160 results about "Order fulfillment" patented technology

The invention relates to the technical field of commodity trade management, and discloses a commodity trade business management system based on a block chain. A block chain data acquisition module of the system obtains commodity basic information, trade enterprise qualification information and logistics node information in real time through a preset data interface, and synchronizes the information to a block chain distributed account book; the trade risk quantitative analysis module generates a trade link real-time risk coefficient set based on account book real-time data in combination with a trade compliance rule base, historical order fulfillment data and current logistics state data; a risk control strategy collaborative analysis module generates a plurality of candidate risk control strategy schemes when the risk coefficient exceeds a preset threshold value, calculates a collaborative execution cost factor when the enterprise qualification state is changed in combination with logistics node information, and obtains an interference influence value set of each scheme on the trade process; and a risk control strategy execution feedback module updates a block chain smart contract execution instruction according to the optimal risk control strategy scheme, and facilitates efficient management and control of commodity trade business.

The invention discloses a multi-objective optimization-based multi-commodity order fulfillment method and device, equipment and a medium, and relates to the technical field of supply chain management. The multi-commodity order fulfillment method comprises the following steps: acquiring order and inventory information including a current order set, a commodity set and a warehouse inventory set; and modeling an order fulfillment problem based on an actual demand of fulfillment of a multi-commodity order in the order and inventory information. The established model is a multi-objective optimization problem containing three objectives. Generating an initial population by adopting a heuristic method based on priority and inventory feasibility; and carrying out iterative optimization on the initial population by adopting a rapid non-dominated sorting genetic algorithm with elitism based on a double-layer elitism strategy to obtain a Pareto non-dominated solution set. And selecting a final order fulfillment scheme from the Pareto non-dominated solution set according to the preference of a decision maker. According to the method, three core operation indexes are synchronously improved under the condition of meeting feasibility constraints such as inventory, processing capability and demand.

The embodiment of the invention provides an order implementation method, system and device based on distributed transactions, equipment and a storage medium, and relates to the technical field of computer application. Receiving an order request sent by user equipment, and sending a TRY request to each micro-service in the plurality of micro-services in parallel; after it is determined that the data reservation operation of each micro-service is successful, CONFIRM requests are sent to each micro-service in parallel; and after determining that the data reservation operation of any micro-service fails or receiving a cancel request for any micro-service, respectively sending a CANCEL request to each micro-service, so that each micro-service cancels the data reservation operation of the micro-service after receiving the CANCEL request sent by the order service. According to the invention, the method achieves the control of a plurality of micro-services, improves the business processing efficiency while guaranteeing the consistency and atomicity of distributed transactions, and further improves the business throughput.

The invention belongs to the technical field of order fulfillment process monitoring, and discloses an order fulfillment process delay early warning method and system based on multi-node state acquisition, and the method comprises the steps: collecting the dynamic state data of multiple nodes in a fulfillment process in real time; matching judgment is carried out through the node rule base, primary early warning is triggered, and an early warning context data set is constructed; inputting the data set into a pre-trained delay risk prediction model, and outputting an overall risk probability and a key influence node identifier; issuing a grading early warning signal according to the risk probability; carrying out interpretable root cause positioning through a root cause analysis rule chain based on directed acyclic graph representation; incremental learning is carried out on the prediction model based on early warning feedback data to form an optimized closed loop; the system correspondingly comprises a data acquisition module, a rule judgment module, a risk prediction module, an early warning release module, a root cause positioning module, a feedback learning module and the like. According to the invention, the early-stage, accurate and automatic early warning and root cause analysis of the full-process risk of order fulfillment are realized.

The invention relates to the technical field of artificial intelligence engineering, and provides a supply chain management-oriented multi-modal AI large model fusion software platform construction method, which adopts the following technical scheme that the supply chain management-oriented multi-modal AI large model fusion software platform construction method comprises the following steps of: collecting multi-source heterogeneous data in a supply chain, comprising real-time inventory change data, historical demand fluctuation characteristics, emergency semantic information, transportation mode multi-modal information, supplier risk scores and public opinion analysis results, and non-structured documents and numerical indexes of cross-enterprise business processes, a multi-modal AI large model fusing texts, images and time sequence information is constructed based on the collected data, and the multi-modal AI large model is used for analyzing the data. And performing semantic feature extraction, numerical index fusion modeling and risk prediction, outputting based on a multi-modal AI model, dynamically regulating and controlling an inventory water level, adaptively regulating and controlling a purchase plan, intelligently regulating and controlling a logistics scheduling strategy, foresight regulating and controlling a supply chain cooperation strategy, and regulating and controlling an order fulfillment progress in real time.

