38 results about "Integer programming" patented technology

This invention relates to the field of power system dispatch and control technology, specifically to a multi-day optimal dispatch method for compressed air storage (CASP) energy storage systems (CASPs) oriented towards continuous extreme scenarios. This method proposes operational constraints for CASPs with unit-like combinations, characterizing practical operational constraints such as minimum continuous operating time, start-stop limits, and waiting times for charge / discharge state transitions. Furthermore, this method proposes an optimal dispatch framework for CASPs on a weekly timescale, addressing various types of extreme scenarios. In addition, the method employs a Benders decomposition-based algorithm and linearization techniques to solve the proposed large-scale mixed linear integer programming problem. This invention improves the engineering practicality and dispatch decision feasibility of CASP operation models, fully explores the long-term energy storage value of CASP in addressing energy imbalances in continuous extreme scenarios, and meets the large-scale dispatch needs of power systems.

This invention relates to the field of container loading optimization technology, and particularly to a container loading optimization method and system considering palletizing. The method includes setting container information, palletizing constraints, and cargo information; generating available pallet sizes and corresponding stack shapes; eliminating stack shapes with bottom coverage below a threshold; using the selected stack shapes to form transverse pallets that meet preset requirements; establishing a mathematical model and solving it using integer programming to obtain an initial loading scheme; performing mixed pallet loading on the remaining container space and remaining cargo, ensuring that the mixed pallet loading meets the requirements of full pallet coverage and full support; generating the mixed pallet loading result and a three-dimensional visualization model. This invention incorporates the entire palletizing-related calculation process into the optimization algorithm to solve the technical problems of cumbersome, inefficient, inaccurate, poor space utilization, and high labor costs in existing container loading calculation processes.

The application discloses a vehicle heat and electricity comprehensive energy system power dispatching method and device, equipment and medium, wherein, the method comprises the following steps: establishing a node model of each part working node in the vehicle heat and electricity comprehensive energy system; determining the power capacity constraint, state constraint, climbing constraint and balance constraint of each part working node, taking the system maintenance cost as the objective function, and solving each part working node power configuration meeting the load requirement and minimum cost by using a preset mixed integer programming method in each preset dispatching period; and generating the optimal power dispatching strategy of the vehicle heat and electricity comprehensive energy system based on the power configuration of each part working node. Thus, the problems that the existing technology cannot reasonably distribute the energy of the vehicle heat and electricity comprehensive energy system coupling the fuel cell and the supercritical carbon dioxide Brayton cycle are solved.

The invention discloses a micro-grid dispatching method, device and equipment and a storage medium, and relates to the technical field of micro-grid management and control, and the method comprises the steps: obtaining an energy operation model corresponding to target energy equipment in a target micro-grid; performing mixed integer programming operation based on the energy operation model to obtain a target operation curve; and performing power scheduling on the target energy equipment according to the target operation curve. According to the method, the mixed integer programming operation is performed according to the energy operation model pre-established for the target energy equipment in the micro-grid, so that the target operation curve corresponding to the optimal overall energy operation condition of the micro-grid is predicted, and power scheduling of the target energy equipment is performed based on the target operation curve. According to the invention, each energy device in the micro-grid is ensured to adaptively operate in an optimal state according to an actual condition, so that the effect of each energy device in a power system is exerted to the greatest extent, the overall economic benefit of the micro-grid is improved, and the energy consumption cost of the micro-grid is effectively reduced.

This invention discloses an SRS sequence collision optimization method, system, electronic device, and storage medium, relating to the field of communication network optimization technology. The method first acquires and preprocesses SRS beam-level measurement data and user signal characteristic data. It then constructs a three-dimensional virtual grid based on beam spatial location to generate a grid-level dataset. Next, it extracts feature quantities and quantifies interference intensity using machine learning, constructing MOD3, MOD6, MOD30, and MOD90 multi-mode interference matrices to identify conflict-risk cells. Finally, it establishes an optimization objective function based on PCI allocation constraints and determines the optimized PCI allocation result using an integer programming algorithm combined with branch-and-prune decision. This invention solves the problems of traditional PCI optimization models being too simplistic and lacking accuracy, minimizing PCI modulus interference, effectively reducing SRS sequence collisions, and improving network measurement accuracy and communication performance.

