CN-121169036-B - Logistics scheduling method and device based on cultural event, electronic equipment and medium

CN121169036BCN 121169036 BCN121169036 BCN 121169036BCN-121169036-B

Abstract

The application relates to the technical field of logistics scheduling based on cultural events, and discloses a logistics scheduling method, a device, electronic equipment and a medium based on cultural events, wherein the method comprises the following steps: the cultural event is analyzed by introducing a large language model, the actual influence of the cultural event on the clearance operation is deeply understood, and the clearance delay or flow change risk caused by the event is predicted and responded in advance by quantizing the cultural event factor into an association rule, so that the multi-objective optimization scheduling is carried out, and the scheme of grading logistics scheduling is obtained. The method has the beneficial effects that the method can effectively avoid the congestion of high-grade goods in the high-impact period of the event, realize the dynamic matching of the logistics resources and the operation capacity of related institutions, and reduce the risks of goods delay, destination congestion and goods loss caused by scheduling mismatch from the source.

Inventors

Xie Qiongbing
CHEN DAWEI
WANG XUETENG
ZENG WEIJIA
HE ZHONGQING
XU KUNYANG
ZHAO SHAN
XU LINGZI

Assignees

深圳市明心数智科技有限公司

Dates

Publication Date: 20260508
Application Date: 20251120

Claims (8)

1. A cultural event based logistics scheduling method, the method comprising: acquiring cultural event related data and a historical clearance operation log in real time; Inputting the cultural event related data and the historical clearance operation log into a preset large language model for analysis to generate an association rule between the cultural event and the clearance operation; Acquiring a to-be-processed logistics order information set, wherein the logistics order information set comprises a plurality of pieces of goods order information, and each piece of goods order information at least comprises a goods category, a destination and a goods grade information; Generating a predicted clearance time window for each of the goods order information based on the association rules and the goods order information; determining a corresponding target area based on the destination of each order of goods in the logistics order information set; Acquiring the rule information of each target area and space-time labels of the rule information; mapping each piece of regulation information and each piece of space-time labels into a preset mathematical space to form a plurality of constraint conditions of the preset mathematical space, thereby obtaining a mathematical model; Introducing soft time window constraint into the mathematical model, and increasing punishment cost for a scheduling scheme exceeding a predicted clearance time window, thereby obtaining an optimized mathematical model; Inputting the forecast clearance time window of each piece of goods order information and the goods order information into a preset mathematical model; and carrying out collaborative decision in the mathematical model through a multi-objective optimization strategy, and carrying out grading logistics scheduling on each piece of goods order information.
2. The cultural event based logistics scheduling method of claim 1, wherein the step of generating a predictive clearance time window for each of the cargo order information based on the association rules and the cargo order information comprises: matching each piece of goods order information with the association rule to obtain a target cultural event factor of each piece of goods order information; inputting the goods order information into a preset clearance duration prediction model to obtain a reference clearance duration under the influence of a cultural event; and correcting the reference clearance time based on the target cultural event factor to generate a clearance time window containing the earliest predicted clearance time window and the latest predicted clearance time window.
3. The cultural event based logistics scheduling method of claim 1, wherein the step of inputting the cultural event related data and the historical clearance operation log into a preset large language model for parsing to generate association rules between cultural events and clearance operations comprises: Extracting abnormal clearance events with clearance delay and improved checking rate, which occur in the history clearance operation log during the occurrence period of the history cultural events, through a preset large language model; analyzing the cultural event related data by using the large language model, and identifying event features which are strongly related to the abnormal clearance event; And carrying out association mapping on the event characteristics and clearance operation parameters to generate association rules taking the event characteristics as input and taking expected clearance influence as output.
4. The cultural event based logistics scheduling method of claim 1, wherein said step of performing hierarchical logistics scheduling on each of said cargo order information in said mathematical model by collaborative decision-making through a multi-objective optimization strategy further comprises, after said step of: clearing each goods order in the logistics order information collection according to the scheme of grading logistics scheduling; acquiring the clearance actual progress of each goods order in real time; Judging whether the deviation value of the clearance actual progress and the theoretical clearance progress of the grading logistics scheduling is larger than a preset threshold value or not; when the deviation between the actual clearance progress and the theoretical clearance progress exceeds a preset threshold, acquiring a target order set which is not cleared yet; and rescheduling the goods orders in the target order set according to the mathematical model.
5. The cultural event based logistics scheduling method of claim 1, wherein said step of performing hierarchical logistics scheduling on each of said cargo order information in said mathematical model by collaborative decision-making through a multi-objective optimization strategy further comprises, after said step of: According to the scheduling result of each goods order, a scheduling confirmation instruction is sent to each relevant terminal; receiving feedback information from each relevant terminal; judging whether each feedback information is refused or not; if the feedback information is refused, acquiring corresponding target goods order information; and adjusting the cargo level information in the target cargo order information, and carrying out grading logistics scheduling on each cargo order information again.
6. A cultural event based logistics scheduling apparatus, the apparatus comprising: The historical clearance operation log acquisition module is used for acquiring the cultural event related data and the historical clearance operation log in real time; the association rule generation module is used for inputting the cultural event related data and the historical clearance operation log into a preset large language model for analysis so as to generate association rules between cultural events and clearance operation; The system comprises a logistics order information collection acquisition module, a storage module and a storage module, wherein the logistics order information collection acquisition module is used for acquiring a logistics order information collection to be processed, the logistics order information collection comprises a plurality of pieces of goods order information, and each piece of goods order information at least comprises a goods category, a destination and a goods grade information; A predicted clearance time window generation module for generating a predicted clearance time window for each of the goods order information based on the association rules and the goods order information; The target area determining module is used for determining a corresponding target area based on the destination of each goods order in the logistics order information set; the space-time tag acquisition module is used for acquiring the rule information of each target area and the space-time tag of the rule information; The mathematical model acquisition module is used for mapping each rule information and each space-time label into a preset mathematical space to form a plurality of constraint conditions of the preset mathematical space so as to obtain a mathematical model; The introducing module is used for introducing soft time window constraint into the mathematical model, and increasing punishment cost for a scheduling scheme exceeding a predicted clearance time window so as to obtain an optimized mathematical model; The input module is used for inputting the forecast clearance time window of the goods order information and the goods order information into a preset mathematical model; And the grading logistics scheduling module is used for carrying out collaborative decision in the mathematical model through a multi-objective optimization strategy and carrying out grading logistics scheduling on the order information of each goods.
7. A computer readable storage medium, characterized in that a computer program is stored, which, when being executed by a processor, causes the processor to perform the steps of the cultural event based logistics scheduling method of any one of claims 1 to 5.
8. An electronic device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the cultural event based logistics scheduling method of any one of claims 1 to 5.

