66 results about "Flexible scheduling" patented technology

The invention relates to a multi-data center elastic scheduling method, which comprises the following steps of: establishing a data center polymer (DCA) to integrate the space-time regulation potential of a dispersed data center, establishing a comprehensive model covering dynamic migration of a working load, power consumption regulation and control of a DVFS (Distributed Valve File System) and collaboration of an optical storage system, and adopting a double-layer elastic scheduling architecture, energy storage charging and discharging, photovoltaic output and other hyperopia actions are optimized to improve long-term decision robustness; and the lower layer solves short view actions such as server scheduling and load distribution in real time based on mixed integer linear programming to realize instant cost optimization, so that power-computing power collaborative scheduling optimization of the data center is realized. According to the method, flexible scheduling of time delay sensitive type and time delay tolerant type workloads is combined, the cooperative effect of an energy storage system and photovoltaic power generation is utilized, the power use efficiency and economical efficiency of the data center are optimized, and dynamic participation of multiple data centers in the power market is achieved.

The invention relates to the field of intelligent manufacturing and production scheduling, and discloses a heater assembly line flexible scheduling method based on production data, and the method comprises the steps: S1, obtaining the production data of a heater assembly line and corresponding environment parameters; initializing an assembly line scheduling constraint condition; wherein the assembly line scheduling constraint condition is used for defining a processing time range, an equipment load threshold value and a material supply period reference value allowed by each process in the heater assembly process; s2, if the environmental parameters exceed a preset safety threshold, dynamically correcting the real-time production data according to the environmental parameters to obtain corrected real-time production data; wherein the environment parameters comprise temperature, humidity and air cleanliness, the scheduling effect evaluation model and the association rule mining algorithm are introduced, the production efficiency improvement rate, the equipment failure rate reduction degree, the material waste reduction amount and the like can be quantitatively evaluated, and the influence relation of the key equipment operation parameters on the scheduling effect is mined.

The invention discloses an elastic scheduling method and system for a power grid based on a dynamic security domain, and relates to the technical field of elastic scheduling methods, and the method comprises the steps: determining the boundary of a non-key constraint based on an elastic adjustment factor, a power grid operation event corresponding to the power grid, and a plurality of constraints; the corresponding optimization event is determined according to the dynamic security domain, the boundary of the non-critical constraint and the real-time working data of the power grid, and the elastic scheduling system of the power grid is determined based on the optimization event, the real-time load data of the power grid and the corresponding real-time power supply data, so that the accuracy of the elastic scheduling system of the power grid is improved; and the elastic scheduling effect of the power grid is further improved. Therefore, the plurality of sub elastic scheduling projects are determined according to the identification of the elastic scheduling mode, the power optimization event of the power grid is determined based on the project content of each sub elastic scheduling project, the corresponding project position and the real-time load data of the power grid, and the accuracy of the online optimization logic of the power grid is ensured.

The invention discloses an optimal scheduling method for a virtual power plant, and relates to the technical field of power regulation, and the method comprises the steps: obtaining multi-modal data of a detection region, calculating a regional load fluctuation index and a resource mobility index, and generating a dynamic feature data set; performing real-time clustering division on the power grid nodes through a clustering algorithm based on the dynamic feature data set to generate a dynamic sub-region set; if the sub-region feature fluctuation exceeds a boundary stability threshold value, triggering boundary redivision; according to the dynamic sub-region set, comparing a building power consumption predicted value with the available load of the charging pile in real time to calculate a demand difference, and generating an elastic scheduling instruction through multi-objective optimization; uncertain factors are monitored in real time, a risk index is calculated, and the priority and the resource allocation strategy of the elastic scheduling instruction are dynamically adjusted based on the risk index; and generating a risk avoidance scheduling scheme through a robust optimization algorithm.