The present application belongs to the field of generator unit maintenance plan arrangement, and relates to a kind of construction method of high-efficiency generator unit maintenance model based on unit aggregation and linear relaxation, based on unit combination model, establishes the basic UC maintenance model, and models the generator unit maintenance problem as a mixed integer programming problem;Further, for the problem that the production and operation constraints of thermal power generating units in the medium and long term maintenance problem of generator unit are complex and difficult to solve, the RCUC model is embedded into the maintenance model by introducing unit aggregation and linear relaxation technology, and the RCUC maintenance model is established;For the maintenance constraints of unit cluster, an improved RCUC maintenance model is proposed, which uses integer variables instead of 0-1 variables for modeling, reduces the size of integer variables and constraints, and improves the solving efficiency of the generator unit maintenance model.

This invention relates to a robot-task allocation method based on the KM algorithm, belonging to the field of robotics. The invention transforms the integer programming problem into a bipartite graph optimal matching problem, solves the maximum matching problem in the bipartite graph using the Hungarian algorithm, and then uses the KM algorithm to solve the optimal matching problem. This invention provides an easy-to-implement, efficient, and effective robot task allocation method. This algorithm is more efficient than other algorithms on dense graphs and can be applied to multi-robot systems performing tasks such as patrol and rescue.

This invention belongs to the field of supply chain collaboration, specifically disclosing a visualized intelligent collaborative operation system for the supply chain. The system includes: a supply chain basic parameter construction module, a multi-objective collaborative delivery digital model construction module, a multi-objective hybrid selection module, and a visualization module. Based on the probability distribution characteristics of uncertain demand parameters, this solution employs a mixed-integer programming method to construct a multi-objective optimization overall model, achieving integrated modeling of the entire supply chain collaborative delivery process from design to operation. By integrating genetic algorithms and simulated annealing algorithms, a multi-objective hybrid selection method based on a parallel selection strategy is designed. A roulette wheel selection method is used to screen high-fitness individuals, and differentiated mutation is designed with a non-uniform mutation mechanism introduced. Simultaneously, the intermediate population is used as the initial solution for the simulated annealing algorithm for local optimization, significantly improving the rationality and timeliness of supply chain collaborative decision-making.

The application discloses a kind of based on Internet of Things's water buffalo precise feeding system and method. Including biological feature acquisition terminal, edge computing device, cloud intelligent platform and execution control module, it is applicable to the intelligent management scene of large-scale water buffalo breeding. The method is by collecting the nose print image of water buffalo, voiceprint signal and temperature data, fusion multi-modal biological feature realizes individual identity recognition;On the basis of identification, call the dynamic nutrition model constructed based on GRU neural network, combine weight, exercise amount, environmental parameter and other characteristics to generate individualized feeding formula;Adopt mixed integer programming algorithm to optimize feed proportioning, give consideration to nutrition, cost and palatability Multiple constraints;It also includes abnormal detection and nutrition compensation mechanism, for identifying healthy abnormal individual and adjusting feeding scheme. The system is based on Internet of Things technology to realize edge inference and cloud cooperation, improve the identification accuracy, response speed and feeding intelligent level.

The present application belongs to the technical field of multi-agent cooperative control and path planning, and particularly relates to a multi-agent collision-free prediction optimization method based on smooth potential field and parallel ADMM. The method is based on the parallel ADMM architecture, and decouples the optimization problem into two sub-problems of individual dynamics and cooperative collision avoidance. At the individual level, the dual decomposition technique is used to convert the constrained optimization into a parallel solution of dual quadratic programming; at the cooperative level, a second-order differentiable smooth potential energy function is used to replace the mixed integer programming to handle the collision avoidance constraint. The present application reduces the computational complexity from exponential to polynomial, and significantly improves the real-time planning capability and robustness of large-scale multi-agent clusters in complex environments.

This application relates to a method for optimizing bridge vase-shaped pier parameters based on mixed-integer programming, comprising: constructing a multi-objective optimization model with the design cost and total construction cost of the vase-shaped pier as objectives; establishing mixed-integer programming constraints based on the multi-objective optimization model; and calculating the global optimal solution of the multi-objective optimization model to obtain the optimized parameters of the vase-shaped pier. This application comprehensively considers both design cost and total construction cost, combines mixed-integer programming to solve the problem, and ensures that the optimized parameters meet design requirements through constraints, achieving quantitative balance and realizing global optimization of key parameters of the vase-shaped pier. This effectively shortens the design cycle, reduces the total construction cost, reduces the types of construction formwork, and simultaneously balances the economy of concrete usage and construction convenience.

