41 results about "Location-allocation" patented technology

The invention provides an intelligent storage location optimization method and system, and belongs to the technical field of storage management, and the method comprises the steps: obtaining the data information of commodities in a storage system, constructing a storage location optimization model, comprising a comprehensive objective function taking maximization of space utilization rate and sorting efficiency and minimization of storage cost as objectives and constraint conditions based on physical rules and business rules; solving the storage location optimization model by using an optimization algorithm, and generating a storage location distribution scheme and prediction performance data; executing the storage location allocation scheme, and collecting actual storage location data and actual operation performance data; comparing the actual storage location data with the storage location allocation scheme to obtain a scheme execution coincidence rate; comparing the actual operation performance data with the predicted performance data to obtain a performance deviation rate; and based on the scheme execution coincidence rate and the performance deviation rate, adjusting the constraint condition of the storage location optimization model and / or the weight coefficient of the comprehensive objective function to obtain an updated storage location optimization model, and carrying out storage location allocation.

The invention discloses an intelligent storage dynamic goods allocation distribution method based on goods allocation popularity analysis, and belongs to the technical field of intelligent storage management. The method comprises the steps of 1, collecting goods location coordinates, goods attributes and historical and current order data; 2, calculating goods real-time demand popularity and goods shelf position popularity based on the current order, and coupling to obtain goods allocation coupling popularity; 3, by taking maximization of the total goods allocation coupling heat and optimization of the estimated picking path as targets, constructing a dynamic equilibrium model and solving and outputting a goods allocation distribution scheme; and step 4, executing distribution and order picking tasks, collecting actual operation data and feeding back the correction heat calculation model to realize closed-loop optimization. According to the method, the coupling conflict between static goods allocation and dynamic order selection is solved, the linkage decision of storage location optimization and path planning is realized, the method can be adaptive to order fluctuation and operation environment change, and the warehousing operation efficiency is remarkably improved.

The application discloses a high-density stereoscopic warehouse dynamic storage space allocation method for WMS, and relates to the technical field of artificial intelligence. Stereoscopic warehouses are arranged along the direction of the roadway, and stackers, shuttles and hoists are arranged in the stereoscopic warehouses. Field programmable gate array acceleration cores are arranged in the edge nodes of the stereoscopic warehouses. The acceleration cores are interconnected with the WMS through a time-sensitive network. The method comprises the following steps: step 1, the acceleration core constructs a beat dependency graph based on the current carrying instruction issued by the WMS, wherein the carrying motion is taken as an event node, and the action connection relationship is taken as a directed edge; step 2, the acceleration core constructs a colored Petri net; and step 3, the acceleration core constructs a graph attention reinforcement learning decision module and takes a heterogeneous graph as input, and the WMS drives the corresponding carrying equipment to perform the actions of warehousing, moving and replenishment. The application can significantly improve the system throughput, reduce the equipment idle rate and beat jitter under the sub-millisecond end-to-end decision delay.

The application discloses a kind of stereoscopic warehouse goods location allocation optimization method, system, equipment and medium, it is related to intelligent warehousing and logistics scheduling technical field, including: in the process of equipment execution warehousing operation, real-time acquisition equipment actual track point and the track deviation amount between equipment pre-planned track, when the track deviation amount accumulates exceeds preset deviation threshold, with current actual equipment state parameter set as initial state, jump to step S2 and re-perform track pre-planning and goods location allocation.The application is by real-time acquisition equipment actual track point and the track deviation amount between pre-planned track, when cumulative deviation is over threshold, with current actual equipment state parameter set as initial state trigger re-planning, form closed loop deviation feedback mechanism, effectively guarantee the robustness and dynamic adaptability of system operation.