The application provides a flexible scheduling group and a scheduling method. The scheduling group comprises a manufacturing execution system, a logistics execution system, an intelligent group control system, a logistics intelligent trolley scheduling system and a process intelligent trolley scheduling system. The intelligent group control system receives a production plan issued by the manufacturing execution system, receives inventory material information of the logistics execution system, receives vehicle position information of the logistics intelligent trolley scheduling system and the process intelligent trolley scheduling system respectively, and formulates scheduling tasks of the process intelligent trolley and the logistics intelligent trolley in real time. Through deep cooperation of the intelligent group control system with the manufacturing execution system, the logistics execution system and other systems, overall management of the whole production process is realized. Through real-time sensing of data of environmental changes and / or data of demand fluctuations by the intelligent group control system, and through on-demand pulling, the coordination and stability of line operation are improved through cooperation with multiple systems.

This invention discloses a method and system for optimizing game resources in a virtual game. The invention relates to the technical field of virtual games. It loads the current load of the virtual game based on a target resource demand sequence and constructs the resource distribution of the virtual game. Then, it performs topological clustering based on the content to be loaded in the virtual game, generating a resource topology map containing multiple game resource clusters, thus improving the accuracy of the resource topology map. The node dependencies in the resource topology map are marked, and flexible scheduling is performed based on the resource content allocated to each resource cluster, thereby outputting a multi-level flexible scheduling strategy. The high-speed video memory area and low-speed memory area of ​​the virtual game are optimized along this flexible scheduling strategy. Resource optimization events of the virtual game are determined based on the smooth constraints of the virtual game. Furthermore, resource anomaly signals of the virtual game are used to determine optimization configuration measures for the high-speed video memory area and low-speed memory area in terms of resource dimensions, improving the accuracy of the optimization configuration measures.

This invention discloses a flexible scheduling method, system, and application for UPMS (Upright Manufacturing System) workshops based on an improved differential evolution algorithm. The method includes: establishing an independent parallel machine scheduling model with sequentially dependent mold-changing time as the objective of minimizing the maximum completion time; using real-valued vector encoding and decoding it into a scheduling scheme through the maximum position value rule; performing mutation and crossover operations of the differential evolution algorithm on the generated test vectors, with optimizations including load balancing optimization based on destruction and reconstruction and mold-changing optimization based on sequential smoothing; finally, updating the population and outputting the optimal scheduling scheme. This invention significantly reduces sequentially dependent mold-changing time, achieves dual optimization of load balancing and mold-changing cost, and improves solution accuracy and efficiency, making it particularly suitable for discrete manufacturing workshops such as textile printing and dyeing, and injection molding.

The invention discloses a method and a device in a node used for wireless communication and artificial intelligence. A first node receives a first information block, the first information block indicating a first resource block set; transmitting a second information block, the second information block indicating a first resource set from the first resource block set, the first resource set being dynamically scheduled; the first resource block set is determined based on an AI / ML model; the first resource block set comprises K1 resource blocks, K1 is a positive integer greater than 1, and time domain resources occupied by at least two resource blocks in the K1 resource blocks are orthogonal; the first set of resource blocks depends on an ID of the AI / ML model. The dynamic scheduling transmission triggered by the UE is realized, the adaptability and the intelligent level of the communication system are improved, a more flexible scheduling mechanism is supported, and the performance, the efficiency and the user experience of the communication system are further improved.

The invention belongs to the crossing field of shipbuilding and electrical engineering, and discloses a shipbuilding process flexible scheduling method based on adjustable potential analysis and a related device, and the method comprises the steps: responding to dynamic disturbance information, and updating a state task network diagram and a scheduling diagram of a shipbuilding process; according to the updated state task network graph and the scheduling graph of the shipbuilding process, dynamic adjustable potential of each task of the shipbuilding process is obtained by combining the dynamic adjustable potential model of each task of the shipbuilding process; and based on the scheduling constraint optimization model, according to the updated state task network diagram and scheduling diagram of the shipbuilding process and the dynamic adjustable potential of each task, generating a flexible scheduling result of the shipbuilding process. An optimal scheduling path can be selected in a disturbance scene to dynamically generate an adjustment strategy, so that the toughness of a production system is remarkably improved; meanwhile, based on dynamic adjustable potential analysis, the adjustment level and the flexible boundary of each task can be accurately identified, and real-time scheduling optimization and intelligent configuration of the flexible manufacturing system are supported.

