16results about How to "Solve scheduling problems" patented technology

The invention provides a gravity energy storage device with a function of uninterruptible loading and unloading of weight blocks, the gravity energy storage device comprises a transportation module and a loading and unloading module, the transportation module comprises a rotating wheel part, a chain part and a bearing mechanism, the bearing mechanism is arranged on the chain part, the rotating wheel part is arranged at the end part of the transportation module, and the chain part moves around the rotating wheel part; the loading and unloading module comprises a conveying channel, a supporting mechanism and a weight block body, the supporting mechanism is arranged on the conveying channel, the weight block body is arranged on the supporting mechanism through driving of the conveying channel, and the supporting mechanism and the bearing mechanism can be coupled or decoupled to drive the weight block body to be separated from or connected with the supporting mechanism. According to the gravity energy storage device with the function of uninterruptible loading and unloading of the weight block, stable and continuous electric energy can be generated during power generation and energy storage under the condition that the device is uninterruptible when the weight block body is loaded and unloaded and the transportation module generates power, and under the condition that equipment does not need to be added, the power generation power and the operation efficiency are improved, and the cost is reduced.

The invention discloses a reservoir group scheduling interval multi-target optimization method under an uncertain condition, and belongs to the technical field of reservoir optimization scheduling. The method comprises the following steps: firstly, establishing an innovative cascade reservoir group interval multi-target scheduling model; secondly, providing a double-population dynamic coordination interval optimization method for solving the interval multi-target scheduling model, and further obtaining an optimal scheduling scheme of the reservoir group; and finally, outputting an optimal scheduling scheme set of the reservoir group. According to the optimization method, through organic combination of a chaos-order mapping initialization strategy, a dynamic adaptive mutual promotion updating strategy and an elite guidance optimization strategy, optimization is rapidly and efficiently carried out to obtain a group of reliable and accurate scheduling scheme sets considering runoff uncertainty; an effective decision-making technical means for solving the cascade reservoir group optimization multi-target complex engineering problem is provided for a scheduling decision maker, the intelligent level and comprehensive benefits of water resource management are improved, and the capacity of a water resource system for coping with complex environments and uncertain factors is further enhanced.

The invention discloses a collaborative resource scheduling method and system based on a programmable network. The method comprises the following steps: performing performance modeling on heterogeneous computing resource data in all computing resource data to obtain a uniform resource performance index; defining target computing resource data required by multi-dimensional resource demand services, and determining matching relationship information between each multi-dimensional resource demand service and the current computer cluster; in the deployment process, according to all the matching relation information, the correspondingly selected multi-dimensional resource demand service is deployed to each computer cluster; determining a shortest deployment path between the routing nodes in each computer cluster based on a Floyd algorithm; and in the actual scheduling process, executing the computing power arrangement scheme generated in the deployment process. According to the collaborative resource scheduling method and system based on the programmable network provided by the embodiment of the invention, the utilization rate of computing power resources in a wide area network can be improved, and a computing power scheduling strategy is dynamically generated.

The invention discloses an integrated offshore wind power jacket foundation grouting operation platform and a grouting operation method thereof. The operation platform comprises a main body frame with a horizontally arranged platform plate, and a through hole is formed in the center of the platform plate; a grouting raw material storage area, a grouting equipment placement area, a grouting preparation area and a grouting operation area are sequentially arranged at four edge positions in the circumferential direction of the platform plate; two cement-based grouting material storage boxes are fixed in the grouting raw material storage area; a grouting tool container, a generator set container and a diving tool container are fixed in the grouting equipment placement area; two grouting stirring tanks, two fresh water storage tanks and two grouting conveying pumps are fixed in the grouting preparation area, and a crane and a high-pressure flushing machine are arranged in the grouting operation area; according to the operation platform and the grouting operation method thereof, grouting operation can be started after the operation platform is pre-assembled at a wharf and is directly transported and installed at the top of the jacket, the construction difficulty is reduced, the cost is saved, and the construction efficiency and the operation safety are improved.

The invention provides a concrete mixer truck dispatching system and method for continuous concrete pouring. The concrete mixer truck dispatching system comprises a mixer truck module, a pouring point module and a control module. The mixer truck module comprises a forward and reverse rotation module, a Beidou positioning module, a terminal display module and a first network communication module, and the mixer truck module is arranged on a mixer truck; each pouring point module comprises an RFID module, an acousto-optic prompt module and a second network communication module, and the pouring point modules are arranged at all pouring point positions; the control module comprises a cloud server and a control terminal module; the mixer truck module and the pouring point module are connected with the cloud server through the network communication module. Through a mixer truck scheduling algorithm deployed at the control terminal module and related hardware installed at the mixer trucks and the pouring points, statistics of data such as task scheduling of the concrete mixer trucks, the distribution condition of the concrete mixer trucks and the pouring strength of the pouring points can be realized, and the concrete pouring efficiency is effectively improved.