Disclosed are systems and methods for determining swap and replenishment opportunities in a pick area of a storage facility. A method can include receiving, by a computer system, current stock levels for bays in the pick area, identifying a subset of the bays as having a replenishment or swap opportunity based on determining that the current stock levels for the subset of the bays is less than a threshold stock level, and determining, for each bay in the subset of the bays, whether the bay has a swap opportunity or a replenishment opportunity. The method can also include determining whether each bay is a static bay based on pick area build information, which can include a pick area layout, current SKUs in the pick area, date of layout build, static location assignments for the bays, and dynamic location assignments for the bays.

Systems and methods are provided for automatically generating prioritized, color-coded tasks based on user input received through a conversation interface of a task management application. User input provided to an automated software assistant is analyzed along with contextual data from multiple sources, including existing tasks, calendar events, emails, and messages. The system determines task attributes such as title, status, deadline, geographic location, urgency, and frequency, and assigns a color tag based on color assignment parameters including task category, priority, and location. Machine learning algorithms analyze historical user-assigned colors in relation to task attributes to predict color assignments for new tasks and establish intelligent color relationships, thereby dynamically updating a prioritized, color-coded task list displayed in a graphical user interface.

The application discloses an intelligent warehouse storage location allocation method for gas valve parts, and belongs to the technical field of warehouse planning, which comprises the following steps: based on the three-dimensional warehouse rack layout of the gas valve parts, a multi-objective location allocation optimization model is constructed; the weight coefficients of each objective function in the multi-objective location allocation optimization model are determined; the improved mycelium growth optimization algorithm is used to solve the optimal solution of the location allocation corresponding to each objective function; a multi-objective evaluation function is constructed in combination with the weight coefficients of each objective function and the optimal solution of the location allocation corresponding to each objective function, and the improved mycelium growth optimization algorithm is used to solve the multi-objective evaluation function, so as to obtain an optimal location allocation scheme. The IFGO algorithm is used for location allocation in the application, and the constructed objective function is used to realize the optimization of the location allocation target, so that the premature convergence of the algorithm can be effectively avoided, more diversity in the population can be maintained, and therefore a more innovative location allocation scheme can be found.

Systems and methods for generating a business planning recommendation for a project may include generating weighted location metrics based on location metrics, generating a location allocation decision based on the weighted location metrics, wherein the location allocation decision includes an allocation of a percentage of the project to house at each location of at least two locations of an enterprise, generating weighted sourcing metrics based on sourcing input parameters, generating a sourcing allocation decision based on the weighted sourcing metrics, wherein the sourcing allocation decision includes an allocation of a percentage of the project to source internally within the enterprise and externally outside the enterprise, and generating a business plan recommendation including a location and sourcing allocation decision for each location based on a combination of the location allocation decision and the sourcing allocation decision.

The invention provides a warehouse-in and warehouse-out dynamic allocation method and system for a medicine warehouse, and relates to the technical field of inventory management. The method comprises the following steps: firstly, acquiring an initial task set, and determining a predicted job density according to the initial task set; secondly, according to the predicted operation density and the real-time carrying information, a dynamic effective period threshold value is determined; secondly, for each ex-warehouse task, determining a first candidate goods allocation set according to the dynamic expiry date threshold value and the specification of the corresponding medicine; generating a corresponding goods allocation scheme according to attribute information in the first candidate goods allocation set; calculating evaluation parameters of each goods allocation scheme, and determining a target goods allocation combination according to the evaluation parameters; and finally, according to the target goods allocation combination, generating a goods allocation scheduling instruction and updating real-time carrying information. According to the technical scheme provided by the invention, multi-objective optimization of the ex-warehouse efficiency, the inventory turnover and the storage resource utilization is realized, and the overall response efficiency and the inventory turnover quality of a complex and dynamic storage environment are also improved.

The application discloses a data migration method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of storage. The target storage type can indicate a storage mode of data, the target strip size can indicate the length of reconstructed data, and the total quantity can indicate a position allocation mode of data in a storage array. In order to reduce the data migration amount, a first starting address and a first space length of an effective storage space in an original storage array can be acquired, so as to determine the position of effective data. Further, based on the target strip size, the first starting address and the first space length can be adjusted to obtain target position information, so that the space length of a target task space indicated by the target position information is an integer multiple of the target strip size. Finally, based on the target strip size, the target storage type and the total quantity, data of the target task space can be completely migrated to a target storage array, and the migration efficiency can be greatly improved.

