A supply and demand balance management system and method based on big data

Abstract

The present invention discloses a supply and demand balance management system and method based on big data, which belongs to the field of scheduling management technology. The system includes a data acquisition module, a data processing module, a capacity scheduling module and a notification and warning module; the data acquisition module is used to collect meteorological information, sales information and capacity information of all sales areas; the data processing module predicts the sales speed of each sales area by analyzing the meteorological information and sales information of each sales area, and plans the sales plan according to the prediction results; the capacity scheduling module adjusts the capacity and dispatches goods according to the sales plan, and the capacity adjustment refers to adjusting the production speed of the total production end according to the predicted sales speed, and the goods dispatch refers to dispatching the goods that cannot be sold within the specified time to other sales areas; the notification and warning module is used to perform warning operations on abnormal conditions of goods and promptly remind staff to handle them.

Description

Technical Field

[0001] The present invention relates to the technical field of scheduling management, and in particular to a supply and demand balance management system and method based on big data. Background Art

[0002] With the rapid development of e-commerce, express delivery and other industries, as well as the increasing demand for logistics, the traditional single large warehouse storage method can no longer meet the requirements of modern logistics. Therefore, distributed warehouses, as a new type of storage method, have gradually attracted widespread attention by establishing multiple small warehouses across the country to achieve efficient cargo management.

[0003] Compared with traditional single large warehouses, distributed warehouses have more flexible layouts, richer service types and more efficient operation modes. They can better adapt to the development trend of urbanization and express delivery business, reduce transportation time and optimize logistics costs. But at the same time, distributed warehouses also face some problems in the operation and management process. For example, when the goods are cooling goods such as air conditioners, cold drinks or fans, their sales speed is greatly affected by temperature. The shipping speed of warehouses in different places may be inconsistent due to temperature differences in different places. Warehouses in high temperature areas have fast shipping speeds, while warehouses in low temperature areas have slow shipping speeds. Or due to misjudgment of the sales environment and other reasons, some warehouses have a large inventory of goods, while some warehouses have a small inventory of goods. These problems will lead to an imbalance in the supply and demand of warehouses at each node. How to adjust the production capacity of the production end according to the different sales environments in different places, how to dispatch goods between warehouses at each node according to the inventory and sales environment of different warehouses, to ensure dynamic adjustments between warehouses at different nodes, and the balance of supply and demand of the entire distributed warehouse, these problems have become urgent problems that need to be solved. Summary of the invention

[0004] The purpose of the present invention is to provide a supply and demand balance management system and method based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a supply and demand balance management system based on big data, which includes a data acquisition module, a data processing module, a production capacity scheduling module and a notification and warning module.

[0006] The data acquisition module is used to collect meteorological information, sales information and production capacity information of all sales areas; the data processing module predicts the sales speed of each sales area by analyzing the meteorological information and production capacity information of each sales area, and plans the sales plan according to the prediction results; the production capacity scheduling module is used to adjust the production speed of the total production end according to the sales plan, and schedule goods in different sales areas; the notification and warning module is used to issue warning operations for backlogs or shortages of goods, and remind staff to handle them.

[0007] The data collection module includes a meteorological information collection unit, a sales information collection unit and a production capacity information collection unit.

[0008] The meteorological information collection unit is used to collect meteorological information of all sales areas, and the meteorological information of each sales area includes historical temperature and future temperature.

[0009] The sales information collection unit is used to collect sales data of all sales areas, and the sales data of each sales area includes historical sales speed.

[0010] The historical temperature and historical sales speed are collected from the records kept by the system, and the future temperature is collected from the weather forecast issued by the Meteorological Bureau.

[0011] The capacity information collection unit is used to collect capacity information of all sales areas, and the capacity information includes production speed, sales cycle and inventory of each sales area.

[0012] Production speed refers to the speed at which goods are produced by the production end. One production end supplies goods to all sales areas. Sales cycle refers to the optimal sales period for goods. Production capacity planning and goods scheduling are carried out according to the completion of goods sales within the sales cycle. Inventory refers to the amount of goods stored in each sales area. The amount of goods stored in different sales areas is different.

[0013] The data processing module includes a sales speed prediction unit and a sales plan planning unit.

