] The beneficial effects of the present invention are:

[0014] 1. The safety margins of different logistical materials are determined by fluctuation types and historical consumption data, which avoids the technical problem of inaccurate safety margin assessment results caused by only considering the historical consumption data of logistical materials. It realizes accurate assessment of the safety margin of logistical materials from the perspective of the volatility of historical consumption data, and also lays the foundation for further ensuring the reliability of the supply of logistical materials.

[0015] 2. The optimal mobilization strategy is determined based on the deviation between the remaining quantity and the safety margin of logistical materials with different fluctuation types after mobilization under different mobilization strategies. It not only takes into account the difference in supply reliability caused by the deviation between the remaining quantity and the safety margin of logistical materials after mobilization, but also further considers the fluctuation type of logistical materials and fully considers the impact of different logistical materials on supply reliability due to differences in volatility, thus ensuring the reliability and accuracy of the mobilization strategy.

[0016] A further technical solution is that the historical consumption data of the logistical materials include the consumption of the logistical materials on different dates.

[0017] A further technical solution is that the method for determining the historical consumption fluctuation coefficient of the logistics materials is:

[0018] Determine the consumption of the logistics materials on different dates based on the historical consumption data, and determine the baseline consumption of the logistics materials based on the consumption of the logistics materials on different dates;

[0019] Dividing the dates into deviation consumption dates and consistent consumption dates based on the consumption of logistic materials on different dates and the deviation of the baseline consumption;

[0020] Determine the deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date based on the number of the deviation consumption dates and the consumption of different deviation consumption dates and the deviation of the benchmark consumption, the number of consistent consumption dates and the consumption of different consistent consumption dates and the deviation of the benchmark consumption, respectively;

[0021] The deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date are used to determine the historical consumption fluctuation coefficient of the logistics material.

[0022] A further technical solution is that the fluctuation type of the logistical materials is determined according to a preset fluctuation range corresponding to the historical consumption fluctuation coefficient of the logistical materials.

[0023] A further technical solution is that the safety margin of the logistical materials is determined according to the fluctuation type of the logistical materials, specifically, the safety margin of the logistical materials is determined according to the fluctuation type of the logistical materials and the preset safety margin corresponding to the fluctuation type.

[0024] A further technical solution is that the method for determining the optimal mobilization strategy is:

[0025] Determine the safety assessment values ​​of different fluctuation types of different mobilization strategies according to the quantity of logistic materials of different fluctuation types, the remaining quantity of different logistic materials of different fluctuation types after mobilization and the deviation amount of the safety margin;

[0026] The comprehensive safety evaluation values ​​of different mobilization strategies are determined by using the safety evaluation values ​​of different fluctuation types, and the optimal mobilization strategy is determined with the maximum comprehensive safety evaluation value as the goal.

[0027] In a second aspect, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-mentioned method for coordinated scheduling of logistics materials based on big data analysis.

[0028] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0031] Figure 1 It is a flow chart of a method for collaborative dispatching of logistics materials based on big data analysis;

[0032] Figure 2 It is a flow chart of the method for determining the fluctuation coefficient of historical consumption of logistic materials;

[0033] Figure 3 It is a flow chart of a method for determining a mobilization strategy for logistics materials of a preset fluctuation type. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0035] The following will further elaborate from two perspectives: method-based embodiments and system-based embodiments.

[0036] Method Example

[0037] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a method for coordinated dispatching of logistics materials based on big data analysis is provided, which is characterized by specifically including:

[0038] S1 obtains historical consumption data of different types of logistical materials of the target unit, and determines historical consumption fluctuation coefficients of different types of logistical materials and fluctuation types of logistical materials based on the historical consumption data, and determines safety margins of different logistical materials through the fluctuation types and historical consumption data;

[0039] Furthermore, the historical consumption data of the logistical materials include the consumption of the logistical materials on different dates.

[0040] Specifically, Figure 2 As shown, the method for determining the historical consumption fluctuation coefficient of the logistics materials is:

[0041] Determine the consumption of the logistics materials on different dates based on the historical consumption data, and determine the baseline consumption of the logistics materials based on the consumption of the logistics materials on different dates;

[0042] Dividing the dates into deviation consumption dates and consistent consumption dates based on the consumption of logistic materials on different dates and the deviation of the baseline consumption;

[0043] Determine the deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date based on the number of the deviation consumption dates and the consumption of different deviation consumption dates and the deviation of the benchmark consumption, the number of consistent consumption dates and the consumption of different consistent consumption dates and the deviation of the benchmark consumption, respectively;

[0044] The deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date are used to determine the historical consumption fluctuation coefficient of the logistics material.

