925 results about "Order processing" patented technology

The invention relates to the technical field of intelligent operation and maintenance and artificial intelligence crossing of a power system, in particular to an intelligent power work order processing method of an RPA fused multi-modal large model, which analyzes multi-modal work order data such as texts, voices, images and the like through a domain adaptation large language model, and realizes fault key information extraction and conflict resolution in combination with a dynamic knowledge graph; performing work order priority scoring and resource allocation by using space-time constraint reinforcement learning; an analysis result is converted into an automatic execution script through an RPA engine, and a whole-process closed loop of order sending, processing and feedback is achieved; meanwhile, a feedback optimization and conflict resolution cooperation mechanism is constructed, and the knowledge graph and the model precision are continuously iterated. The method improves work order processing efficiency and analysis precision, enhances decision scientificity, and is suitable for an intelligent operation and maintenance scene of a power system.

The invention relates to the technical field of industrial production scheduling optimization, and discloses an industrial production process intelligent scheduling and optimization method and system.The industrial production process intelligent scheduling and optimization method comprises the steps that resource competition hotspots are identified by establishing a resource time two-dimensional matrix; according to the method, the resource competition relationship between the emergency order and the existing order can be accurately identified, global re-planning is replaced by local fine tuning, the optimal insertion position is determined by constructing an order interference degree evaluation model, the hotspot intensity is reduced by implementing a resource competition mitigation strategy, and optimal embedding of the emergency order is realized by adopting a progressive order insertion algorithm. The disturbance to an existing production plan is minimized, the emergency order processing efficiency and the system stability are remarkably improved, and the technical problem of intelligent scheduling of emergency orders in industrial production is solved.

The invention relates to an implementation method and device for an EtherCAT master station system based on a non-operating system, and the method comprises the steps: achieving the adaptation of an SOEM protocol stack to a hardware abstraction layer of an EtherCAT master station through the byte order processing based on a bit mask and a staged shift strategy and the EtherCAT frame receiving and transmitting control based on annular buffer area index management; on the basis of non-real-time task priority scheduling processing of a hardware timer, main circulation driven by a single-thread event and overtime monitoring of a blocking communication synchronization mechanism in combination with the timer, adaptation of an SOEM protocol stack to an EtherCAT master station operating system abstraction layer is achieved; through network scanning and communication parameter configuration, a memory management mechanism based on CoE standard mapping and a periodic position mode of a slave station, adaptation of an EtherCAT master station application layer is realized. According to the invention, through optimization and adaptation of the SOEM protocol stack, operation-system-free and microsecond-level communication jitter of the EtherCAT master station system is realized.

The invention provides an e-commerce service intelligent multi-warehouse delivery method and system, and the method comprises the steps: generating a global inventory view according to the user order information of a cross-e-commerce platform and a corresponding logistics performance demand, and carrying out the dynamic adjustment through a preset priority rule, a sorting priority sequence is generated through a dynamically adjusted inventory distribution strategy, spectral feature matching is carried out on mixed goods in all warehouses according to the sorting priority sequence and SKU identification information, goods sorting is completed in combination with target warehouse illumination environment parameters corresponding to inventory geographical distribution, and goods identification information is generated; then generating a cross-warehouse allocation decision by using a distributed inventory sharing model, and finally generating a multi-warehouse collaborative delivery instruction according to the cross-warehouse allocation decision and the cargo identification information; according to the technical scheme provided by the invention, intelligent management of the whole process from order processing to final cargo distribution is realized, the efficiency of inventory management and logistics scheduling is improved, and the accuracy and timeliness of order processing are ensured.

The invention provides an intelligent operation and maintenance work order processing method, device and equipment based on multi-modal data fusion and a medium, and the method comprises the steps: collecting alarm information of each business program or business subsystem in an IT operation and maintenance scene, the alarm information comprising a text log, a performance index, configuration information and network topology data; the collected alarm information is preprocessed; extracting key information according to the pre-processed alarm information; based on the extracted key information, generating a root cause hypothesis chain by analyzing an application relationship and a topological dependency relationship of each component in the plurality of service subsystems; according to the extracted key information and the root cause hypothesis chain, combining historical processing records in a knowledge base to generate a work order containing a suggested solution, and pushing the work order to a corresponding processor; and receiving a solution fed back by the processor, and completing work order processing.