The application discloses an edge intelligent body flexible scheduling method based on Lyapunov optimization and Stackelberg game. The application constructs a cloud-edge-end three-layer edge intelligent body federated learning network architecture to complete distributed collaborative training under the premise of protecting data privacy. In view of the problems of heterogeneous edge intelligent body network nodes, non-independent and identically distributed data and limited communication resources, a long-term joint optimization model of client selection and bandwidth allocation is established, and model accuracy, time delay and energy consumption are considered. Lyapunov optimization is used to decouple long-term random optimization into real-time decision-making per time slot, and to convert constraints into virtual queue stability control. Dynamic client selection is realized based on Stackelberg game, and high-quality nodes are adaptively selected. Adaptive bandwidth allocation is completed through an evolutionary algorithm, and communication requirements of key clients are preferentially guaranteed. The application can significantly improve model accuracy, reduce time delay and energy consumption, guarantee long-term stability of the system, and is suitable for high-dynamic edge intelligent body federated learning scenes.

A communication method and device can be applied to the field of satellite communication, such as NTN. The method comprises: a terminal device receiving downlink control information, the downlink control information being used for indicating a scheduling delay parameter K, K being a positive integer; the terminal device starts to send first data from a first time unit, wherein the first time unit is a Kth, or a (K + Koffset) th, or a (K + Koffset-G) th uplink time unit after a time unit n; wherein the time unit n is later than the time unit used for bearing the downlink control information, the Koffset is a predefined or preconfigured time unit number, both the n and the Koffset are positive integers, and the G is the time unit number of the guard band in a frame period. Through the technical scheme provided by the invention, flexible scheduling can be realized.

The apparatus may be a wireless device configured to receive an indication of a single TB scheduled across a plurality of slots and across one of a plurality of sub-bands within a virtual cell or a plurality of component carriers associated with a carrier aggregation, and receive or transmit the TB via the plurality of slots and one of the plurality of sub-bands or the plurality of component carriers. In certain aspects, the apparatus may be a network device configured to transmit an indication of a TB scheduled across a plurality of slots and across one of a plurality of sub-bands within a virtual cell or a plurality of component carriers associated with a carrier aggregation and to transmit or receive the TB via the plurality of slots and one of the plurality of sub-bands or the plurality of component carriers.

The invention discloses a visual injection molding production flexible scheduling method and system, relates to the field of flexible scheduling, and solves the problem that injection molding equipment cannot be efficiently and visually scheduled. The method comprises the following steps: analyzing injection molding completion durations of different injection molding equipment in an injection molding workshop; obtaining to-be-optimized equipment and flat replacement equipment corresponding to different to-be-optimized equipment; defining an actual processing flow of the injection molding product in an injection molding workshop by combining different to-be-optimized equipment; carrying out flat replacement on single to-be-optimized equipment in the injection molding workshop by using flat replacement equipment, and analyzing to obtain first selection numerical values of different flat replacement equipment in different to-be-optimized equipment; simultaneously carrying out flat replacement on a plurality of to-be-optimized devices in the injection molding workshop by using a plurality of flat replacement devices, and analyzing to obtain second selection numerical values of different flat replacement device combinations in different flat replacement object groups; and scheduling the optimal displacement equipment or the optimal displacement equipment combination according to different selection values. According to the invention, efficient visual scheduling of the injection molding equipment is realized.