[0014] The sales speed prediction unit is used to calculate the predicted sales speed of each sales area. First, the historical temperature and historical sales speed of each sales area are obtained, and these data are preprocessed to remove abnormal values ​​and extreme values; secondly, the temperature and sales speed in the same time period are associated, and the associated data in each sales area are respectively fitted by a logarithmic function to obtain a relationship formula between temperature and sales speed, and each sales area corresponds to a relationship formula; finally, the future temperature of each sales area is substituted into the corresponding relationship formula to calculate the predicted sales speed of each sales area.

[0015] The sales plan planning unit is used to plan the production speed adjustment direction and the goods dispatch direction. Substitute the predicted sales speed and inventory of each sales area into the formula to calculate the total expected sales time and the expected sales time corresponding to each sales area, and compare and judge with the sales cycle respectively to obtain the production speed adjustment direction and the goods dispatch direction of each sales area. The production speed adjustment direction includes expanding production capacity, reducing production capacity and keeping unchanged; the goods dispatch direction of each sales area includes transferring in, transferring out and maintaining the status quo.

[0016] The best case scenario is the total forecast Equal to the sales cycle, ensure that the goods produced are sold just within the sales cycle, the goods are effectively circulated, and there will be no inventory backlog or shortage. Of course, the sales speed always changes with temperature changes, and the production speed also needs to change accordingly. When the total expected sales time is greater than the sales cycle, it means that the sales speed is too slow, and the production speed needs to be reduced to prevent inventory backlog. When the total expected sales time is less than the sales cycle, it means that the sales speed is too fast, and the production speed needs to be increased to prevent the shortage of goods.

[0017] The estimated sales time corresponding to each sales area must also be equal to the sales cycle. When the estimated sales time is greater than the sales cycle, it means that the sales speed is too slow and the goods need to be transferred to other sales areas to prevent inventory backlogs. When the estimated sales time is less than the sales cycle, it means that the sales speed is too fast and the goods need to be transferred from other sales areas to prevent the loss of goods.

[0018] The capacity scheduling module includes a capacity adjustment unit and a cargo scheduling unit.

[0019] The capacity adjustment unit is used to adjust the production speed of the total production end. When the production speed adjustment direction is to expand or reduce the production capacity, the sum of the predicted sales speeds of each sales area and the sum of the inventory are substituted into the formula to calculate the adjusted production speed, and the production speed of the production end is adjusted according to the adjusted production speed.

[0020] The goods dispatching unit is used to dispatch the inventory goods of each sales area. When the goods dispatching direction of the sales area is transfer-in or transfer-out, the predicted sales speed and inventory of each sales area are respectively substituted into the formula to calculate the shortage inventory or excess inventory, and the goods in the sales area with the goods dispatching direction of transfer-out are transferred to the sales area with the goods dispatching direction of transfer-in.

[0021] The notification warning module is used for warning operations.

[0022] First, sum up the shortage inventory of all sales areas to get the total shortage inventory, and sum up the excess inventory of all sales areas to get the total excess inventory. Second, subtract the total shortage inventory from the total excess inventory to get the inventory difference. Finally, determine whether the inventory difference is within the inventory threshold interval. If it is, it is normal and no warning operation is performed. If it is not, determine whether the inventory difference is greater than the maximum value of the inventory threshold interval or less than the minimum value of the inventory threshold interval. If it is greater than the maximum value of the inventory threshold interval, a goods backlog warning is issued; if it is less than the minimum value of the inventory threshold interval, a goods missing warning is issued.

[0023] A supply and demand balance management method based on big data, the method comprising the following steps:

[0024] S1. Collect production capacity information, as well as weather information and sales information for each sales area;

[0025] S2. Predict sales speed based on weather information in each sales area and formulate sales plans;

[0026] S3. Adjust production speed and dispatch inventory through sales plan;

[0027] S4. Perform early warning operations in abnormal situations to remind staff to handle them.

[0028] In S1, the capacity information includes the production speed, sales cycle and inventory of each sales area. The meteorological information refers to the temperature information in the sales area, including the historical temperature and future temperature; the sales information refers to the sales speed of the sales area, including the historical sales speed.

[0029] Production speed refers to the speed at which goods are produced at the production end; sales cycle refers to the optimal sales period for goods; inventory refers to the quantity of goods stored in each sales area. Historical temperature and historical sales speed are collected from records saved by the system; future temperature is collected from weather forecasts issued by the Meteorological Bureau.