The invention discloses a logistics center intelligent optimization scheduling system based on data analysis, and relates to the technical field of intelligent optimization scheduling, during operation of the system, key data in logistics center operation is collected and processed, after preprocessing, the inventory state of a logistics center is managed and optimized, and based on real-time inventory data and order demand information, the logistics center intelligent optimization scheduling system based on data analysis is obtained. Based on real-time traffic data, order demands and vehicle positions, calculation is carried out to obtain a comprehensive optimization index SOF, according to the order demands, the cargo capacity, the vehicle capacity and the real-time positions, vehicles are intelligently distributed, the loading sequence and the loading rate are optimized, and through the Internet of Things technology and a data analysis tool, the real-time traffic data and the real-time traffic data are analyzed. And the vehicle position, the transportation state, the environment change and the order processing progress are monitored in real time, the scheduling optimization level of the logistics system is evaluated in real time by comparing the comprehensive optimization index SOF with a preset threshold value, and an abnormal early warning and feedback mechanism is provided.

The invention discloses a customer service robot system integrating knowledge base question and answer retrieval and work order processing, which comprises a natural language understanding and generating module, a knowledge retrieval module, a business system integration module, a dialogue management and decision module and a cue word management module, and relates to the technical field of artificial intelligence. Through cooperation of a large language model and a dialogue management module, the system realizes multiple rounds of deep understanding of a natural language, and can actively guide a user to clarify a demand, such as gradually inquiring an equipment model and fault details during repair, memorizing a dialogue context and avoiding information omission. Compared with traditional regular customer service, the method has the advantages that the accuracy of understanding complex problems is remarkably improved, open dialogue scenes such as technical consultation and fault diagnosis are supported, user interaction experience is closer to manual service seats, and the problems that multi-round dialogue understanding is limited, progress data cannot be obtained in real time, multiple knowledge bases are fused, and the automation degree of the business process is low are solved.

The invention discloses a logistics order management system and method, and belongs to the technical field of logistics information management. The method comprises the following steps: step 1, generating a unique digital fingerprint for each logistics order; step 2, performing multi-level security encryption and state synchronization management on order information; 3, constructing a digital twinborn model corresponding to the order, collecting and preprocessing key data in real time and visually displaying the key data in the logistics process, and realizing dynamic monitoring of the whole process; step 4, based on an order state consensus mechanism, automatically matching optimal logistics resources and driving an order processing flow, and generating a verifiable order execution proof chain at the same time; and step 5, performing intelligent analysis and adaptive optimization on the full-life-cycle data of the order, and continuously improving the overall efficiency and precision of logistics management.

The invention discloses a commodity order information intelligent processing system, which relates to the technical field of commodity order information intelligent processing and comprises a commodity information acquisition module, an intelligent analysis module and a processing execution module. In order to solve the defects that an existing system is insufficient in response to real-time market fluctuation and demand prediction, cannot dynamically balance inventory and order quantity, is limited in collaborative scheduling capability among multiple warehouses, and is easy to cause order delay or inventory redundancy; according to the invention, commodity order information is acquired through the commodity information acquisition module, the intelligent analysis module analyzes the commodity order information, and then the processing execution module executes processing; according to the invention, the optimal processing capability of each warehouse can be comprehensively evaluated, and the warehouse most suitable for delivery is matched. Through the intelligent process, the operation efficiency of the warehouse can be improved, the inventory pressure can be reduced, the resource allocation can be optimized, the order processing accuracy and the delivery speed can be finally improved, and the overall response capability of the supply chain can be enhanced.

The invention relates to the technical field of intelligent work order scheduling platform design, and discloses an intelligent work order scheduling system, method and device and a medium, and the method comprises the steps: the system achieves the efficient and intelligent scheduling of a device fault work order through integrating a plurality of function modules. Firstly, the work order access module receives equipment fault information of different channels, and it is ensured that the information is comprehensive and timely. Then, the portrait construction module constructs a multi-dimensional ability portrait by using the historical service data of the maintenance personnel, and provides a data basis for intelligent matching; and then, the intelligent distribution module accurately matches and associates the most suitable maintenance personnel with the work order according to the portrait data and the work order parameters. And the order grabbing interaction module generates a to-be-grabbed work order list and an order grabbing interface, so that the scheduling flexibility is enhanced, and the scheduling efficiency is improved. The execution tracking module monitors the work order processing progress in real time, and transparent and controllable scheduling is ensured. And finally, the knowledge base question and answer module provides professional knowledge support for the maintenance personnel and helps the maintenance personnel to quickly solve the work order problem.