The invention provides an improved grey wolf optimization algorithm for casting heat treatment production scheduling. According to the method, the swarm intelligence and natural heuristic characteristics of the grey wolf optimization algorithm are combined, and the global search capability and the local development capability of the algorithm are enhanced by improving a population initialization strategy, a weight strategy and a nonlinear convergence factor. By optimizing the diversity and weight parameters of the initial population, the algorithm can more effectively solve the complex workshop scheduling problem. The scheduling rule of the production task is analyzed by adopting an optimization algorithm method, and resources and time are reasonably allocated, so that the production efficiency and the product quality are improved. The method is of great significance in improving the flexibility and robustness of casting heat treatment workshop scheduling, and a new path is provided for achieving intelligent production and energy conservation and emission reduction.

The invention discloses a shared vehicle scheduling method and a server. The scheduling method comprises the following steps: receiving a pre-scheduling request sent by a mobile terminal; enabling an application program of the mobile terminal to display the scheduling task group; receiving a scheduling starting request of the mobile terminal; if the target vehicle is located in the vehicle pulling point, the target vehicle is included in a scheduling task group; if the target vehicle is not located in the vehicle pulling point, sending prompt information that the target vehicle is not located in the vehicle pulling point; receiving a scheduling ending request for the target vehicle; the position of the target vehicle is judged, and if the target vehicle is located in the vehicle delivery point, the scheduling request is completed; and if not, sending prompt information that the target vehicle is not in the vehicle delivery point. After the operation and maintenance personnel open the application program of the mobile terminal, the system automatically creates the scheduling task group and displays the scheduling task group in the electronic map, the operation and maintenance personnel can schedule the shared vehicles according to the vehicle pulling points indicated by the electronic map, the scheduling method is simple and clear, operation is convenient, and the operation and maintenance personnel can be rapidly and effectively guided to schedule the shared vehicles.

The present application relates to the technical field of flexible job shop scheduling in intelligent manufacturing and production scheduling, and particularly relates to an optimization method for solving flexible job shop scheduling with adjusted resource constraints. The method comprises the following steps: initializing parameters and randomly generating an initial population; using a crossover operator and a mutation operator in sequence to evolve the current population; executing a hybrid decoding strategy on the current population; sorting the individuals in the current population in ascending order of maximum completion time to form an elite population, and updating the elite population through problem-specific local search; judging whether the evolution condition is met, and if yes, executing mathematical evolution based on CP, and outputting a final solution when the running time reaches the total running time. The present application has the positive effects of reducing resource waiting time, improving machine utilization, and improving the resource utilization efficiency and scheduling performance of the entire workshop production.

This invention discloses a method and system for collaborative optimization of task scheduling and data caching, belonging to the fields of edge computing and mobile network technology. The method includes: constructing an edge computing environment through multiple edge servers, cloud servers, and a data cache; performing service chain-aware matching on arriving tasks within the edge computing environment to reuse computation results; scheduling tasks using a particle swarm optimization algorithm; obtaining a task scheduling scheme based on a comprehensive fitness function and task scheduling; executing the task scheduling scheme to obtain intermediate result data items; evaluating the value of the intermediate result data items using a multi-dimensional evaluation model to obtain a value evaluation result; updating the content of the data cache based on a genetic algorithm and the value evaluation result; and achieving collaborative optimization between repeated task scheduling and data caching. This invention achieves effective processing of tasks combining multiple services through a service chain-aware matching mechanism and establishes a bidirectional feedback collaborative optimization mechanism for task scheduling and data caching.

The invention relates to the technical field of computer visualization, and discloses a mass stratum data scheduling and visualization method, device, equipment and medium, and the method comprises the steps: initializing an LOD model according to user interaction parameters to obtain attribute display parameters, and determining a data display range according to the attribute display parameters; scheduling data block index numbers in a data display range by using a multi-resolution data scheduling algorithm; judging whether a target data block corresponding to the data block index number exists in a buffer area or not; when the target data block exists in the buffer area, displaying the target data block through a display thread; when the target data block does not exist in the buffer area, sending the target data block into the buffer area through the data read-in thread, and returning to the step of displaying the target data block through the preset display thread; and performing data assembly drawing on the displayed target data block to obtain visual stratum data. According to the invention, the efficiency of mass stratum data scheduling and visualization can be improved.