The invention relates to the technical field of warehouse logistics management, and discloses a warehouse container automatic operation method and system based on a three-dimensional mechanism. The method comprises the following steps of: counting characteristic parameters of an operation scene, calculating a target weight when the characteristic parameters continuously exceed a threshold value, obtaining a weight on that day according to five-day linear interpolation smooth transition, scoring candidate storage locations according to the weight on that day, selecting an optimal storage location, and selecting an optimal crane by integrating optimal scheduling of a moving distance, operation time and a queue length. According to the invention, the adaptive capability of the storage location allocation decision to the scene change, the smoothness and strategy continuity of the weight adjustment process, and the weight configuration convergence and operation efficiency optimization effect based on feedback correction are improved.

The application discloses an intelligent goods location pre-allocation method and system based on a four-layer closed-loop management architecture. The intelligent goods location pre-allocation method comprises the following steps: a feedforward guidance layer encodes physical world constraints into a structured rule set with rigid / flexible separation and injects the structured rule set into the decision-making context of an AI agent; the AI agent outputs a goods location pre-allocation scheme with a unified confidence; a feedback sensing layer collects actual execution deviations; a self-correction layer automatically selects a correction mode from parameter fine-tuning, strategy rollback and complete re-planning according to a double-threshold three-mode mechanism; an upper system fallback gating layer automatically switches to a default algorithm of an upper system when the unified confidence is lower than a threshold; and a full-link observable layer records data throughout the whole process for auditing. Through the four-layer closed-loop management architecture, the application solves the technical problems of lack of physical constraint guarantee, closed-loop correction capability and full-automatic operation safety when the AI agent is directly applied to goods location allocation, and is suitable for pure single-deep, pure double-deep and mixed three types of goods shelf architectures.

Techniques are disclosed for mapping an indoor space using light fidelity (Li-Fi) communication. An entity may obtain location information for a plurality of Li-Fi devices, that includes at least one mobile Li-Fi device. The entity may determine, based on the location information, a mapping of the indoor space, where the mapping comprises spatial information for one or more continuous areas of the indoor space based on LOS Li-Fi communication between Li-Fi devices of the plurality of Li-Fi devices. The entity may be a Li-Fi device or a server. The entity may assign locations of Li-Fi devices in LOS communication with each other to the same continuous area to help determine the mapping.

The invention relates to the technical field of warehouse management, in particular to a comprehensive management method and system for an ERP warehouse, and the method comprises the steps: collecting storage multi-source data, and generating a structured data set through standardized preprocessing; based on the structured data set, initial storage location allocation parameters are obtained through a multi-parameter weighted adaptation algorithm, inventory early warning parameters are obtained by combining a sequential anomaly correction and threshold derivation algorithm with the initial storage location allocation parameters, and high-precision management and control parameters are generated through target screening; constructing a storage full-process execution model based on the high-precision management and control parameters, and outputting a service operation result; according to a service operation result, judging abnormity through a dynamic verification algorithm, and generating a parameter correction instruction and system optimization data; and inputting the high-precision management and control parameters, the system optimization data and the warehousing service scene label into the collaborative management model, and outputting a warehousing management strategy adaptive to the scene. According to the scheme, a scientific and quantitative storage location distribution mechanism is constructed, so that the operation efficiency is improved.