The invention relates to the technical field of artificial intelligence, in particular to a government affair hotline complaint classification and automatic order sending system and method based on a large model, and adopts a four-layer architecture to realize full-process intelligent management of government affair complaints from acceptance to disposal. The four-layer architecture comprises a multi-mode sensing layer, an intelligent decision-making layer, a dynamic single-layer dispatching layer and a closed-loop self-optimization layer; the method has the beneficial effects that an efficient, accurate and intelligent government affair hotline complaint classification and automatic order dispatching system is constructed by fusing a large model technology and an innovative data processing and order dispatching strategy, rapid and accurate classification and automatic order dispatching of complaint work orders are realized, the work order processing flow is remarkably optimized, the processing period is shortened, and the working efficiency is improved. The quality and efficiency of government affair services are improved, and the satisfaction degree of the public to the government affair services is enhanced.

The invention discloses a workshop task allocation method and system based on multiple dimensions, and relates to the technical field of production control management. Comprising the steps of obtaining order data and then performing preprocessing; based on the preprocessed order data, an advanced machine learning algorithm is adopted to construct a decision tree model, and the processing complexity of each order is identified; determining a task allocation scheme by using an optimization algorithm according to the identified order processing complexity and the current state of the production line; monitoring the actual operation condition of each production line in real time, starting a dynamic adjustment mechanism when the work load of a certain production line is unbalanced, and re-evaluating and adjusting task distribution; through intelligent task allocation and resource optimization, the production efficiency and customer satisfaction are improved, and meanwhile, dynamic adjustment and intelligent management of the production process are realized.

The invention relates to the technical field of data processing, in particular to an IPC message queue timeout processing method and device, electronic equipment and a medium, when IPC messages of a user layer are received, timestamps, priorities and timeout time of the IPC messages are obtained, the message processing sequence is adjusted according to the timestamps and the priorities, and the messages are processed according to the sequence. And when it is determined that the message is not correctly processed within the timeout time, marking the message as a dead message and moving the message into a dead message queue, determining a generation reason of the dead message in the dead message queue, and processing the reason. According to the method, the timestamps, the priorities and the timeout time of the messages are comprehensively considered, ordered processing and timeout management are carried out on the messages, and the messages which are not processed in the timeout process are converted into dead messages in time and are processed independently, so that process blockage is avoided, the influence of the dead messages on a system is reduced, the performance overhead is reduced, and the reliability and efficiency of IPC communication are improved.

System and methods are provided for automated SKU management. Embodiments include a user interface for receiving diverse catalog files, a Catalog Transformation module, a Real-Time Data Mesh (RTDM) module, a Master Data Governance (MDG) module, a Global Data Repository (GDR), and a Search Platform. The Catalog Transformation module, through iterative learning, transforms catalog files to a standard format and predicts categorization and attribute mapping. The RTDM module is configured to perform real-time data exchange. The MDG module validates the transformed catalogs. The GDR stores validated catalogs. Embodiments can include a Dynamic SKU Creation module and a Global Pricing Engine for real-time pricing. Embodiments improve data accuracy and SKU management, facilitating integrated order processing and fulfillment.

The invention discloses an order processing method and system based on a message queue, and belongs to the technical field of computers, and the method comprises the steps: receiving order data from a business platform, carrying out the preprocessing of the order data, reading related fields from a preset business rule library, and carrying out the data marking of an order; intelligently distributing orders by using a rule engine, and pushing integral messages of the distributed orders to corresponding consumption queues through message queues; after the order adding and inventory reserving operation is successfully submitted, submitting a subsequent state flow operation of the order as an asynchronous task to a state flow queue for processing; key indexes are collected through the real-time monitoring module, monitoring data are fed back to the dynamic rule module, and self-adaptive optimization of an order distribution strategy is achieved. According to the method, the row lock contention of the database can be remarkably reduced, the concurrent processing capability of the system is improved, the system stability and the data consistency are enhanced, and the resource utilization and the system expansibility are optimized.