This invention discloses a multi-timescale coordinated scheduling method and device for low-voltage DC interconnected distribution areas. The invention employs a day-ahead long-term optimization scheduling method to obtain the day-ahead scheduling plan, a day-intraday rolling optimization scheduling method to continuously revise the day-ahead scheduling plan, and a real-time optimization scheduling method to schedule converter power, load reduction power, and electric vehicle quota power. This achieves multi-timescale coordinated scheduling of low-voltage DC interconnected distribution areas, enabling flexible scheduling of controllable resources in the distribution area at multiple time scales, reducing the impact of the randomness of photovoltaic power output, and improving the economy and safety of distribution area operation.

The invention discloses a terminal guidance resource flexible scheduling method and device. The method comprises the following steps: constructing a behavior tree comprising a root node layer, a system level control node layer, a single machine level control node layer, a bottom layer condition and an action node layer from top to bottom; constructing a Bayesian network according to the situation information detected by the aircraft to be decided; the behavior tree determines an intelligent agent corresponding to the aircraft to be guided based on probability distribution of a Bayesian network aircraft implementation countering strategy; determining a guidance control constraint and a detection strategy based on the intelligent agent corresponding to the to-be-guided aircraft, and performing online trajectory planning of the to-be-guided aircraft based on the guidance control constraint; and based on the detection strategy, updating the detection action and situation information of the to-be-guided aircraft. According to the method, situation changes can be sensed more accurately, and the decision accuracy is improved.

The invention provides a timed task processing method and device, equipment and a medium, which are applied to the technical field of computers, and the method comprises the following steps: obtaining a to-be-executed target timed task which is not allocated with a scheduler instance; judging whether the target timed task is within the executive capability range of the current scheduler instance or not; and if the target timed task is within the execution capability range of the current scheduler instance, allocating the target timed task to the current scheduler instance, and starting a coroutine through the current scheduler instance to execute the target timed task at the multiple target physical nodes. Through the embodiment of the invention, the timed task is allocated according to the execution capability of the scheduler instance, the flexible scheduling of the timed task is improved, the coroutine is started through the scheduler instance, and the timed task is executed in parallel at a plurality of target physical nodes, so that the actual execution of the timed task does not block the main cycle of the scheduler instance, and therefore, high concurrency is realized, and the scheduling efficiency is improved. And the scheduling efficiency of the timed task is improved.

The invention discloses a multi-target optimization-based multi-ship dredging intelligent scheduling method, which comprises the following steps of: S1, establishing a computable engineering database based on a channel geological condition and various ship mechanical performance conditions; s2, constructing a construction period-cost-carbon emission multi-target flexible scheduling model; s3, assumed conditions and constraint conditions during flexible scheduling of the channel dredging ship are constructed; s4, an NSGA-III multi-objective optimization algorithm is introduced, a Pareto optimal solution set is formed, and finally a dredging construction ship dispatching set after construction period-cost-carbon emission balance is output; and S5, selecting a construction period-cost-carbon emission weight ratio based on the AHP, and outputting an optimal field scheduling solution so as to obtain a final dredging scheduling scheme. According to the method, the problem that the construction period, cost and carbon emission of channel dredging engineering are difficult to balance is solved, intelligent, multi-target coordination and dynamic optimization control of the whole dredging construction process are achieved, and the cost, the construction period and the carbon emission level of the whole construction process are reduced.

The invention discloses a shared service time slot resource allocation method, system and device and a medium, and particularly relates to the technical field of communication networking, and the technical key points are as follows: responding to an allocation request of at least one time slot request node, and based on the service priority and service type of each time slot request node, allocating a time slot resource to the time slot request node; sequencing the priority of the at least one time slot request node to obtain a node sequence; service transmission information and time slot information of all the time slot request nodes are acquired, and the time slot application number of all the time slot request nodes is calculated; and obtaining time slots occupied by completed services of all nodes at the current request moment, and sequentially allocating time slot resources of respective time slot application quantity to each time slot request node according to the node sequence. Users with high priorities can preferentially recover services, the influence degree of abnormal conditions is reduced, and the resource utilization rate and the service stability are improved; management is carried out through a dynamic time slot distribution mode, and sharing and flexible scheduling of time slot resources among nodes are achieved.