This invention discloses a method for dynamic warehouse location allocation based on location heat analysis, belonging to the field of intelligent warehouse management technology. The method includes: Step 1: collecting location coordinates, product attributes, historical and current order data; Step 2: calculating the real-time demand heat of products and shelf location heat based on current orders, and coupling them to obtain location coupling heat; Step 3: constructing a dynamic equilibrium model with the goal of maximizing total location coupling heat and optimizing the estimated picking path, and solving to output a location allocation scheme; Step 4: executing allocation and picking tasks, collecting actual operation data, and feeding back to correct the heat calculation model to achieve closed-loop optimization. This invention solves the coupling conflict between static location allocation and dynamic order picking, realizes the linkage decision-making between location optimization and path planning, and can adapt to order fluctuations and changes in the operating environment, significantly improving warehouse operation efficiency.

In one aspect, a method of determining a location of a user within an indoor space, includes emitting a radiofrequency signal into the indoor space, receiving backscattered training radiofrequency signals, including multipath, for at least one location within the indoor space, converting the received training signals into a point cloud for each location of the at least one location, assigning a signature for each location based on the point cloud for each location, receiving additional radiofrequency signals, including multipath, converting the additional radiofrequency signals into an additional point cloud, and determining a location of the user by comparing the additional point cloud to the assigned signatures.

The application discloses a warehouse location dynamic management method and system based on RFID and two-dimensional code double identification, and relates to the technical field of warehouse location management. The method comprises the following steps: calling a historical order sequence and a real-time order sequence; obtaining a plurality of elastic warehouse location units based on elastic warehouse location allocation according to storage convenience; deploying a plurality of RFID warehouse location identification tags; in a storage cross-warehouse location dynamic storage process in response to the real-time order sequence, performing plate single identity process data writing and writing of the plurality of RFID warehouse location identification tags; in a processing process of the real-time order sequence, performing space matching verification on a multi-angle image of warehouse-in remaining materials to update wear-resistant two-dimensional code tags and refresh associated storage information of the plurality of RFID warehouse location identification tags. The technical problem that the warehouse location management in the prior art is difficult to dynamically adjust according to order conditions, resulting in low warehouse scheduling efficiency, is solved, and the technical effect of improving warehouse scheduling efficiency is achieved.

The invention relates to the technical field of artificial intelligence, and discloses an intelligent warehouse management method and system based on artificial intelligence. The method comprises the following steps: acquiring accurate cargo coordinates, and constructing a first correlation degree matrix based on the accurate cargo coordinates and each free cargo allocation coordinate; updating a goods allocation occupation state matrix according to the first correlation degree matrix, generating a first AGV scheduling sequence, and generating a target path by taking the accurate goods coordinates in the first AGV scheduling sequence as a target position; calculating the planning redundancy of the target path and calculating the real-time positioning deviation; and when the real-time positioning deviation exceeds the planning redundancy, updating the first goods allocation weight to obtain a second goods allocation weight, correcting the first association degree matrix by using the second goods allocation weight, and re-executing goods allocation distribution to obtain a second AGV scheduling sequence. According to the invention, the cargo positioning information is improved from pure position sensing to a core variable for driving warehousing decision making, and the operation efficiency and environmental adaptability of the intelligent warehousing management system are improved.

An asset queuing system, whether it be for a data center system or power generation system or otherwise shared resource of pooled assets, including both a dynamic pricing system and billing system, to dynamically reallocate tasks inclusive of computational tasks being performed on computational asset or electricity production on a power generation system with queuing and location placement amongst proximity locations based at least in part on valorization of operational byproducts. The system controls queuing of assets and tasks specifically accounting for variations of time of day or seasonal by combining feedforward and feedback loop control system as a function of revenue derived by the operational byproducts in addition to dynamic placement of primary asset task and assets into an extended network of multiple proximity locations.

