CN-122022407-A - Service order dynamic allocation method and system based on multidimensional data analysis

CN122022407ACN 122022407 ACN122022407 ACN 122022407ACN-122022407-A

Abstract

The invention relates to the technical field of data processing methods, in particular to a service order dynamic allocation method and a system based on multidimensional data analysis, wherein the method comprises the steps of determining the emergency degree of a current temporary order according to user information of a target user and the temporary order information of the current temporary order, and determining an insertable group according to the arrangement order information of each arranged order in a service group; determining the delay possibility degree of the current temporary order inserted into the pluggable group and the interference possibility degree of the current temporary order inserted into other orders in the pluggable group according to the temporary order information and the arrangement order information, determining the total order completion easiness degree of the pluggable group according to the arrangement order information, and determining the target insertion group of the current temporary order according to the delay possibility degree, the interference possibility degree and the total order completion easiness degree. By the technical scheme, global order scheduling optimization is realized, and the stability and the high efficiency of the whole task flow are maintained.

Inventors

XU JUN
ZHOU SHUWU

Assignees

匠达(苏州)科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. A method for dynamic allocation of service orders based on multidimensional data analysis, the method comprising the steps of: Determining the emergency degree of the current temporary order according to the user information of the target user and the temporary order information of the current temporary order, and determining an insertable group according to the arrangement order information of each arranged order in the service group; determining the delay possibility degree of the current temporary order inserted into the pluggable group and the interference possibility degree of the current temporary order to other orders in the pluggable group by combining the temporary order information and the arrangement order information; determining a total order completion easiness level of an insertable grouping according to the arrangement order information, and determining a target insertable grouping of the current temporary order in combination with the delay possibility level, the interference possibility level and the total order completion easiness level.
2. The service order dynamic allocation method based on multidimensional data analysis according to claim 1, wherein the determining the urgency of the current temporary order according to the user information of the target user and the temporary order information of the current temporary order comprises: determining complaint information and priority in the user information, and determining interval duration between required arrival time and current time in the temporary order information; and combining the complaint information, the priority and the interval duration to determine the emergency degree of the current temporary order.
3. The method for dynamic allocation of service orders based on multidimensional data analysis as recited in claim 1, wherein said determining pluggable packets based on placement order information for each placed order in the service packets comprises: Determining an idle period between any two adjacent scheduled orders according to the scheduling order information of each scheduled order in the service group; And if the required arrival time of the current temporary order is in the idle period and the idle period time is longer than the predicted service time of the current temporary order, the service packet is used as an insertable packet.
4. The method for dynamic allocation of service orders based on multidimensional data analysis as recited in claim 1, wherein determining how likely a current temporary order is to be delayed from itself by insertion into an insertable packet in combination with the temporary order information and the placement order information comprises: determining a previous predicted completion time for a current temporary order inserted into the pluggable packet for which an order was previously placed; determining an interval duration between a required arrival time and a previous predicted completion time in the temporary order information; And determining the delay possibility degree of the current temporary order inserted into the pluggable group according to the interval duration.
5. The method for dynamic allocation of service orders based on multidimensional data analysis as recited in claim 4, wherein determining how likely a current temporary order is to be delayed from itself by insertion into an insertable packet based on the interval duration comprises: determining a front arrangement position of a current temporary order inserted into the pluggable group and the front arranged order, and determining a position distance between a required arrival position and the front arrangement position in temporary order information; and determining the delay possibility degree of the current temporary order inserted into the pluggable group by combining the interval duration and the position distance.
6. The method for dynamic allocation of service orders based on multidimensional data analysis as recited in claim 1, wherein determining the likelihood of interference of a current temporary order inserted into an insertable group with respect to other orders in the insertable group in combination with the temporary order information and the placement order information comprises: determining a post-placement location of a post-placed order in the insertable grouping, where the current temporary order is inserted, determining a location distance between the required arrival location and the post-placement location in the temporary order information; Determining a distance difference between the position distance and the maximum position of the historical order, and determining a service duration proportion of the predicted service duration in the temporary order information compared with the maximum service duration of the historical order; And determining the interference possibility degree of the current temporary order inserted into the pluggable group on other later arranged orders in the pluggable group by combining the distance difference and the service duration proportion.
7. The method of dynamic allocation of service orders based on multidimensional data analysis of claim 6, wherein determining how likely a current temporary order is to interfere with other post-arranged orders in an insertable grouping by inserting the current temporary order into the insertable grouping in combination with the distance difference and the specific gravity of the service duration comprises: determining the average value of the delay possibility degree of the current temporary order inserted into the pluggable group and the emergency degree of other later arranged orders; And determining the interference possibility degree of the current temporary order inserted into the pluggable group on other later arranged orders in the pluggable group by combining the delay possibility degree, the emergency degree average value, the distance difference and the service duration proportion.
8. The service order dynamic allocation method based on multidimensional data analysis according to claim 1, wherein determining total order completion easiness of pluggable packets according to the arrangement order information comprises: determining the total predicted service duration and the total predicted travel distance of the scheduled order in the pluggable group according to the schedule order information; And determining the total order completion easiness of the pluggable packet according to the total predicted service duration and the total predicted travel distance.
9. The method of dynamic allocation of service orders based on multidimensional data analysis of claim 1, wherein determining a target insert group for a current temporary order in combination with the potential level of delay, the potential level of interference, and the total order completion ease comprises: Determining a suitability level for adding a current temporary order to an pluggable packet in combination with the delay likelihood level, the interference likelihood level, and the total order completion ease level; and taking the pluggable group with the maximum suitability as a target insertion group of the current temporary order, and inserting the current temporary order between corresponding adjacent arranged orders in the target insertion group.
10. A service order dynamic allocation system based on multidimensional data analysis, wherein the system is used for realizing the service order dynamic allocation method based on multidimensional data analysis according to any one of claims 1 to 9, and the system comprises: The order correlation analysis module is used for determining the emergency degree of the current temporary order according to the user information of the target user and the temporary order information of the current temporary order, and determining the pluggable group according to the arrangement order information of each arranged order in the service group; and the global scheduling optimization module is used for determining the total order completion easiness degree of the pluggable grouping according to the arrangement order information, and determining the target pluggable grouping of the current temporary order by combining the delay possibility degree, the interference possibility degree and the total order completion easiness degree.