Description

Logistics scheduling method and device based on cultural event, electronic equipment and medium Technical Field The invention relates to the technical field of application of cultural event-based logistics scheduling and artificial intelligence in logistics optimization, in particular to a cultural event-based logistics scheduling method, a cultural event-based logistics scheduling device, electronic equipment and a cultural event-based logistics scheduling medium. Background In the international logistics field, accurate prediction of clearance aging is the core of making a high-efficiency logistics scheduling plan, however, the existing clearance aging prediction system and method have significant defects, and the current industry generally relies on static historical data, for example, simply adopts the average clearance period of a certain destination as a prediction reference. The method completely ignores short-term and severe impact of local cultural events on clearance efficiency, leads to far-exceeding static prediction time of actual clearance time, has higher prediction error rate, and can cause large-area delay of goods, thereby leading to destination congestion, rapid increase of storage cost and increase of cargo damage risk. Disclosure of Invention Based on this, it is necessary to provide a method, a device, an electronic device and a medium for scheduling logistics based on cultural events aiming at the existing problem of scheduling logistics based on cultural events. A cultural event based logistics scheduling method, the method comprising: acquiring cultural event related data and a historical clearance operation log in real time; Inputting the cultural event related data and the historical clearance operation log into a preset large language model for analysis to generate an association rule between the cultural event and the clearance operation; Acquiring a to-be-processed logistics order information set, wherein the logistics order information set comprises a plurality of pieces of goods order information, and each piece of goods order information at least comprises a goods category, a destination and a goods grade information; Generating a predicted clearance time window for each of the goods order information based on the association rules and the goods order information; Inputting the forecast clearance time window of each piece of goods order information and the goods order information into a preset mathematical model; and carrying out collaborative decision in the mathematical model through a multi-objective optimization strategy, and carrying out grading logistics scheduling on each piece of goods order information. Further, before the step of inputting the predicted clearance time window of each item order information and the item order information into the preset mathematical model, the method further includes: determining a corresponding target area based on the destination of each order of goods in the logistics order information set; Acquiring the rule information of each target area and space-time labels of the rule information; Mapping each of the regulation information and the space-time labels into a preset mathematical space to form a plurality of constraint conditions of the preset mathematical space, thereby obtaining the mathematical model. Further, after the step of mapping each of the rule information and the space-time tag into a preset mathematical space to form a plurality of constraint conditions of the preset mathematical space, the step of obtaining the mathematical model further includes: Introducing soft time window constraint into the mathematical model, and increasing punishment cost for scheduling schemes exceeding a predicted clearance time window, thereby obtaining an optimized mathematical model. Further, the step of generating a predicted clearance time window for each of the order information based on the association rules and the order information includes: matching each piece of goods order information with the association rule to obtain a target cultural event factor of each piece of goods order information; inputting the goods order information into a preset clearance duration prediction model to obtain a reference clearance duration under the influence of a cultural event; and correcting the reference clearance time based on the target cultural event factor to generate a clearance time window containing the earliest predicted clearance time window and the latest predicted clearance time window. Further, the step of inputting the cultural event related data and the historical clearance operation log into a preset large language model for analysis to generate an association rule between the cultural event and the clearance operation comprises the following steps: Extracting abnormal clearance events with clearance delay and improved checking rate, which occur in the history clearance operation log during the occurrence period of the history cult