[0030] In S2, the steps for predicting sales velocity and formulating sales plans are as follows:

[0031] S201. Obtain the historical temperature and historical sales speed of each sales area, pre-process the data, and remove abnormal values ​​and extreme values.

[0032] S202: Associating the temperature and sales speed in the same time period in each sales area to ensure that there is only one pair of associated data in each time period.

[0033] S203, respectively fitting the associated data in each sales area by means of a logarithmic function to obtain a relationship formula between temperature and sales speed, wherein each sales area corresponds to one relationship formula.

[0034] S204. Substitute the future temperature of each sales area into the corresponding relationship formula to calculate the predicted sales speed of each sales area. The calculation formula is as follows:

[0035] ;

[0036] Where Y ’ To predict sales speed, season is the seasonal influence coefficient, speed is the sales speed constant, a is the temperature influence coefficient, which is greater than 1, and x is the future temperature.

[0037] S205. Divide the inventory of each sales area by the predicted sales speed to obtain the estimated sales time, mark the sales area whose estimated sales time is less than the sales cycle as the sales area to be transferred in, and mark the sales area whose estimated sales time is greater than the sales cycle as the sales area to be transferred out.

[0038] S206: Put the inventory and predicted sales speed of each sales area into a sales volume set respectively. The sales volume set includes , where n represents the number of sales regions, represents the inventory quantity of the nth sales region, is the predicted sales speed of the nth sales region. The inventory and predicted sales speed of all sales regions are summed up, and the calculation formula is as follows:

[0039] ;

[0040] ;

[0041] In the formula, K is the total inventory and Y is the total predicted sales speed. Divide the total inventory by the total predicted sales speed to get the total estimated sales time, and substitute it into the formula to determine the direction of capacity adjustment. The judgment formula is as follows:

[0042] ;

[0043] In the formula, result is the capacity adjustment direction, and T is the sales cycle.

[0044] In S3, the production speed adjustment and inventory scheduling steps are as follows:

[0045] S301. When the capacity adjustment direction is to remain unchanged, the production speed does not change. When the capacity adjustment direction is to expand or reduce capacity, substitute the sales volume set into the formula to calculate the adjusted production speed. The formula is as follows:

[0046] ;

[0047] Where CN is the adjusted production speed, CS is the production speed, K is the total inventory, Y is the total predicted sales speed, and T is the sales cycle.

[0048] S302: multiply the predicted sales speed of the sales area marked as to be transferred by the sales cycle, subtract the inventory of the corresponding sales area from the calculated value, and put the obtained shortage inventory into the shortage inventory set in descending order. , where m represents the number of sales areas to be transferred. Indicates the shortage inventory quantity to be transferred to the mth sales area.

[0049] S303, multiply the predicted sales speed of the sales area marked as to be transferred out by the sales cycle, and then subtract the calculated value from the inventory of the corresponding sales area, and put the obtained excess inventory into the excess inventory set in descending order, including , where p represents the number of sales areas to be transferred out. Represents the excess inventory in the pth sales area to be transferred out.

[0050] S304. Sum all elements in the shortage inventory set to obtain the total shortage inventory, and sum all elements in the surplus inventory set to obtain the total surplus inventory. The formula is as follows:

[0051] ;

[0052] ;

[0053] In the formula, is the total shortage inventory, and S is the total excess inventory. The total excess inventory minus the total shortage inventory gets the inventory difference, and it is determined whether the inventory difference is within the inventory threshold range. If it is, it is a normal situation, and if it is not, it is an abnormal situation. The judgment formula is as follows:

[0054] ;

[0055] In the formula, For inventory status, is the maximum value of the inventory threshold interval, The minimum value of the inventory threshold interval.

[0056] S305. The priority of the sales area to be transferred is set in descending order of the shortage inventory in the shortage inventory set. The larger the shortage inventory, the higher the priority of the corresponding sales area to be transferred. Goods are transferred to the sales area to be transferred in order of priority. The calculation formula for the transferred inventory is as follows:

[0057] ;

[0058] In the formula, is the actual inventory quantity transferred into the fth sales area to be transferred, is the shortage inventory to be transferred to the fth sales area, is the total shortage inventory, and S is the total excess inventory.