The invention relates to a warehouse inventory management and optimization method based on artificial intelligence, and the method comprises the steps: constructing a novel mathematical model through comprehensive consideration of the storage position of a commodity, tray partition, order priority, system state and other factors, solving through employing a deep reinforcement learning DQN network, achieving the intelligent decision of a commodity pickup position, and generating an optimal picking path; according to the method provided by the invention, the order processing time can be effectively shortened, aiming at the requirements of small-batch and multi-category orders, the storage efficiency is improved, the movement distance of a stacker and the number of goods taking times are reduced, the operation cost is reduced, and flexible scheduling can be performed according to the priority to adapt to the real-time state change of the system; compared with a traditional method, after the optimization strategy is adopted, the number of times of taking out the trays is remarkably reduced, and the method has the remarkable beneficial effects, can be widely applied to the field of intelligent warehousing, improves the automation, informatization and intelligentization levels of warehousing management and meets the requirements of the modern logistics industry for an efficient warehousing system.

The invention relates to the technical field of power equipment supply chain management, and discloses a power equipment supply chain collaborative management system based on an alliance chain, comprising an alliance chain network layer: a distributed network composed of a manufacturer node, a supplier node, a logistics node, a detection node and a grid company node, each node maintaining account book consistency through a consensus algorithm; the intelligent contract execution layer comprises an order processing contract, a logistics tracking contract, a quality acceptance contract and a settlement management contract, and supports automatic execution of a business process; and the data management platform is provided with a distributed storage unit, an encryption transmission unit and an authority control unit and is used for realizing encryption storage and hierarchical access of key data. Full-process automation of order matching, production plan generation and logistics tracking is realized through an intelligent contract execution layer, an AI prediction module can pre-judge a demand peak value in advance based on historical data, a node processing priority is optimized in combination with a dynamic consensus algorithm, and manufacturer order response time is compressed.

The invention relates to a logistics order processing efficiency analysis method based on cloud computing, and the method comprises the steps: constructing a multi-dimensional and multi-node behavior log and environment variable synchronous collection system, and obtaining standardized structured data through timestamp calibration, abnormal value elimination, semantic normalization and desensitization processing; and based on node features, sequence features and environment embedding, generating a multi-node multi-scene feature vector, and inputting the multi-node multi-scene feature vector to a multi-order causal nested graph neural network for dynamic causal modeling among nodes, events and constraints. Through combination of anti-fact inference and multi-source evidence fusion, hidden bottleneck automatic identification, attribution report output and optimization suggestion generation are realized; through expert and user feedback mechanisms and working condition and rule change adaptive network structure adjustment, long-term accurate optimization and dynamic closed-loop updating of the bottleneck diagnosis model are realized. According to the invention, the intelligence and adaptive level of order flow bottleneck identification can be improved, and a high-quality data basis and intelligent decision support are provided for flow optimization in a complex logistics scene.

The invention provides an integral shopping mall order rolling processing optimization method and system based on big data, and the method comprises the steps: employing a dynamic priority adjustment mechanism for a conflict order list, and adjusting the order processing priority based on the user behavior track data, including historical exchange preference, and obtaining a resource distribution scheme; integrating the order sequence through a queue reordering mechanism, reordering based on the resource allocation scheme to obtain a final processing sequence, preferentially executing the high-priority request, and maintaining the queue stability at the same time; if residual conflicts exist in the final processing sequence, supplementary resources are extracted from a preset standby inventory through a standby resource set scheduling mechanism, a complete execution plan is obtained, and the plan covers all order processing paths; and on the basis of the complete execution plan, monitoring the order processing progress, and obtaining a stable operation order flow through progress tracking and anomaly detection, real-time state feedback and iterative adjustment.

The invention discloses a multilingual work order processing method and device based on a dynamic LoRA network, computer equipment and a storage medium, and the method comprises the steps: receiving multilingual voice input, and converting the voice input into a source language text in real time; identifying a feature vector of the source language text; calculating the correlation with a plurality of LoRA networks to be selected according to the feature vectors; determining an activation probability of each to-be-selected LoRA network based on the correlation, and dynamically activating a target LoRA network through a pre-configured gating network according to the activation probability; fusing the target LoRA network into a basic large language model to generate a fusion model; and performing cross-language translation and work order content generation on the source language text by using the fusion model, and outputting a standard work order of a target language so as to distribute the work order to a corresponding processing module according to the work order content. By dynamically activating the proper LoRA network, the efficiency and accuracy of multilingual work order processing are improved.