[0045] Furthermore, the fluctuation type of the logistical materials is determined according to a preset fluctuation range corresponding to the historical consumption fluctuation coefficient of the logistical materials.

[0046] It should be noted that the safety margin of the logistical materials is determined according to the fluctuation type of the logistical materials, specifically, the safety margin of the logistical materials is determined according to the fluctuation type of the logistical materials and the preset safety margin corresponding to the fluctuation type.

[0047] In another embodiment, the method for determining the historical consumption fluctuation coefficient of the logistics materials is:

[0048] Determine the consumption of the logistic materials on different dates based on the historical consumption data, and determine the baseline consumption of the logistic materials based on the consumption of the logistic materials on different dates, determine the absolute value of the deviation according to the deviation between the consumption on different dates and the baseline consumption, and judge whether the sum of the absolute values ​​of the deviations on different dates meets the requirements, if so, proceed to the next step, if not, determine the fluctuation type of the logistic materials based on the preset fluctuation type;

[0049] According to the consumption of logistics materials on different dates and the deviation of the baseline consumption, the dates are divided into deviation consumption dates and consistent consumption dates, and it is determined whether the quantity of the deviation consumption date meets the requirements. If so, the next step is entered; if not, the fluctuation type of the logistics materials is determined based on the preset fluctuation type;

[0050] Obtain the consumption of different deviation consumption dates and the deviation of the baseline consumption, and determine the deviation coefficient of the deviation consumption date in combination with the quantity of the deviation consumption date, and judge whether the deviation coefficient of the deviation consumption date meets the requirements. If so, proceed to the next step; if not, determine the fluctuation type of the logistics materials based on the preset fluctuation type;

[0051] The deviation coefficient of the consistent consumption date is determined based on the number of the consistent consumption dates, the consumption of different consistent consumption dates, and the deviation of the benchmark consumption. The historical consumption fluctuation coefficient of the logistics materials is determined using the deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date.

[0052] In another embodiment, the method for determining the historical consumption fluctuation coefficient of the logistics materials is:

[0053] Determine the consumption of the logistics materials on different dates based on the historical consumption data, and determine the changes in consumption of different adjacent dates based on the consumption of the logistics materials on different dates, and judge whether the changes in consumption do not meet the requirements of the adjacent dates. If so, proceed to the next step; if not, determine the fluctuation type of the logistics materials based on the preset fluctuation type;

[0054] Determine the quantity of the change date according to the change of consumption on different adjacent dates, and determine the comprehensive change of the change date in combination with the change of consumption on different change dates, and judge whether the comprehensive change of the change date meets the requirements. If so, proceed to the next step; if not, determine the fluctuation type of the logistics materials based on the preset fluctuation type;

[0055] Determine the baseline consumption of the logistics materials according to the consumption of the logistics materials on different dates, and divide the dates into deviation consumption dates and consistent consumption dates according to the deviation of the consumption of the logistics materials on different dates and the baseline consumption;

[0056] Determine the deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date based on the number of the deviation consumption dates and the consumption of different deviation consumption dates and the deviation of the benchmark consumption, the number of consistent consumption dates and the consumption of different consistent consumption dates and the deviation of the benchmark consumption, respectively;

[0057] The historical consumption fluctuation coefficient of the logistics materials is determined by using the deviation coefficient of the deviation consumption date, the deviation coefficient of the consistent consumption date and the comprehensive change amount of the change date.

[0058] S2 determines the shortage risk of different types of logistic materials based on the remaining quantity and safety margin of different types of logistic materials. When it is determined through the shortage risk of different types of logistic materials that the overall shortage risk of the logistic materials of the target unit does not meet the requirements, proceed to the next step;

[0059] Furthermore, the method for determining the risk of shortage of logistic materials is:

[0060] The risk of shortage of the logistical materials is determined based on the remaining amount of the logistical materials and the ratio of the deviation amount of the safety margin to the safety margin.

[0061] Specifically, it is determined that the overall shortage risk of the target unit's logistics materials does not meet the requirements, including:

[0062] Different types of logistics materials are divided into different necessity intervals based on the historical consumption data of different types of logistics materials;

[0063] Determine the type and quantity of logistic materials of the target unit in different necessity intervals by using the shortage risks of different types of logistic materials, and determine the shortage risk assessment amount in different necessity intervals in combination with the shortage risks of different types of logistic materials in different necessity intervals;

[0064] The basic weight values ​​of different necessity intervals are determined by using the range intervals corresponding to different necessity intervals, and the overall shortage risk of the logistical materials of the target unit is determined in combination with the shortage risk assessment amounts of the different necessity intervals. The overall shortage risk of the logistical materials of the target unit is determined by presetting the shortage risk threshold to determine whether the requirement is met.