The application provides a task processing method and device, which are applied to a terminal. The task processing method comprises the following steps: acquiring sequence state information of a to-be-processed task sequence, and determining a current query frequency according to the sequence state information, wherein the order of each to-be-processed task in the to-be-processed task sequence is determined according to priority information corresponding to each to-be-processed task; a current to-be-processed task is acquired from the to-be-processed task sequence based on the current query frequency; a target processing strategy of the current to-be-processed task is determined according to available resource information corresponding to the terminal; and the current to-be-processed task is processed according to the target processing strategy. The application implements a dynamic flow limiting strategy, can distinguish the priority of to-be-processed tasks, and realizes flexible scheduling and adjustment of to-be-processed tasks in the case that the importance of to-be-processed tasks is different and resource occupation is different, thereby improving the resource utilization efficiency of the terminal.

The invention discloses a 5G network slice security isolation system and a 5G network slice security isolation method oriented to multiple service scenes, provides a unified security isolation framework covering a computing layer, a storage layer, a network layer and a management layer, forms top-down policy distribution and a bottom-up feedback mechanism, and realizes integrity and consistency of end-to-end isolation. According to the method, slice service requirements are abstracted into requirement vectors, differentiated network slice isolation strategies are carried out according to the requirement vectors, and different service slices can still meet respective performance and safety requirements in the same physical infrastructure; meanwhile, the performance index and the security situation of each slice are monitored in real time in the operation period, and once the slice state is found to deviate from an expected target, the system can automatically trigger resource adjustment, flow rerouting or priority adjustment, so that the isolation strategy has dynamic adaptability and flexible scheduling capability.

The invention discloses a quantum block chain-driven highway intelligent energy transaction and adaptive scheduling method. The method comprises the steps of deploying renewable energy power generation, energy storage, charging and discharging, vehicle condition and environment sensing and edge nodes along a highway; the edge node collects data in real time and writes the data into the block chain, and the quantum optimization scheduling module operates a quantum approximate optimization algorithm to output an optimal scheduling scheme to the smart contract; the intelligent contract automatically matches two-way energy transaction between the vehicle and the station, settles awards and records and links the awards; the cross-regional cluster completes regional A-B energy transaction and settlement through an intelligent contract; the edge nodes continuously monitor energy storage temperature, power and communication delay, fault early warning is triggered when a threshold is exceeded, an intelligent contract starts a standby mechanism to dispatch energy storage and electric vehicle feedback electric quantity, and whole-process data is linked for evidence storage. Quantum calculation, the block chain and the V2G are fused, efficient, transparent, safe and flexible scheduling of highway infrastructure energy is achieved, the green energy utilization rate and the system sustainability are improved, and the method is suitable for highway energy management.

This invention discloses a visualized flexible scheduling method and system for machining production, relating to the field of production scheduling technology. The method includes: obtaining machining machine groups and the machining coordinate system of each machining machine group based on the process machines of all core processes; obtaining the first span machine of schedulable parts and all process machines based on simulated machining; and performing flexible scheduling using a multi-machine scheduling method. This invention addresses the problem in existing flexible scheduling methods for machining production where, when there are many types of machining machines in the workshop and multiple processing routes for parts, the numerous possible equipment combinations in case of machine failure lead to poor timeliness or local optima after rescheduling the machining machines, thus preventing the most efficient flexible scheduling of parts.