The invention provides an order fulfillment method and system supporting delayed delivery after cut-off, and relates to the technical field of warehouse management, and the method comprises the steps: obtaining fulfillment orders of a plurality of delayed delivery requests; carrying out delayed delivery qualification verification on each fulfillment order; inquiring the real-time state of a warehouse-out notification list associated with each verified performance order in the warehouse; according to the real-time state, classifying and intercepting the performance orders passing the verification to obtain a plurality of first target performance orders which are successfully intercepted; performing performance order delivery date modification processing on each first target performance order to generate a plurality of second target performance orders; under the condition that each second target fulfillment order reaches the delivery day cut-off time, generating a finished goods supply order, an ex-warehouse notification order and a delivery carriage acceptance order of the second target fulfillment order, and synchronously executing management operations of inventory freezing, inventory release and inventory supplementary occupation; and otherwise, waiting for the second target fulfillment order to the delivery day cut-off time.

The invention belongs to the related technical field of vehicle control and scheduling, and particularly relates to an unmanned vehicle scheduling system and method based on strategy driving, and the system employs a three-layer architecture, and comprises a framework layer which comprises a visual human-computer interaction interface, a scheduling service system and an automatic driving system, data management, work order management, scheduling task execution and unmanned vehicle state feedback functions are provided, and the layer is kept unchanged when a service scene is newly added; the strategy layer supports three elements of dynamic configuration and strategy management and provides a customized interface of scheduling rules and parameters, and the three elements of the strategy comprise a scheduling algorithm plug-in program, a parameter configuration page and a new work order page; and the scheduling layer is used for instantiating and operating scheduling logic, associating a specific strategy, calling the function of the framework layer and the scheduling capability defined by the strategy layer to command the unmanned vehicle to complete scheduling operation, and realizing business work order fulfillment. The system and the method have the advantages of rapid scene adaptation, high system compatibility, low development cost, flexible service configuration and the like.

A mobile robot for travelling within an order fulfillment center including a deck and one or more vertical storage racks, a vertical storage rack of the one or more storage racks including a plurality of horizontal rails, spaced apart from each other on respective levels of the vertical storage rack, and a pair of vertical tracks, spaced apart from each other and extending between the plurality of levels of the vertical storage rack, the mobile robot including a motor, a shaft configured to be driven by the motor, first and second pairs of wheels and a pair of drive gears.

An automated order fulfillment system and mobile robot are disclosed, where the mobile robot includes a compliant drive for moving between levels of a multilevel storage structure. In one example, the compliant drive comprises a drive shaft having splines configured to provide rotational play that prevents jamming of a vertical drive gear on the end of the shaft with a rack in a vertical track.

The invention relates to the technical field of supply chain finance, in particular to a supply chain finance movable property pledge supervision risk dynamic assessment method and system, and the method comprises the steps: obtaining transportation GPS position and temperature, humidity and vibration data, marking abnormity, analyzing order fulfillment and inventory circulation, judging inventory overstock or delay, assessing price fluctuation risk, and calculating pledge risk weighted value. And judging and updating the risk level. According to the invention, through real-time monitoring of temperature and humidity, vibration, path deviation and other information in the transportation process, whole-process monitoring of transportation and inventory circulation is realized, and the pledge risk identification capability is improved. Weighted evaluation is carried out in combination with transportation, performance, inventory and market price data, the risk contribution degree is reflected, the evaluation result is updated in time, a supervisor is helped to find problems in advance, the response speed is increased, the fund risk is reduced, the transparency and safety of movable property pledge management in supply chain finance are improved, and the financing risk is effectively prevented.

Systems and methods for an e-commerce health care marketplace are provided. In one embodiment, a method comprises, responsive to a query from a user, retrieving from a database a list of responses comprising one or more health care providers offering one or more health care services at a provider-supplied price; filtering the list of responses based on a geographic location included in the query; providing, for display, the filtered list of responses; receiving a payment from the user for a response selected from the filtered list of responses; automatically sending a notification of the payment to a provider associated with the selected response; and responsive to receiving an order fulfillment notification from the provider, automatically providing the payment to the provider. In this way, health care consumers may make informed purchasing decisions when shopping for health care services and health care providers may receive prompt payment for services delivered.