[0065] Furthermore, whether the overall shortage risk of the logistics materials of the target unit meets the requirements is determined by presetting the shortage risk threshold, specifically including:

[0066] When the overall shortage risk of the logistics materials of the target unit is less than the preset shortage risk threshold, it is determined that the overall shortage risk of the logistics materials of the target unit does not meet the requirements.

[0067] In another embodiment, determining that the overall shortage risk of logistics materials of the target unit does not meet the requirements specifically includes:

[0068] Determine whether there are logistic materials whose shortage risks do not meet the requirements based on the shortage risks of different types of logistic materials of the target unit, and if so, determine that the overall shortage risk of the logistic materials of the target unit does not meet the requirements, and if not, proceed to the next step;

[0069] Determine the logistic materials with critical shortage risk through the shortage risks of different types of logistic materials, and use them as critical risk logistic materials, and judge whether the type and quantity of the critical risk logistic materials meet the requirements. If so, proceed to the next step; if not, determine that the overall shortage risk of the logistic materials of the target unit does not meet the requirements;

[0070] Determine the basic shortage risk of the target unit's logistics materials based on the shortage risks of different critical risk logistics materials and the types and quantities of critical risk logistics materials, and judge whether the basic shortage risk of the target unit's logistics materials meets the requirements. If so, proceed to the next step; if not, determine that the overall shortage risk of the target unit's logistics materials does not meet the requirements;

[0071] Different types of logistical materials are divided into different necessity intervals based on historical consumption data of different types of logistical materials, and the type quantity and quantity ratio of the critical logistical materials of the target unit in different necessity intervals are determined according to the shortage risks of different types of logistical materials, and the shortage risk assessment amount in different necessity intervals is determined in combination with the shortage risks of different types of logistical materials in different necessity intervals;

[0072] The basic weight values ​​of different necessity intervals are determined by using the range intervals corresponding to different necessity intervals, and the overall shortage risk of the logistical materials of the target unit is determined in combination with the shortage risk assessment amounts of the different necessity intervals. The overall shortage risk of the logistical materials of the target unit is determined by presetting the shortage risk threshold to determine whether the requirement is met.

[0073] Furthermore, when the shortage risk of the logistical materials is within a preset risk range, the logistical materials are determined to be critical risk logistical materials.

[0074] In another embodiment, determining that the overall shortage risk of logistics materials of the target unit does not meet the requirements specifically includes:

[0075] Determine whether there are logistic materials whose shortage risks do not meet the requirements based on the shortage risks of different types of logistic materials of the target unit, and if so, determine that the overall shortage risk of the logistic materials of the target unit does not meet the requirements, and if not, proceed to the next step;

[0076] Determine the logistic materials with critical shortage risk through the shortage risk of different types of logistic materials, and use them as critical risk logistic materials. Classify different types of logistic materials into different necessity intervals based on their historical consumption data;

[0077] Determine the type and quantity of critical logistic materials of the target unit in different necessity intervals and the quantity ratio of the type and quantity through the shortage risks of different types of logistic materials in different necessity intervals, and determine the shortage risk assessment amount in different necessity intervals in combination with the shortage risks of different types of logistic materials in different necessity intervals, and judge whether the shortage risk assessment amount of the preset necessity interval meets the requirements, if so, proceed to the next step, if not, determine that the overall shortage risk of the logistic materials of the target unit does not meet the requirements;

[0078] The basic weight values ​​of different necessity intervals are determined by using the range intervals corresponding to different necessity intervals, and the overall shortage risk of the logistical materials of the target unit is determined in combination with the shortage risk assessment amounts of the different necessity intervals. The overall shortage risk of the logistical materials of the target unit is determined by presetting the shortage risk threshold to determine whether the requirement is met.

[0079] S3 determines whether the fluctuation type of the logistics materials is a preset fluctuation type. If so, a mobilization strategy of the logistics materials of the preset fluctuation type is determined based on the historical consumption data and the remaining quantity of the logistics materials. If not, proceed to the next step.