[0059] In S4, an abnormal situation refers to when the inventory situation is an inventory backlog or inventory shortage, and an early warning operation is performed for this situation to remind the staff to handle it.

[0060] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0061] The present invention predicts the demand of each sales area locally, transfers goods to the sales area with overstock, and transfers goods to the sales area with insufficient inventory, so as to realize dynamic adjustment between the sales areas. The demand for goods is predicted as a whole, and the production capacity is expanded or reduced in advance to ensure the balance between supply and demand between production and sales, and avoid the accumulation or shortage of a large amount of goods. At the same time, the inventory difference between the total excess inventory and the total shortage inventory is calculated to determine the degree of impact. When the degree of impact is large, an early warning is automatically issued to remind the staff to intervene manually. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0063] Figure 1 It is a structural schematic diagram of a supply and demand balance management system based on big data of the present invention;

[0064] Figure 2 It is a flow chart of a supply and demand balancing management method based on big data of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] See also Figure 1 The present invention provides a supply and demand balance management system based on big data, which includes a data acquisition module, a data processing module, a production capacity scheduling module and a notification and warning module.

[0067] The data collection module is used to collect weather information, sales information and production capacity information of all sales areas; the data processing module predicts the sales speed of each sales area by analyzing the weather information and production capacity information of each sales area, and plans the sales plan according to the prediction results; the production capacity scheduling module is used to adjust the production speed of the total production end according to the sales plan, and schedule goods in different sales areas; the notification and warning module is used to issue warning operations for backlogs or shortages of goods, and remind staff to deal with them.

[0068] The data collection module includes a meteorological information collection unit, a sales information collection unit and a production capacity information collection unit.

[0069] The meteorological information collection unit is used to collect meteorological information of all sales areas. The meteorological information of each sales area includes historical temperature and future temperature.

[0070] The sales information collection unit is used to collect sales data of all sales areas, and the sales data of each sales area includes historical sales speed.

[0071] The historical temperature and historical sales speed are collected from the records kept by the system, and the future temperature is collected from the weather forecast issued by the Meteorological Bureau.

[0072] The capacity information collection unit is used to collect the capacity information of all sales areas. The capacity information includes production speed, sales cycle and inventory of each sales area.

[0073] Production speed refers to the speed at which goods are produced by the production end. One production end supplies goods to all sales areas. Sales cycle refers to the optimal sales period for goods. Production capacity planning and goods scheduling are carried out according to the completion of goods sales within the sales cycle. Inventory refers to the amount of goods stored in each sales area. The amount of goods stored in different sales areas is different.

[0074] The data processing module includes a sales speed prediction unit and a sales plan planning unit.

[0075] The sales speed prediction unit is used to calculate the predicted sales speed of each sales area. First, the historical temperature and historical sales speed of each sales area are obtained, and these data are preprocessed to remove outliers and extreme values; secondly, the temperature and sales speed in the same time period are associated, and the associated data in each sales area are fitted using a logarithmic function to obtain the relationship formula between temperature and sales speed, and each sales area corresponds to a relationship formula; finally, the future temperature of each sales area is substituted into the corresponding relationship formula to calculate the predicted sales speed of each sales area.

[0076] The sales plan planning unit is used to plan the production speed adjustment direction and the goods dispatch direction. Substitute the predicted sales speed and inventory of each sales area into the formula to calculate the total expected sales time and the expected sales time corresponding to each sales area, and compare and judge with the sales cycle to obtain the production speed adjustment direction and the goods dispatch direction of each sales area. The production speed adjustment direction includes expanding production capacity, reducing production capacity and keeping unchanged; the goods dispatch direction of each sales area includes transferring in, transferring out and maintaining the status quo.

[0077] The best case scenario is that the total estimated sales time is equal to the sales cycle, ensuring that the goods produced are sold just within the sales cycle, the goods are effectively circulated, and there will be no inventory backlog or shortage. Of course, the sales speed always changes with temperature changes, and the production speed also needs to change accordingly. When the total estimated sales time is greater than the sales cycle, it means that the sales speed is too slow, and the production speed needs to be reduced to prevent inventory backlogs. When the total estimated sales time is less than the sales cycle, it means that the sales speed is too fast, and the production speed needs to be increased to prevent the shortage of goods.