The invention discloses a whole vehicle garage location distribution system and method, and belongs to the field of warehouse management. The system comprises a multi-level data mapping module which is used for abstracting a physical warehouse into a warehouse-warehouse area-warehouse location three-level digital twinborn model and synchronizing a warehouse location state in real time to form a dynamic capacity pool; the virtual capacity expansion module is used for setting a virtual warehouse which is logically equivalent to the physical warehouse so as to realize capacity expansion of the physical warehouse; the configurable strategy engine is used for storing and configuring a vehicle warehousing strategy based on the strategy tree structure; and the real-time distribution module is used for obtaining the target parking space of the vehicle by traversing the strategy tree after the vehicle off-line signal is triggered. According to the invention, high flexibility, real-time performance and expandability of a whole vehicle parking space distribution rule are realized, and a whole vehicle parking space distribution system which is pluggable in strategy, flexible in capacity and real-time in calculation is provided.

The invention discloses an informatization management system for warehouse logistics, and belongs to the technical field of informatization processing. Comprising a warehouse main data management module used for managing warehouse information, warehouse area information, warehouse location information, a warehouse location template, platform information, stacker information and a goods collection route; the business main data management module is used for managing cargo owner information, material information, business partner information, packaging information, a batch attribute template and business parameters; and the rule management module is used for managing a quality inspection rule, a positioning rule, condition configuration, distribution logic global assignment, a package distribution rule, a storage location distribution rule, a bar code analysis rule, a UDI verification rule, a wave plan rule and a replenishment rule. And during material information management, corresponding packaging information, a batch attribute template, a quality inspection rule, a bar code analysis rule, a UDI verification rule, a positioning rule, a storage location distribution rule, a replenishment rule and storage area information are selected, and owner information and material information are received from the MDC.

The invention relates to the technical field of inventory monitoring, and discloses an inventory access real-time monitoring method and system based on RFID scanning. Comprising the steps that unique identification information of warehoused goods is acquired through an RFID scanning device, and multi-dimensional attributes of the goods are extracted in combination with a goods attribute database to form a comprehensive data set; calling a goods allocation information base to screen available goods allocation meeting conditions, generating a preliminary candidate list, and adjusting the priority of the goods allocation; determining a final distributable goods location subset through goods compatibility judgment, and selecting an optimal recommended goods location based on location and path parameters; and updating the goods location information base, generating a distribution instruction, and transmitting the distribution instruction to an automatic carrying system to complete goods storage location dynamic matching. According to the method, the accuracy of inventory access monitoring can be improved, and the rationality and the high efficiency of goods allocation distribution are guaranteed.

This invention discloses a method and related equipment for precise outbound storage location allocation based on customer freshness constraints. By combining the dual constraints of customer freshness and outbound time window with precise matching of specifications and tracking information, this invention achieves direct location of order lines to storage locations, significantly improving positioning accuracy and picking efficiency. It defines outbound time windows based on the customer's historical outbound year and week, guiding the system to prioritize the allocation of tires whose production year and week are closest to the customer's most recent outbound year and week, avoiding mismatched outbound new and old tires, ensuring that storage location allocation matches the customer's actual outbound needs, and improving inventory turnover. It employs a greedy algorithm combined with a pre-sorting mechanism to directly output the optimal storage location without complex iterations, greatly improving outbound efficiency. A built-in dynamic update mechanism ensures that the allocation scheme is updated in real time as data changes, maintaining optimal performance. A unique emergency allocation mechanism can quickly provide feasible alternatives when no perfectly matching storage location is available, ensuring order fulfillment efficiency.

The invention relates to the technical field of warehouse logistics automation, and particularly discloses a deep learning warehouse location intelligent distribution method and system, and the system comprises a data perception fusion module, a spatial-temporal feature extraction module, a multi-target decision module and a dynamic execution feedback module. Commodity relevance and storage location accessibility are modeled by using a graph neural network and a time sequence convolutional network, sorting efficiency, storage area load balance and real-time adaptability are optimized by using a multi-objective evolutionary algorithm, dynamic optimization and adaptive adjustment of storage location allocation are finally realized through closed-loop feedback, and the overall efficiency of storage operation is effectively improved.