[0080] It should be noted that if Figure 3 As shown, the method for determining the mobilization strategy of the logistics materials of the preset fluctuation type is:

[0081] Based on the historical consumption data and the remaining quantity of the logistics materials of the preset fluctuation type, the deviation between the remaining quantity of the logistics materials of the preset fluctuation type and the historical consumption quantity on different dates is determined, and the deviation date is determined according to the material deviation quantity;

[0082] The number of deviation dates and the material deviation amounts of different deviation dates are used to determine the mobilization threshold of the logistics materials of the preset fluctuation type, and the mobilization strategy of the logistics materials of the preset fluctuation type is determined by the mobilization threshold.

[0083] Furthermore, the deviation date and the sufficient date are determined according to the material deviation amount, specifically including:

[0084] When the material deviation amount of the date is not within the preset deviation range, it is determined that the date is a deviation date; when the material deviation amount of the date is within the preset deviation range, it is determined that the date is a sufficient date.

[0085] In another embodiment, the method for determining the mobilization strategy of the logistics materials of the preset fluctuation type is:

[0086] S31 determines the deviation between the remaining quantity of the logistics materials of the preset fluctuation type and the historical consumption quantity on different dates based on the historical consumption data and remaining quantity of the logistics materials of the preset fluctuation type, and uses it as the material deviation quantity, and determines whether there is a date when the material deviation quantity is greater than the preset deviation threshold value, if yes, proceeds to the next step, if no, proceeds to step S34;

[0087] S32 takes the date when the material deviation amount is greater than the preset deviation threshold as the screening deviation date, and determines whether the number of the screening deviation dates is greater than the preset number of dates. If so, the mobilization strategy of the logistics materials of the preset fluctuation type is determined based on the average value of the material deviation amount of the screening deviation date. If not, proceed to the next step;

[0088] S33 obtains the number and proportion of the screening deviation dates, and determines the comprehensive deviation of the screening deviation date in combination with the material deviations of different screening deviation dates, and judges whether the comprehensive deviation of the screening deviation date meets the requirements. If so, proceeds to the next step; if not, determines the mobilization strategy of the logistics materials of the preset fluctuation type based on the average value of the material deviations of the screening deviation dates;

[0089] S34 determines the deviation date according to the material deviation amount, and judges whether the number of the deviation date is less than the preset date number. If not, proceed to the next step. If so, determine the mobilization strategy of the logistics materials of the preset fluctuation type based on the preset deviation amount.

[0090] S35 determines the mobilization quantity threshold of the logistics materials of the preset fluctuation type by using the number of the deviation dates and the material deviation quantities of different deviation dates, and determines the mobilization strategy of the logistics materials of the preset fluctuation type by using the mobilization quantity threshold.

[0091] S4 takes the storage space as a constraint condition and determines the optimal mobilization strategy based on the deviation between the remaining quantity of logistics materials with different fluctuation types after mobilization and the safety margin according to different mobilization strategies.

[0092] It should be noted that the method for determining the optimal mobilization strategy is:

[0093] Determine the safety assessment values ​​of different fluctuation types of different mobilization strategies according to the quantity of logistic materials of different fluctuation types, the remaining quantity of different logistic materials of different fluctuation types after mobilization and the deviation amount of the safety margin;

[0094] The comprehensive safety evaluation values ​​of different mobilization strategies are determined by using the safety evaluation values ​​of different fluctuation types, and the optimal mobilization strategy is determined with the maximum comprehensive safety evaluation value as the goal.

[0095] System Example

[0096] In a second aspect, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes the above-mentioned method for coordinated scheduling of logistics materials based on big data analysis.

[0097] Through the above embodiments, the present invention achieves the following beneficial effects:

[0098] 1. The safety margins of different logistical materials are determined by fluctuation types and historical consumption data, which avoids the technical problem of inaccurate safety margin assessment results caused by only considering the historical consumption data of logistical materials. It realizes accurate assessment of the safety margin of logistical materials from the perspective of the volatility of historical consumption data, and also lays the foundation for further ensuring the reliability of the supply of logistical materials.

[0099] 2. The optimal mobilization strategy is determined based on the deviation between the remaining quantity and the safety margin of logistical materials with different fluctuation types after mobilization under different mobilization strategies. It not only takes into account the difference in supply reliability caused by the deviation between the remaining quantity and the safety margin of logistical materials after mobilization, but also further considers the fluctuation type of logistical materials and fully considers the impact of different logistical materials on supply reliability due to differences in volatility, thus ensuring the reliability and accuracy of the mobilization strategy.