An order processing system 100 comprising a first storage system 102 for a first set of goods held in goods transport means, and a second storage system 106 for a second set of goods. First storage system 102 has an automated storage system with a framework and a plurality of tile or platform units 116 arranged on a grided framework of columns and rows (Fig 6). Each of the plurality of tile units 116 are configured to support a goods transport means (508, Fig 8) holding a first set of goods and comprising a drive unit (Fig 9B) operable to move the goods transport means to an adjacent tile unit in a column direction or in a row direction. A first pick face 104 is formed at an edge of the grid at which the first set of goods are accessible for retrieval, and a control system operable to individually control the tile units to move the goods transport means around the grid and into, and out of, first pick face 104. Second storage system 106 has a second pick face 108 at which the second set of goods are accessible for retrieval. First storage system 102 and second storage system 106 are arranged such that first pick face 104 is adjacent to second pick face 108. Order processing system 100 further comprises a pick area 110 first and second pick faces 104, 108 and pick area 110 comprises a support 112 for receiving goods retrieved from first pick face 104 and second pick face 108.

The embodiment of the invention provides a maintenance work order processing method and system, and relates to the technical field of intelligent household appliances. The method comprises the following steps: acquiring work order text information in maintenance work order data, extracting maintenance key information of the work order text information, matching at least one alternative maintenance personnel portrait according to the maintenance key information and all maintenance personnel portraits, and determining the maintenance personnel portraits according to the alternative maintenance personnel portraits and the maintenance key information. And respectively calculating a matching score of each alternative maintenance personnel portrait, and taking the alternative maintenance personnel corresponding to the alternative maintenance personnel portrait with the highest matching score as the push maintenance personnel. Therefore, accurate identification of maintenance requirements and automatic pushing of optimal technicians can be realized, and work order processing efficiency, distribution accuracy and after-sales service response speed are remarkably improved.

The invention discloses a work order generation method, a work order processing method and a work order management system. The work order generation method comprises the following steps: performing text extraction on multi-modal problem data reported by a user to obtain corresponding target text data; analyzing the multi-modal problem data by using the problem classification model to obtain a corresponding problem type, inputting the target text data into a work order template matched with the problem type to obtain a work order to be processed, and determining a generation timestamp of the work order to be processed; analyzing the multi-modal problem data by using an emotional tendency recognition model to obtain a corresponding emotional tendency; and packaging the emotional tendency, the question type, the work order to be processed and the corresponding generation timestamp corresponding to the multi-modal question data into a work order information packet, sending the work order information packet to a server, and receiving a question result fed back by the server. The technical problem that the work order generation accuracy is poor due to the fact that the multi-modal feedback data of the user cannot be fully understood in the related technology is solved.

The invention provides an intelligent customer service work order processing method based on a large language model, a medium and electronic equipment. Full-process automatic processing of user service requirements from receiving to feedback is achieved through modular design. The method comprises the following steps: receiving and preprocessing demand information input by a user; performing semantic understanding on the normalized input by using a large language model, identifying a demand category, and extracting key parameters such as a room number and demand details; selecting a corresponding work order generation tool from a preset tool library based on the identified demand category, and matching a required business interface; a required information list is preset according to different requirement categories, whether the extracted key parameters are complete or not is automatically checked, and if not, a prompt is generated to guide a user to supplement information; after the information is complete, calling a corresponding work order template according to the demand category, filling the key parameters into the template to generate a standard work order, and pushing the standard work order to a back-end business processing system; and receiving a back-end processing result, combining the back-end processing result with basic reply content generated by the tool, and performing retouching through a large language model to form a final reply to be fed back to the user. Through the above process, specific demands of users in the vertical field can be accurately understood, the standard work order can be automatically generated and pushed, and the processing result can be acquired in real time and fed back to the user, so that the problems that existing intelligent customer service cannot extract complete demands, work order generation lacks specifications and the processing result cannot be fed back in a closed loop mode are solved; and the service efficiency and the user experience are greatly improved.

The invention relates to the technical field of logistics information processing, and particularly discloses a high-quality and high-efficiency logistics order management system. The system comprises a registration and login terminal, an intelligent review terminal, an order processing terminal and a block chain evidence storage terminal, and is modularly deployed based on a distributed architecture. The intelligent review terminal introduces an image recognition and rule engine to realize automatic order splitting and suggestion merging; the order processing terminal combines a scoring model and a path optimization algorithm to realize dynamic payment routing and multi-target path planning; the block chain evidence storage terminal generates a non-tampering credible receipt based on hash and zero knowledge verification, and supports cross-chain auditing. The system supports GeoHash fragmentation, Flink parallel computing, high-availability container scheduling and hot and cold data hierarchical storage, and the order processing efficiency, the system elasticity and the data security are remarkably improved. The logistics order full-life-cycle management method is suitable for logistics order full-life-cycle management in a high-concurrency and high-credibility scene.