[0078] The estimated sales time corresponding to each sales area must also be equal to the sales cycle. When the estimated sales time is greater than the sales cycle, it means that the sales speed is too slow and the goods need to be transferred to other sales areas to prevent inventory backlogs. When the estimated sales time is less than the sales cycle, it means that the sales speed is too fast and the goods need to be transferred from other sales areas to prevent the loss of goods.

[0079] The capacity scheduling module includes a capacity adjustment unit and a cargo scheduling unit.

[0080] The capacity adjustment unit is used to adjust the production speed of the total production end. When the production speed adjustment direction is to expand or reduce the production capacity, the sum of the predicted sales speed of each sales area and the sum of the inventory are substituted into the formula to calculate the adjusted production speed, and the production speed of the production end is adjusted according to the adjusted production speed.

[0081] The cargo dispatching unit is used to dispatch the inventory of each sales area. When the cargo dispatching direction of a sales area is transfer-in or transfer-out, the predicted sales speed and inventory of each sales area are respectively substituted into the formula to calculate the shortage inventory or excess inventory, and the cargo in the sales area with the cargo dispatching direction of transfer-out is transferred to the sales area with the cargo dispatching direction of transfer-in.

[0082] The notification warning module is used for warning operations.

[0083] First, sum up the shortage inventory of all sales areas to get the total shortage inventory, and sum up the excess inventory of all sales areas to get the total excess inventory. Second, subtract the total shortage inventory from the total excess inventory to get the inventory difference. Finally, determine whether the inventory difference is within the inventory threshold interval. If it is, it is normal and no warning operation is performed. If it is not, determine whether the inventory difference is greater than the maximum value of the inventory threshold interval or less than the minimum value of the inventory threshold interval. If it is greater than the maximum value of the inventory threshold interval, a goods backlog warning is issued; if it is less than the minimum value of the inventory threshold interval, a goods missing warning is issued.

[0084] See also Figure 2 The present invention provides a supply and demand balance management method based on big data, which comprises the following steps:

[0085] S1. Collect production capacity information, as well as weather information and sales information for each sales area;

[0086] S2. Predict sales speed based on weather information in each sales area and formulate sales plans;

[0087] S3. Adjust production speed and dispatch inventory through sales plan;

[0088] S4. Perform early warning operations in abnormal situations to remind staff to handle them.

[0089] In S1, the capacity information includes the production speed, sales cycle and inventory of each sales area. The meteorological information refers to the temperature information in the sales area, including the historical temperature and future temperature; the sales information refers to the sales speed of the sales area, including the historical sales speed.

[0090] Production speed refers to the speed at which goods are produced at the production end; sales cycle refers to the optimal sales period for goods; inventory refers to the quantity of goods stored in each sales area. Historical temperature and historical sales speed are collected from records saved by the system; future temperature is collected from weather forecasts issued by the Meteorological Bureau.

[0091] In S2, the steps for predicting sales velocity and formulating sales plans are as follows:

[0092] S201. Obtain the historical temperature and historical sales speed of each sales area, pre-process the data, and remove abnormal values ​​and extreme values.

[0093] S202: Associating the temperature and sales speed in the same time period in each sales area to ensure that there is only one pair of associated data in each time period.

[0094] S203, respectively fitting the associated data in each sales area by means of a logarithmic function to obtain a relationship formula between temperature and sales speed, wherein each sales area corresponds to one relationship formula.

[0095] S204. Substitute the future temperature of each sales area into the corresponding relationship formula to calculate the predicted sales speed of each sales area. The calculation formula is as follows:

[0096] ;

[0097] Where Y ’ To predict sales speed, season is the seasonal influence coefficient, speed is the sales speed constant, a is the temperature influence coefficient, which is greater than 1, and x is the future temperature.

[0098] S205. Divide the inventory of each sales area by the predicted sales speed to obtain the estimated sales time, mark the sales area whose estimated sales time is less than the sales cycle as the sales area to be transferred in, and mark the sales area whose estimated sales time is greater than the sales cycle as the sales area to be transferred out.