[0100] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0101] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0102] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for coordinated dispatching of logistics materials based on big data analysis, characterized in that: Specifically include: Acquire historical consumption data of different types of logistical materials of the target unit, and determine historical consumption fluctuation coefficients of different types of logistical materials and fluctuation types of logistical materials based on the historical consumption data, and determine safety margins of different logistical materials through the fluctuation types and historical consumption data; Determine the shortage risk of different types of logistic materials based on the remaining quantity and safety margin of different types of logistic materials. When it is determined through the shortage risk of different types of logistic materials that the overall shortage risk of the logistic materials of the target unit does not meet the requirements, proceed to the next step; Determine whether the fluctuation type of the logistics materials is a preset fluctuation type. If so, determine the mobilization strategy of the logistics materials of the preset fluctuation type based on the historical consumption data and the remaining quantity of the logistics materials. If not, proceed to the next step. Taking storage space as a constraint, determining the optimal mobilization strategy based on the deviation between the remaining quantity of logistics materials after mobilization and the safety margin of different fluctuation types under different mobilization strategies; The method for determining the historical consumption fluctuation coefficient of the logistics materials is as follows: Determine the consumption of the logistics materials on different dates based on the historical consumption data, and determine the baseline consumption of the logistics materials based on the consumption of the logistics materials on different dates; Dividing the dates into deviation consumption dates and consistent consumption dates based on the consumption of logistic materials on different dates and the deviation of the baseline consumption; Determine the deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date based on the number of the deviation consumption dates and the consumption of different deviation consumption dates and the deviation of the benchmark consumption, the number of consistent consumption dates and the consumption of different consistent consumption dates and the deviation of the benchmark consumption, respectively; Determine the historical consumption fluctuation coefficient of the logistics materials by using the deviation coefficient of the deviation consumption date and the deviation coefficient of the consistent consumption date; The safety margin of the logistical materials is determined according to the fluctuation type of the logistical materials, specifically according to the fluctuation type of the logistical materials and the preset safety margin corresponding to the fluctuation type. It is determined that the overall shortage risk of the target unit's logistics materials does not meet the requirements, including: Different types of logistics materials are divided into different necessity intervals based on the historical consumption data of different types of logistics materials; Determine the type and quantity of logistic materials of the target unit in different necessity intervals by using the shortage risks of different types of logistic materials, and determine the shortage risk assessment amount in different necessity intervals in combination with the shortage risks of different types of logistic materials in different necessity intervals; Determine the basic weight values ​​of different necessity intervals by using the range intervals corresponding to different necessity intervals, and determine the overall shortage risk of the logistics materials of the target unit in combination with the shortage risk assessment amounts of the different necessity intervals, and determine whether the overall shortage risk of the logistics materials of the target unit meets the requirements by presetting the shortage risk threshold; The preset shortage risk threshold is used to determine whether the overall shortage risk of the target unit's logistics materials meets the requirements, including: When the overall shortage risk of the logistics materials of the target unit is less than the preset shortage risk threshold, it is determined that the overall shortage risk of the logistics materials of the target unit does not meet the requirement; The method for determining the mobilization strategy of the logistics materials of the preset fluctuation type is: Based on the historical consumption data and the remaining quantity of the logistics materials of the preset fluctuation type, the deviation between the remaining quantity of the logistics materials of the preset fluctuation type and the historical consumption quantity on different dates is determined, and the deviation date is determined according to the material deviation quantity; The number of deviation dates and the material deviation amounts of different deviation dates are used to determine the mobilization threshold of the logistics materials of the preset fluctuation type, and the mobilization strategy of the logistics materials of the preset fluctuation type is determined by the mobilization threshold.

2. The method for coordinated dispatching of logistics materials based on big data analysis according to claim 1, characterized in that: The historical consumption data of the logistics materials include the consumption of the logistics materials on different dates.

3. The method for coordinated dispatching of logistics materials based on big data analysis according to claim 1, characterized in that: The fluctuation type of the logistical materials is determined according to a preset fluctuation range corresponding to the historical consumption fluctuation coefficient of the logistical materials.

4. The method for coordinated dispatching of logistics materials based on big data analysis according to claim 1, characterized in that: The method for determining the risk of shortage of logistic materials is as follows: The risk of shortage of the logistical materials is determined based on the remaining amount of the logistical materials and the ratio of the deviation amount of the safety margin to the safety margin.

5. A computer system comprising: A memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, characterized in that: when the processor runs the computer program, it executes a method for coordinated scheduling of logistics materials based on big data analysis as described in any one of claims 1-4.

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