A method of order fulfillment at a fulfillment center includes: identifying a first number of available collection units available for processing a corresponding first number of orders, identifying, from a list of unfulfilled orders at the fulfillment center, a second number of unfulfilled orders each of which is to be assigned to one of the first number of available collection units for packing, where the second number is selected such that an efficiency metric, which is based on (i) a total distance traversed by a collection device to collect the component items corresponding to the second number of unfulfilled orders from the storage area and (ii) a third number of component items collected using the collection device traversing the total distance, satisfies a threshold condition, and generating a signal to assign one or more particular collection devices to collect the third number of component items.

The invention discloses a plastic trade scene-oriented cargo purchase-sales-stock data management system, which belongs to the technical field of cargo purchase-sales-stock management and specifically comprises a database, a purchase management module, a sales management module, a stock management and distribution module and an order tracking module. According to the method, a purchase order-inventory real-time binding mechanism is introduced, original inventory data is updated through in-transit inventory data, a traditional inventory is divided into new inventory concepts of available inventory and in-transit inventory, after sales order data is obtained, an inventory locking engine mechanism is called, a binding relation between a sales order and a new inventory is generated, and the new inventory is obtained. According to the method, the locked inventory is determined through matching and locking of the sales order and the inventory, the inventory data is updated again to cancel after verification of the locked inventory, dynamic monitoring and synchronous association of the inventory data, the purchasing data and the sales data are achieved, the inventory management efficiency and the order performance accuracy are effectively improved, and goods are effectively prevented from being oversold and mistakenly sold.

The application provides a logistics transportation management method and system based on artificial intelligence, relates to the field of logistics transportation, and solves the technical problems that the prior art is difficult to balance real-time performance, distribution feasibility and resource utilization efficiency in the sudden interruption scene of a logistics vehicle, resulting in slow scheduling response, frequent secondary conflicts or failure of high-value order fulfillment. The method comprises the following steps: obtaining a set of orders to be delivered by a target vehicle at present and real-time position information; based on a preset hard constraint condition, screening candidate vehicles and constructing a task migration feasibility graph; inputting the task migration feasibility graph into a pre-trained lightweight graph neural network model to output the compatibility scores of each candidate vehicle for each order to be delivered in the order set; based on the compatibility scores, evaluating the urgency of the order to be delivered; and based on the urgency of the order to be delivered, updating the delivery task scheme of each candidate vehicle. The application is used in the process of logistics transportation.

A product order fulfillment system includes: a multi-level transport system, each level thereof having a corresponding independent asynchronous level transport system; a lifting transport system with more than one independent lift axis, in a common lift cell, each of the more than one independent lift axis being configured to independently hold and transport the at least one case along a trajectory, independently of each other independent lift axis; and a controller operably coupled to the multi-level transport system and the lifting transport system; where the asynchronous trajectories of the common lift cell output an ordered sequence of mixed cases in accordance to a predetermined case out ordered sequence of mixed cases; and where the controller is configured to heuristically generate optimal trajectory solutions for the asynchronous trajectories, and assign the at least one case to at least one asynchronous level transport axis based on at least one qualitative metric characterized by the optimal trajectory solutions.

A product order fulfillment system includes: a multi-level transport system, each level thereof having a corresponding independent asynchronous level transport system; a lifting transport system with more than one independent lift axis, in a common lift cell, each of the more than one independent lift axis being configured to independently hold and transport the at least one case along a trajectory; and a controller operably coupled to the multi-level transport system and the lifting transport system; where the asynchronous trajectories of the common lift cell output an ordered sequence of mixed cases in accordance to a predetermined case out ordered sequence of mixed cases; and where the controller is configured to heuristically generate optimal trajectory solutions for the asynchronous trajectories, and assign the at least one case to at least one asynchronous level transport axis based on at least one qualitative metric characterized by the optimal trajectory solutions.

Fleet management of unmanned aerial vehicles (UAVs) is disclosed. Fleet management systems and methods may be implemented within UAVs, or systems utilizing UAVs, utilized in a delivery system configured to pick up a payload or a package at a shipping location and deliver a payload or package to a delivery location. The fleet management systems and methods may facilitate system operations of a UAV fleet, including, without limitation, positioning or deploying UAVs to meet or fill demand, prepositioning UAVs to meet a demand prediction, association delivery' orders to UAVs, order fulfillment, fleet maintenance management during operations, and flight path planning or generation.