[0099] S206: Put the inventory and predicted sales speed of each sales area into a sales volume set respectively. The sales volume set includes , where n represents the number of sales regions, represents the inventory quantity of the nth sales region, is the predicted sales speed of the nth sales region. The inventory and predicted sales speed of all sales regions are summed up, and the calculation formula is as follows:

[0100] ;

[0101] ;

[0102] In the formula, K is the total inventory and Y is the total predicted sales speed. Divide the total inventory by the total predicted sales speed to get the total estimated sales time, and substitute it into the formula to determine the direction of capacity adjustment. The judgment formula is as follows:

[0103] ;

[0104] In the formula, result is the capacity adjustment direction, and T is the sales cycle.

[0105] In S3, the production speed adjustment and inventory scheduling steps are as follows:

[0106] S301. When the capacity adjustment direction is to remain unchanged, the production speed does not change. When the capacity adjustment direction is to expand or reduce capacity, substitute the sales volume set into the formula to calculate the adjusted production speed. The formula is as follows:

[0107]

[0108] Where CN is the adjusted production speed, CS is the production speed, K is the total inventory, Y is the total predicted sales speed, and T is the sales cycle.

[0109] S302: multiply the predicted sales speed of the sales area marked as to be transferred by the sales cycle, subtract the inventory of the corresponding sales area from the calculated value, and put the obtained shortage inventory into the shortage inventory set in descending order. , where m represents the number of sales areas to be transferred. Indicates the shortage inventory quantity to be transferred to the mth sales area.

[0110] S303, multiply the predicted sales speed of the sales area marked as to be transferred out by the sales cycle, and then subtract the calculated value from the inventory of the corresponding sales area, and put the obtained excess inventory into the excess inventory set in descending order, including , where p represents the number of sales areas to be transferred out. Represents the excess inventory in the pth sales area to be transferred out.

[0111] S304. Sum all elements in the shortage inventory set to obtain the total shortage inventory, and sum all elements in the surplus inventory set to obtain the total surplus inventory. The formula is as follows:

[0112] ;

[0113] ;

[0114] In the formula, is the total shortage inventory, and S is the total excess inventory. The total excess inventory minus the total shortage inventory gets the inventory difference, and it is determined whether the inventory difference is within the inventory threshold range. If it is, it is a normal situation, and if it is not, it is an abnormal situation. The judgment formula is as follows:

[0115] ;

[0116] In the formula, For inventory status, is the maximum value of the inventory threshold interval, The minimum value of the inventory threshold interval.

[0117] S305. The priority of the sales area to be transferred is set in descending order of the shortage inventory in the shortage inventory set. The larger the shortage inventory, the higher the priority of the corresponding sales area to be transferred. Goods are transferred to the sales area to be transferred in order of priority. The calculation formula for the transferred inventory is as follows:

[0118] ;

[0119] In the formula, is the actual inventory quantity transferred into the fth sales area to be transferred, is the shortage inventory to be transferred to the fth sales area, is the total shortage inventory, and S is the total excess inventory.

[0120] In S4, an abnormal situation refers to when the inventory situation is an inventory backlog or inventory shortage, and an early warning operation is performed for this situation to remind the staff to handle it. Example

[0121] Assume that there are three sales areas, A, B and C, and the future temperatures are 26°C, 32°C and 35°C respectively, the seasonal influence coefficients are all 1.2, the sales speed constant is 100, and the temperature influence coefficients are 1.2, 1.3 and 1.4 respectively. The predicted sales speed is:

[0122] A: Servings / day;

[0123] B: Servings / day;

[0124] C: Servings / day;

[0125] Assuming the sales cycle is 1 day, the inventory in sales areas A, B and C is 2644, 1585 and 868 copies respectively, then the estimated sales time is:

[0126] A: , B: , C: ;

[0127] A is marked as the sales area to be transferred out, and C is marked as the sales area to be transferred in. Sum the inventory of A, B, and C with the predicted sales speed, and put them into the formula to determine the direction of capacity adjustment.

[0128] ;

[0129] The direction of capacity adjustment is: reducing capacity; assuming the production speed is 5097 pieces / day, continue to substitute the formula to calculate the adjusted production speed:

[0130]

[0131] Calculate the excess inventory of A and the shortage inventory of C respectively:

[0132] A: , C: ;

[0133] Assume that the inventory threshold interval is [-50, +50], and the inventory situation is:

[0134] Inventory backlog: In this case, the inventory quantity transferred from sales area A to sales area C is 400 pieces, and an early warning operation is carried out at the same time to remind the staff to handle it.