The present invention discloses a method for dividing star clusters and a method for handing over slave satellites in collaboration with multiple star clusters, and relates to the field of space-based detection technology. The specific implementation of the method includes: for each slave star of any star cluster, calculating the first distance from the slave star to the central control center of each star cluster; comparing multiple first distances to determine the minimum value of the first distance; determining the star cluster to which the central control center corresponding to the minimum value of the first distance belongs as the target star cluster of the slave star. This implementation can compare the distances of each satellite in the star cluster relative to the center of each star cluster, determine the optimal star cluster to which the satellite belongs, thereby improving the satellite utilization rate during the execution of observation tasks, and rationally utilizing on-board resources, and the slave satellites between star clusters can be flexibly switched based on the distance relative to the center of each star cluster, so as to observe the observation target, so that the observation effect of the entire star cluster is optimal, and is suitable for various mission scenarios.

The invention relates to the technical field of Internet of Things, in particular to a device access system and method based on dynamic registration, the system comprises a dynamic registration service system and an Internet of Things platform system, the dynamic registration service system is used for obtaining a dynamic registration request sent by a device to be accessed and authenticating the dynamic registration request, the Internet of Things intermediate station system matches a target Internet of Things intermediate station according to the device type and the protocol type of the device to be accessed, and sends scheduling information to the dynamic registration service system; business of a traditional system is separated, the dynamic registration service system is only responsible for registration and authentication of the equipment and does not involve the function of a business level, the traditional business part is separated to a platform system in the Internet of Things to be carried out, the overall safety of the system is greatly improved, and the security of the system is greatly improved. And unified management of devices of different types and different protocols is facilitated.

The present invention belongs to the technical field of cryptographic resource scheduling, and specifically relates to a multi-source and multi-target cryptographic resource scheduling method, including initializing relevant parameters of cryptographic resource nodes and cryptographic task nodes; determining whether each cryptographic resource node is a focus node or a peripheral node, and determining the convergence domain of the focus node; for each cryptographic task node, calculating the single node protection capability, for each focus node, calculating the focus weight; updating the speed of each cryptographic resource node according to the single node protection capability and the focus weight, each cryptographic resource node updates its position according to the calculated speed, and after repeated iterations, finally obtains the optimal position and optimal overall layout of each cryptographic resource node. The present invention can ensure that when a cryptographic resource demand appears at a cryptographic task node, under the condition that the overall protection capability meets the requirements, the cryptographic resources can be deployed to the cryptographic task node in the shortest possible time, and at the same time, there will be no excessive aggregation of multiple cryptographic resource nodes.

The present invention discloses a star-coordinated master star handover method, which relates to the field of space-based detection technology. The specific implementation of the method includes: the current master star in the star cluster generates a master star handover instruction; wherein the master star handover instruction indicates the handover time, the master star identifier of the current master star and the slave star identifier of the master star to be handed over; according to the master star identifier of the current master star and the slave star identifier of the master star to be handed over, the current master star sends the task arrangement information of the star cluster to the master star to be handed over; the current master star receives the first handover response result of the master star to be handed over; when the first handover response result is that the handover is allowed, at the handover time, the current master star switches to the slave star of the star cluster, and the master star to be handed over switches to the master star of the star cluster. This implementation method can flexibly switch the master star of the star cluster based on the distance of each satellite in the star cluster relative to the central control center, the observation task requirements, etc., so as to efficiently and clearly observe the target, so that the observation effect of the entire star cluster is optimized and adapted to various task scenarios.

The invention discloses a natural gas power plant and power system cooperative scheduling method and device, a medium and equipment. According to the method, operation parameters of each natural gas power plant and power demand data of a power system are obtained in real time, a natural gas pipeline network topological graph is firstly constructed, then operation indexes of the power plants are updated through the graph, and the real-time power generation hours are calculated in combination with a preset formula. Then, according to the operation index, the reported data and the number of hours capable of generating power, calculating a declared gas amount surplus and gas consumption early warning information; and finally, the data and the real-time power demand are combined to carry out optimal scheduling on the natural gas power plant. According to the invention, the scheduling accuracy and response speed are improved, and the resource allocation is optimized, so that the problem that the natural gas power plant cannot be accurately scheduled according to the requirements of the power system in the prior art is solved.

The embodiment of the invention provides a scheduling method, device and equipment applied to a large-scale unmanned vehicle cluster, and the method comprises the steps: receiving a frame selection operation instruction for selecting a map region on a map display interface after a frame selection function is triggered, and determining a target map region selected on the map display interface; and determining a target unmanned vehicle in a real area corresponding to the target map area, displaying information of the target unmanned vehicle at a corresponding position of the target map area, and sending an operation instruction to the target unmanned vehicle. According to the scheduling method and system applied to the large-scale unmanned vehicle cluster provided by the embodiment of the invention, a user can intuitively control the unmanned vehicles; moreover, through frame selection instruction operation, a corresponding unmanned vehicle cluster can be selected, and targeted instructions can be sent in batches.