Warehouse automation and methods of sorting and sequencing garment items can be used to enhance efficiencies of order fulfillment processes. For example, this document describes warehouse automation of systems and methods for efficiently compiling store replenishment orders for garment items. The systems and methods make store replenishment of garment items highly efficient. In some examples, the systems and methods are focused on automation (e.g., using autonomous mobile robots that transport pods containing garment items) and arranging the garment items in store-ready containers that can be wheeled out directly into the retail area for efficient store replenishment.

An order fulfillment facility with a delivery system is disclosed having plurality of mobile robots with containers to bring customer orders and / or power supply device / s to UAV / s for final delivery. UAV leaves the discharged power supply devices that are received in empty container and transported to storage area for replenishment and diagnostic checks. Order fulfillment operations along with power supply device charging and monitoring is performed to achieve timely delivery of customer orders.

A system for order fulfilment including automated stacking of mixed case packages on a support in a predetermined spatial arrangement to form a stack of mixed case packages according to an order, the system includes at least one sortation unit for receiving all trays from each traying unit and a buffer storage unit for temporary storage of the trays sourced from the diverts, and more than one palletizing unit for stacking of mixed case packages on a support in a predetermined spatial arrangement to form a stack of mixed case packages according to an order being sourced with packages from at least one detraying unit.

This invention belongs to the field of smart logistics technology and discloses a method for cost and carbon emission collaborative optimization for hubs and regional warehouse networks. It constructs a three-dimensional global collaborative optimization model of cost, carbon emission, and timeliness, and adjusts target weights in real time through a dynamic weight adaptive mechanism. It integrates cost and carbon emission elements across the entire supply chain to establish a three-flow linkage, coupled with a multi-dimensional constraint system. This breaks down optimization barriers in warehousing and transportation, and dynamically adapts to regional carbon emission quotas and cargo urgency. While ensuring timely order fulfillment, it achieves the collaborative goal of minimizing overall cost and keeping carbon emissions within quota limits, balancing economic benefits and environmental responsibility, and enhancing the overall competitiveness of the supply chain. Through edge nodes, it achieves heterogeneous data cleaning and standardization, dynamically calibrates carbon emission factors and quantifies them into unified units, and completes distributed storage, access control, and full-chain traceability through a consortium blockchain, ultimately constructing a digital twin data foundation.

The invention provides a prediction method and a prediction device for order fulfillment duration, and the method relates to the technical field of electronics, the prediction method is applied to a multi-task prediction model, the multi-task prediction model comprises at least one feature learning layer, the feature learning layer comprises a task learning layer, and the task learning layer comprises at least one feature learning layer. The task learning layer comprises a first feature extraction module and an inter-task attention mechanism module, and the prediction method comprises the following steps: obtaining original data in response to a merchant browsing operation of a user; obtaining a first feature of the first task and a second feature of the second task based on the original data and a first feature extraction module; task association features are obtained based on the original data and an inter-task attention mechanism module; obtaining a target fusion feature based on the first feature, the second feature and the task association feature; and based on the target fusion feature, obtaining a first predicted delivery time length and a second predicted delivery time length. Based on the scheme, the time difference between the two predicted delivery durations can be reduced, so that the user experience is improved.

The application relates to the technical field of enterprise operation management, in particular to a retail enterprise inventory coordination management system based on intelligent order performance and cross-channel demand prediction, which comprises an order management module, an intelligent order performance module, a demand prediction module, an inventory coordination management module, a data analysis module and a user management module; compared with the simple scheme of directly using a historical logistics cycle as a predicted delivery time in the prior art, the scheme has the shortcoming that the current logistics progress and the actual situation cannot be accurately reflected, the scheme adopts a more refined prediction formula, comprehensively considers a logistics average cycle T, a current logistics progress P and respective corresponding coefficients beta and gamma, so that the delivery time can be more accurately predicted, more reliable logistics information is provided for customers, and customer experience and trust degree are improved.