The invention discloses a power transmission line image video analyzing and monitoring system, and relates to the field of power transmission line monitoring. The multi-modal acquisition module adopts a 4K camera, a thermal infrared imager and the like to acquire data and perform time-space synchronization; the edge processing module operates YOLOv6s to detect defects and upload compressed features; the cloud analysis module analyzes and predicts by means of 3D-CNN and digital twinning technologies; the early warning linkage module gives a multi-stage alarm and dispatches a work order; the storage security module encrypts the storage data. The power transmission line is intelligently monitored, defects are detected in a multi-mode mode, and real-time early warning and quick response are achieved; the cloud edge collaboratively improves the operation and maintenance efficiency and shortens the work order processing period; reliable operation in a complex environment reduces storage and annual average operation and maintenance cost, and ensures power grid safety.

The invention discloses an inspection intelligent analysis method and system for power marketing, and the method comprises the steps: building a mapping relation between power data and business data in a target marketing region according to the power supply distribution information of the target marketing region, and obtaining a fusion data set; performing semantic mapping on the fused data set to obtain a power marketing data view; obtaining a rule between every two pieces of data in the electricity marketing data view to identify an abnormal service; determining target business data corresponding to the abnormal business, and obtaining an abnormal business analysis result based on a pre-constructed marketing inspection full-business model; generating a problem tracking work order according to the abnormal service analysis result, and matching a corresponding work order processing flow to obtain a problem processing work order; extracting an abnormal service processing opinion in the problem processing work order to predict a rectification effect of an abnormal service; and an inspection analysis report of the abnormal service is generated based on the rectification effect and the abnormal service processing opinion, so that the efficiency and accuracy of inspection analysis are improved.

The invention belongs to the technical field of customer service work order processing, and discloses an event priority ranking distribution method and system, and the method comprises the steps: converting historical multi-round dialogue data into a numeralized historical work order emotion score sequence set; the Hidden Markov model is trained by using a Boem-Weili algorithm, and core dynamic parameters of customer emotional evolution are learned; an optimal risk score threshold value after calibration is obtained through calibration; for each work order in progress, the probability distribution of each current hidden state is deduced in real time, and a forward-looking negative upgrading risk score is calculated; and when the negative upgrading risk score exceeds the calibrated risk score threshold, automatically triggering priority adjustment, and generating an updated work order record. According to the invention, a quantifiable framework based on probability prediction is provided, and customer support is converted from passive and post-response type work order processing into an active and pre-warning type risk management normal form.

The invention discloses an intelligent optimal scheduling system and method based on multi-target production, relates to the technical field of intelligent scheduling optimization, and solves the problems that a scheduling scheme is difficult to adapt to the change of a production environment due to the fact that the scheduling scheme is generated by adopting a fixed weight or a static priority in the prior art. And the accuracy of the multi-target production scheduling scheme is low. A product comprehensive function is constructed according to product data, equipment data, order data and inventory data; generating a scheduling scheme according to the product comprehensive function and performing production scheduling according to the scheduling scheme; an alarm signal is generated according to equipment data, a product comprehensive function of multiple product production is constructed, multiple objective functions are combined through adaptive weights, the optimal state can be dynamically adjusted according to real-time production data, the accuracy of a production scheduling scheme is improved, meanwhile, the equipment and order states are monitored in real time, and the production scheduling efficiency is improved. An early warning signal can be sent in time, and the situation that equipment cannot work normally or orders are not processed in time is avoided.

The invention discloses a real-time performance retail system based on urban entity supermarket distributed inventory, which organically integrates a plurality of functional modules such as inventory data acquisition, geographic index construction, target supermarket determination, state feedback, scheduling, task issuing and the like. And a whole-process automatic and intelligent processing system from commodity inventory information acquisition to order fulfillment completion is formed. The system can automatically complete inventory matching, supermarket screening, path optimization and task allocation in a city retail scene with high concurrency of orders and dynamic change of the inventory, so that manual participation links are effectively reduced, and the response time of order processing and distribution is shortened; meanwhile, based on a distributed inventory geographic index and an intelligent scheduling algorithm, the method can dynamically adapt to real-time changes of supermarket inventory and geographic environment, so that the timeliness, accuracy and user experience of order fulfillment are remarkably improved.