The invention provides a server position distribution method, electronic equipment and a storage medium, and relates to the technical field of server position distribution, and the method comprises the steps: for any to-be-distributed server QW, determining a CPU utilization rate corresponding to each preset moment in an operation cycle of the QW; determining server power corresponding to each preset moment in the operation cycle of the QW; determining a CPU temperature determination model corresponding to the QW at each preset moment; determining a model according to the server power corresponding to each preset moment of the QW in the operation cycle and the CPU temperature, and determining the CPU temperature corresponding to each preset moment of the QW in the operation cycle; according to the server power and the CPU temperature of each to-be-allocated server at the same preset moment, allocating each to-be-allocated server to a corresponding cabinet; according to the invention, cabinet resource waste and energy redundancy are avoided, risks of local overheating and the like can be avoided, and the space and heat dissipation resources of the cabinet are utilized to the maximum extent.

A method for commissioning an electromechanical locking device at a location, with the locking device includes an electronic identifier, and with the method having the following steps: receiving a location-specific user input by a, in particular mobile, device for defining the location in particular, with the receiving taking place by performing the location-specific user input on the device, assigning, in particular initially assigning, the identifier to the defined location to form an ID location assignment, subsequently sending the ID location assignment by the device to a computing unit.

An order picking location assignment method, a put wall and an electronic device, which are used for reasonably assigning picking positions to orders and improving order picking efficiency. The method comprises: on the basis of the frequency of appearance of items to be picked in orders to be picked, calculating the degree of hotness of each item to be picked; on the basis of the degrees of hotness of the items to be picked, selecting from among the orders to be picked the hottest order as a seed order, the seed order containing a great number of hot items to be picked; and, on the basis of the similarity between each order to be picked and the seed order, assigning picking locations. The present application can concentrate as much as possible picking locations of hot items to be picked, helping to reduce the workload of transferring the items to be picked and improving picking efficiency.

The invention provides a public facility layout method and system based on user preference and behavior simulation, and the method is technically characterized in that the method comprises the steps: obtaining the facility selection preference of a user through a narrative preference questionnaire, and describing the influence of each element on a selection behavior through a discrete selection model; a selection probability prediction model is established in combination with overall or sub-crowd parameters; simulating a facility selection pattern of a demand point through a Monte Carlo method, taking average utility maximization as a core optimization target, and adopting a genetic algorithm to realize iterative search of facility positions to obtain an optimized layout scheme meeting efficiency, fairness and multi-dimensional demands; matching relation analysis and index calculation of utility, distance, coverage rate and the like are carried out on the result, and a visual scheme is output, so that the defects that a traditional position-distribution model only considers the distance, ignores individual differences and depends on candidate points can be overcome, and a scientific and reasonable optimization tool is provided for public service facility planning.

Systems and methods are provided for automatically generating prioritized, color-coded tasks based on user input received through a conversation interface of a task management application. User input provided to an automated software assistant is analyzed along with contextual data from multiple sources, including existing tasks, calendar events, emails, and messages. The system determines task attributes such as title, status, deadline, geographic location, urgency, and frequency, and assigns a color tag based on color assignment parameters including task category, priority, and location. Machine learning algorithms analyze historical user-assigned colors in relation to task attributes to predict color assignments for new tasks and establish intelligent color relationships, thereby dynamically updating a prioritized, color-coded task list displayed in a graphical user interface.

This invention discloses a cold chain intelligent storage allocation system based on a dynamic logical grid. The system includes: a grid adaptive generation module for dynamically determining the width of logical grid cells and virtually dividing shelves based on historical data; a heat prediction module for predicting the heat level of products; a location allocation engine for performing multi-objective weighted scoring on idle grid intervals based on space compactness, heat zone matching degree, and expiration urgency to select the optimal storage location; and an inventory binding and automated interaction module for associating information and generating equipment instructions. This invention eliminates the need for physical tracks and achieves dynamic, high-precision adaptation and intelligent allocation of cold chain product storage space through a pure software system, significantly improving warehouse space utilization, storage and retrieval efficiency, and expiration management level.