[0135] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0136] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A supply and demand balance management method based on big data, characterized in that: The method comprises the following steps: S1. Collect production capacity information, as well as weather information and sales information for each sales area; S2. Predict sales speed based on weather information in each sales area and formulate sales plans; S3. Adjust production speed and dispatch inventory through sales plan; S4. Perform early warning operations in abnormal situations to remind staff to handle; In S2, the steps for predicting sales velocity and formulating sales plans are as follows: S201, obtaining the historical temperature and historical sales speed of each sales area, preprocessing the data, and removing abnormal values ​​and extreme values; S202, associating the temperature and sales speed in the same time period in each sales area, ensuring that there is only one pair of associated data in each time period; S203, respectively fitting the associated data in each sales area by means of a logarithmic function to obtain a relationship formula between temperature and sales speed, wherein each sales area corresponds to a relationship formula; S204. Substitute the future temperature of each sales area into the corresponding relationship formula to calculate the predicted sales speed of each sales area. The calculation formula is as follows: ； Where Y ’ To predict sales speed, season is the seasonal influence coefficient, speed is the sales speed constant, a is the temperature influence coefficient, and x is the future temperature; S205, respectively divide the inventory of each sales area by the predicted sales speed to obtain the estimated sales time, mark the sales area whose estimated sales time is less than the sales cycle as the sales area to be transferred in, and mark the sales area whose estimated sales time is greater than the sales cycle as the sales area to be transferred out; S206: Put the inventory and predicted sales speed of each sales area into a sales volume set respectively. The sales volume set includes , where n represents the number of sales regions, represents the inventory quantity of the nth sales region, is the predicted sales speed of the nth sales region; the inventory and predicted sales speed of all sales regions are summed up, and the calculation formula is as follows: ； ； Where K is the total inventory, Y is the total predicted sales speed, and the total inventory is divided by the total predicted sales speed to get the total estimated sales time. Substitute it into the formula to determine the direction of capacity adjustment; the judgment formula is as follows: ； In the formula, result is the capacity adjustment direction, and T is the sales cycle; In S3, the production speed adjustment and inventory scheduling steps are as follows: S301. When the capacity adjustment direction is to remain unchanged, the production speed does not change; when the capacity adjustment direction is to expand or reduce the capacity, the sales volume set is substituted into the formula to calculate the adjusted production speed; the formula is as follows: ； Where CN is the adjusted production speed, CS is the production speed, K is the total inventory, Y is the total predicted sales speed, and T is the sales cycle; S302: multiply the predicted sales speed of the sales area marked as to be transferred by the sales cycle, subtract the inventory of the corresponding sales area from the calculated value, and put the obtained shortage inventory into the shortage inventory set in descending order. , where m represents the number of sales areas to be transferred. Indicates the shortage inventory quantity to be transferred to the mth sales area; S303, multiply the predicted sales speed of the sales area marked as to be transferred out by the sales cycle, and then subtract the calculated value from the inventory of the corresponding sales area, and put the obtained excess inventory into the excess inventory set in descending order, including , where p represents the number of sales areas to be transferred out. represents the excess inventory of the pth sales area to be transferred out; S304. Sum all elements in the shortage inventory set to obtain the total shortage inventory, and sum all elements in the surplus inventory set to obtain the total surplus inventory. The formula is as follows: ； ； In the formula, is the total shortage inventory, S is the total excess inventory; the total excess inventory minus the total shortage inventory gets the inventory difference, and it is determined whether the inventory difference is within the inventory threshold range. If it is, it is a normal situation, and if it is not, it is an abnormal situation; the judgment formula is as follows: ； In the formula, For inventory status, is the maximum value of the inventory threshold interval, is the minimum value of the inventory threshold interval; S305. The priority of the sales area to be transferred is set in descending order of the shortage inventory in the shortage inventory set. The larger the shortage inventory, the higher the priority of the corresponding sales area to be transferred. Goods are transferred to the sales area to be transferred in order of priority. The calculation formula for the transferred inventory is as follows: ； In the formula, is the actual inventory quantity transferred into the fth sales area to be transferred, is the shortage inventory to be transferred to the fth sales area, is the total shortage inventory, S is the total excess inventory; In S1, the capacity information includes the production speed, sales cycle, and inventory in each sales area; the meteorological information refers to the temperature information in the sales area, including historical temperature and future temperature; the sales information refers to the sales speed in the sales area, including historical sales speed; In S4, an abnormal situation refers to when the inventory situation is an inventory backlog or inventory shortage, and an early warning operation is performed for this situation to remind the staff to handle it.