The invention discloses a cross-border e-commerce intelligent multi-warehouse allocation data simulation system and method, and the system comprises each warehouse inventory management module which is used for synchronizing global multi-warehouse real-time and in-transit inventory data; the sales order management module is used for acquiring undelivered order information; the key warehouse marking configuration module is used for setting an allocation strategy rule based on the inventory coverage rate; the global inventory view generation module is used for executing prospective inventory distribution simulation and outputting a global inventory view; the sales order marking module is used for marking whether the order needs to be delivered by a key overseas warehouse or not according to a view; and the just-to-be-allocated module is used for accurately calculating the minimum necessary allocation quantity required to be allocated from the Chinese warehouse to each key overseas warehouse according to the marked order, and generating an instruction report. According to the method, artificial experience is replaced by simulation calculation, data driving and prospective optimization of allocation decision making are realized, inventory overstock and cross-border logistics cost are effectively reduced, and order fulfillment speed and overall elasticity of a supply chain are improved.

Systems, methods, and apparatus are disclosed that provide a pickup process for items purchased from a store. In some embodiments, a mobile computing device of a customer may determine whether the mobile computing device and therefore the customer are in a pickup zone for a store. In response to determining that the mobile computing device is in the pickup zone, the mobile computing device may notify the customer and request whether the customer wishes to initiate pickup of purchased items from the store. The mobile computing device may notify a merchandise pickup system of the customer's desire to pickup the purchased items.

This invention discloses a remote USB sharing system, including a sharing unit, a seller login center unit, and a communication unit. It also discloses a remote USB sharing method comprising six steps. The remote USB sharing system proposed in this invention features a simple architecture, low development cost, ease of operation, and convenient real-time communication, facilitating mutual learning and exchange among colleagues. It is particularly beneficial for novice sales personnel, allowing for quick onboarding, effectively reducing training costs, and significantly improving operational efficiency. For buyers, the order placement and login processes are also relatively simple, and the system includes communication and consultation functions, greatly enhancing the buyer's experience when purchasing remote USB dongles. This promotes its widespread adoption. The remote USB sharing method proposed in this invention has simple and reasonable steps, enabling real-time communication between buyers and sellers, which facilitates order fulfillment, significantly improves sales performance, and ultimately enhances corporate profitability.

A retail fulfillment system, including: a storage structure; a plurality of mobile robots configured to move laterally along storage structure aisles and vertically through the storage structure to deposit and retrieve containers to and from the plurality of container storage locations; and a container input / output interface system including: a matrix of container access bays where the plurality of mobile robots are configured to deliver and retrieve the containers to and from the container access bays through a robot interface. Each of the container access bays includes an autonomous interlock system that is activated, separate from the plurality of mobile robots, in response to a presence of a container, of the containers, at the respective one of the container access bays to cause a barrier system to transition to an access state enabling access by an operator through the access face to the container.

This invention discloses a method for visually tracking the entire lifecycle of chip sales orders, relating to the field of order management technology based on knowledge graphs. The method includes: acquiring order events and packaging identifiers of sales orders, identifying multiple sub-batches, and extracting event interval sequences for each sub-batch; querying the humidity clock semantics of each interval using a knowledge graph based on the order event information corresponding to the event interval sequences, determining the allowable exposure time and duration of each interval in conjunction with the packaging identifier, and generating a clock calculation sequence; calculating the remaining humidity clock quantity for each sub-batch, and constructing a set of remaining humidity clocks for each order sub-batch; extracting the conservative deliverable status, clock fork quantity, and dominant sub-batch for each lifecycle node, constructing an order node status group, and generating visual tracking results for the order. This invention can accurately reflect the state differentiation during the unpacking and batching of humidity-sensitive chips, improving the authenticity and targeted management of order fulfillment tracking.

The invention relates to the technical field of supply chain management, in particular to a supply chain collaboration platform intelligent software interaction system based on a large model, which comprises a dynamic replenishment strategy module for generating a dynamic replenishment strategy model according to historical purchase cycle data of multiple categories of materials, and the model takes an inventory turnover rate and a stockout probability as optimization targets; the collaborative prediction and feedback module takes an output result of the dynamic replenishment strategy model as an input, drives a collaborative prediction engine to perform order fulfillment deviation analysis, and dynamically updates prediction model parameters through a feedback mechanism; the logistics routing adaptive adjustment module is used for constructing a path propagation map based on the time sequence data of the logistics abnormal event, and performing adaptive adjustment on a routing decision model in combination with a real-time transportation state; and the intelligent contract cooperative regulation and control module synchronizes the adjusted routing strategy and the production plan change information to an intelligent contract system, and triggers scheduling elastic regulation and control and cooperative clause automatic updating of each node of the supply chain.