Description

Service order dynamic allocation method and system based on multidimensional data analysis Technical Field The invention relates to the technical field of data processing methods, in particular to a service order dynamic allocation method and system based on multidimensional data analysis. Background With the deep integration of digital economy and service type manufacturing, the off-line engineering service industries such as equipment operation and maintenance, home appliance after-sales and on-line technical service enter a large-scale development stage, the total amount of market orders is continuously increased, and clients have higher requirements on services. Meanwhile, the service orders show remarkable fragmenting, emergency insertion, emergency occurrence of service demand change and other emergency occurrence, and the overall optimization capacity, dynamic response capacity and risk prevention and control capacity of the order scheduling and distributing system are challenged unprecedented. Most of the existing scheduling technologies are designed in a passive response mode, local temporary adjustment can be carried out only for the conditions of order change, emergency bill insertion and the like, and risk pre-judging and chain conduction analysis capability based on multi-dimensional historical data and real-time operation data is lacked. When emergency such as emergency bill insertion occurs, local manual adjustment is very easy to cause linkage delay of all-link orders, and the smooth execution rhythm of the original task sequence is thoroughly disturbed. Conventional scheduling methods typically allocate when handling emergency inserts based only on user priority and the current level of busyness of each order service group. The single-dimension decision mode is very easy to cause unexpected disruption of the plan of the original order in the group and chain delay due to lack of global simulation and influence evaluation of the whole task chain after the order is inserted, and finally, the resource allocation and the task sequence arrangement are unreasonable. Disclosure of Invention In order to solve the technical problems that the prior scheduling scheme for temporary emergency orders is easy to disturb the original order plan and generate chain delay and reduce the order task management level, the invention aims to provide a service order dynamic allocation method and system based on multidimensional data analysis, and the adopted technical scheme is as follows: The invention provides a service order dynamic allocation method based on multidimensional data analysis, which comprises the following steps: Determining the emergency degree of the current temporary order according to the user information of the target user and the temporary order information of the current temporary order, and determining an insertable group according to the arrangement order information of each arranged order in the service group; determining the delay possibility degree of the current temporary order inserted into the pluggable group and the interference possibility degree of the current temporary order to other orders in the pluggable group by combining the temporary order information and the arrangement order information; determining a total order completion easiness level of an insertable grouping according to the arrangement order information, and determining a target insertable grouping of the current temporary order in combination with the delay possibility level, the interference possibility level and the total order completion easiness level. Further, the determining the emergency degree of the current temporary order according to the user information of the target user and the temporary order information of the current temporary order includes: determining complaint information and priority in the user information, and determining interval duration between required arrival time and current time in the temporary order information; and combining the complaint information, the priority and the interval duration to determine the emergency degree of the current temporary order. Further, the determining an insertable package according to the arrangement order information of each arranged order in the service package includes: Determining an idle period between any two adjacent scheduled orders according to the scheduling order information of each scheduled order in the service group; And if the required arrival time of the current temporary order is in the idle period and the idle period time is longer than the predicted service time of the current temporary order, the service packet is used as an insertable packet. Further, determining how likely the current temporary order is to be delayed by itself by insertion into the pluggable packet in combination with the temporary order information and the placement order information, comprising: determining a previous predicted completion time for a current tempo