2. A supply and demand balance management system based on big data, applied to a supply and demand balance management method based on big data as claimed in claim 1, characterized in that: The system includes a data acquisition module, a data processing module, a capacity scheduling module and a notification and warning module; The data acquisition module is used to collect weather information, sales information and production capacity information of all sales areas; the data processing module predicts the sales speed of each sales area by analyzing the weather information and production capacity information of each sales area, and plans the sales plan according to the prediction results; the production capacity scheduling module is used to adjust the production speed of the total production end according to the sales plan and schedule goods in different sales areas; The notification and warning module is used to provide warnings for cargo backlog or shortage, and remind staff to handle the situation.

3. A supply and demand balance management system based on big data according to claim 2, characterized in that: The data collection module includes a meteorological information collection unit, a sales information collection unit and a production capacity information collection unit; The meteorological information collection unit is used to collect meteorological information of all sales areas, and the meteorological information of each sales area includes historical temperature and future temperature; The sales information collection unit is used to collect sales data of all sales areas, and the sales data of each sales area includes historical sales speed; The capacity information collection unit is used to collect capacity information of all sales areas, and the capacity information includes production speed, sales cycle and inventory of each sales area.

4. The supply and demand balance management system based on big data according to claim 2 is characterized by: The data processing module includes a sales speed prediction unit and a sales plan planning unit; The sales speed prediction unit is used to calculate the predicted sales speed of each sales area; first, the historical temperature and historical sales speed of each sales area are obtained, and these data are pre-processed to remove abnormal values ​​and extreme values; Secondly, the temperature and sales speed in the same time period are correlated, and the correlation data in each sales area are fitted using a logarithmic function to obtain the relationship formula between temperature and sales speed. Each sales area corresponds to a relationship formula; finally, the future temperature of each sales area is substituted into the corresponding relationship formula to calculate the predicted sales speed of each sales area; The sales plan planning unit is used to plan the production speed adjustment direction and the cargo scheduling direction; the predicted sales speed and inventory of each sales area are substituted into the formula to calculate the total expected sales time and the expected sales time corresponding to each sales area, and the two are compared and judged with the sales cycle to obtain the production speed adjustment direction and the cargo scheduling direction of each sales area; the production speed adjustment direction includes expanding production capacity, reducing production capacity and keeping unchanged; the cargo scheduling direction of each sales area includes transferring in, transferring out and maintaining the status quo.

5. The supply and demand balance management system based on big data according to claim 2, characterized in that: The capacity scheduling module includes a capacity adjustment unit and a cargo scheduling unit; The capacity adjustment unit is used to adjust the production speed of the total production end; when the production speed adjustment direction is to expand or reduce the production capacity, the sum of the predicted sales speeds of each sales area and the sum of the inventory are substituted into the formula to calculate the adjusted production speed, and the production speed of the production end is adjusted according to the adjusted production speed; The cargo dispatching unit is used to dispatch the inventory cargo of each sales area; when the cargo dispatching direction of the sales area is transfer-in or transfer-out, the predicted sales speed and inventory quantity of each sales area are respectively substituted into the formula to calculate the shortage inventory quantity or the excess inventory quantity, and the cargo in the sales area with the cargo dispatching direction of transfer-out is transferred to the sales area with the cargo dispatching direction of transfer-in.

6. The supply and demand balance management system based on big data according to claim 2, characterized in that: The notification warning module is used for warning operation; First, the shortage inventory of all sales regions is summed up to get the total shortage inventory, and the excess inventory of all sales regions is summed up to get the total excess inventory; Second, subtract the total shortage inventory from the total excess inventory to get the inventory difference; Finally, determine whether the inventory difference is within the inventory threshold range. If it is, it is a normal situation and no warning operation is performed; If it is not, determine whether the inventory difference is greater than the maximum value of the inventory threshold interval or less than the minimum value of the inventory threshold interval. If it is greater than the maximum value of the inventory threshold interval, issue a goods backlog warning; If the inventory level is less than the minimum value of the threshold range, a missing goods warning will be issued.

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