The application discloses a 6G all-in-one network management computing power session method and system, and belongs to the technical field of mobile communication.The technical problem to be solved by the application is how to realize flexible scheduling and on-demand allocation of computing power and network fusion resources in a 6G all-in-one network environment without changing network devices, and to build a mobile network environment supporting the computing power as a service mode for users.The technical scheme adopted is that the method is to deploy an algorithm network fusion perception network element, an algorithm network fusion control scheduling network element and an algorithm network fusion service arrangement network element on the core network side, so that the improved core network has the functions of communication, perception and computing power integration;and the computing power application request index is analyzed and identified, the computing power service arrangement is performed, the computing power and network Qos configuration mapping is performed, the algorithm network fusion resources are decided and scheduled, and the distributed collaborative computing task is issued, so that the computing power session creation is completed, so as to meet the different computing power requirements of mobile terminals.

This invention relates to the field of outbound logistics and discloses a method, apparatus, equipment, and medium for outbound avoidance in a warehousing and logistics system. The method includes: when several hangers awaiting outbound are currently in an idle state and not in a prohibited outbound time interval queue, calculating the total outbound time for each hanger; obtaining the outbound timestamp of the first hanger and, combined with the total outbound time, calculating the outbound timestamp of the last hanger; updating the current storage bar to an outbound state, and calculating the avoidance time intervals for other storage bars based on the outbound timestamps of the first and last hangers and the track running speed, adding them to the corresponding prohibited outbound time interval queues; issuing an execution command to cause the current storage bar to perform a mechanical action, and after execution, updating it to an idle state. This achieves outbound avoidance functionality, is easy to execute and manage, has low cost, and allows for flexible scheduling without hanger data limitations during a single outbound process, making the entire process efficient and simple.

This application provides a license scheduling method, system, storage medium, and electronic device, relating to the field of cloud service technology. The technical solution provided in this application determines the degree of license stability required by the current license request and allocates it to a static license pool or a dynamic license pool. The first license sequence in the static license pool has a lower license switching frequency, providing users with long-term stable license guarantees and avoiding frequent license opening and closing operations that disrupt user workflows. The second license sequence in the dynamic license pool allows for a higher license switching frequency to improve the utilization efficiency of license resources. Through this dual-pool separation and differentiated scheduling mechanism, the system ensures both the continuity of licenses and work stability for users with high stability requirements, while also enabling flexible scheduling and efficient resource utilization for users with low stability requirements. It can adopt targeted scheduling methods based on users' stability needs, thereby improving user experience.

The invention discloses an optimal control method for a double-track cache machine. The method comprises the following steps: generating a board width heat map according to a board width frequency distribution model; generating a candidate switching window prediction list; forming an optimized input vector; setting plate width constraint, cache constraint and mechanism action constraint; quickly generating a first candidate switching strategy set; calculating a comprehensive performance index of each candidate switching strategy; generating a new candidate switching strategy set to avoid local optimal retention; and the double-track cache machine is driven to complete track mode switching according to the target switching window, and the cache proportion, the lifting layer position, the width adjusting width, the clutch conveying speed and the plate distance are synchronously adjusted according to instructions. According to the method, the track mode switching opportunity can be dynamically optimized according to the incoming material plate width change trend, beat loss, congestion and utilization rate reduction caused by switching lag are effectively avoided, and the flexible scheduling capacity and the production line comprehensive efficiency of the double-track cache machine in the variable production environment are improved.

This invention discloses a virtual power plant system scheduling method based on deep reinforcement learning, belonging to the field of power energy optimization management technology. The method includes: collecting multi-source real-time data from the virtual power plant; constructing a causal graph model and generating causal feature vectors and adjacency matrices; inputting the causal feature vectors and adjacency matrices into a reinforcement learning framework, performing enhancement processing through a causal attention mechanism to generate an optimized scheduling strategy; extracting economic and safety objective function values ​​from the optimized scheduling strategy, constructing a multi-objective optimization problem, and using gradient descent to track equilibrium points and obtain a flexible scheduling scheme; inputting the flexible scheduling scheme into a high-fidelity digital twin model, performing behavioral risk detection during simulation operation, and outputting a risk report and correction parameter vectors. This invention achieves a leap from statistical correlation analysis to causal reasoning, solving the problem of blind spots in scheduling decisions under high-dimensional uncertainty.