Aspects of the disclosure provide techniques for defining communication parameters. A method includes obtaining input information relating to a communication source and a set of communication targets; generating, in accordance with a target function that indicates a set of constraints to be satisfied by a set of communication parameters, the set of communication parameters for communications from the communication source to the set of communication targets, the generating including: performing a linear programming operation to generate one or more first communication parameters of the set of communication parameters based on the set of constraints, and performing a mixed-integer programming operation to generate one or more second communication parameters of the set of communication parameters based on the set of constraints, wherein the set of communication parameters is based on a predictive model configured to predict a behavior of the set of communication targets; and providing the set of communication parameters.

The present application relates to a kind of for inhibiting new energy station high-frequency oscillation follow / construct network control configuration method, belong to power system high-frequency oscillation stability control technical field.The present application first establishes follow network type converter output impedance analytical model and station aggregation output impedance model, and verifies the accuracy of model by frequency sweep;Second, based on impedance analysis method, identify system high-frequency oscillation risk, determine the target frequency band and expected compensation of impedance remodeling;Then establish the output impedance analytical model of construct network type converter;Finally, whether the branch is transformed as the decision variable of construct network type, with the least number of transformed branch as the target, with the overall impedance of hybrid system satisfying stability margin as the constraint, optimization configuration model is established and mixed integer programming method is used to solve optimal configuration scheme.The present application can remodel station impedance characteristics by optimizing configuration of a small number of construct network type branches, inhibit high-frequency oscillation from the source, with the advantages of small amount of reconstruction, accurate configuration and strong adaptability.

This invention discloses a unit combination optimization method and system. Based on the output characteristics analysis of different types of generating units, a mathematical model of each unit in the power system is constructed. The baseline state of each unit is obtained from the mathematical model. Building upon existing unit combination research, this method balances the goals of renewable energy consumption and optimal economic cost, comprehensively considering the unit itself, the system, and constraints. It improves computational efficiency while enhancing the matching degree between the unit combination plan and the grid transmission capacity, reserving space for economic dispatch and safety verification. A heuristic algorithm with low computational complexity and ease of operation provides a feasible approach to the above objectives. By arranging the start-up, shutdown, and output states of the units, the method effectively avoids the solution process of mixed integer programming problems, improving the computational efficiency of long-cycle unit combination problems in large-scale practical power systems, reducing computation time from several hours to a few minutes.

The application discloses a two-stage serial heat pipe constraint layout optimization method based on mixed integer programming, relates to the technical field of component layout optimization, and comprises the following steps: determining the number of components in a component layout area, the structural size of the components, the power of the components, the number of heat pipes, the structural size of the heat pipes, the performance parameters of the heat pipes and the arrangement form of the heat pipes; determining the number of heat pipes required by each component; constructing and solving an optimization model of the distribution relationship between the components and the heat pipes to obtain the distribution relationship between the components and the heat pipes; using continuous coordinates to describe the central positions of the components, linearly modeling constraint conditions and a preset optimization target, and constructing a component layout optimization model based on mixed integer programming; and solving the component layout optimization model to obtain the position of each component in the component layout area. The application can realize the optimization solution of the component layout under the consideration of quality characteristic requirements and heat pipe constraints, has low optimization solution difficulty, is high in efficiency, and has small influence of the component scale on the solution efficiency.

The application discloses a satellite model predictive control method based on convex mixed integer programming and belongs to the technical field of spacecraft orbit optimization and control, and solves the problems that traditional methods depend on continuous control input, are inconsistent with discrete characteristics of a satellite propulsion system, do not fully consider the discrete nature of a thruster, are difficult to consider accuracy and efficiency when dealing with complex maneuvers, and cannot effectively optimize fuel consumption. The application first establishes a non-convex optimal control model of a mission satellite, then convexes non-convex terms and introduces integer decision variables, then solves a benchmark trajectory of a convex optimization problem without collision avoidance constraints, finally solves a convex optimization problem with collision avoidance constraints to obtain an optimal control sequence, and realizes fuel optimization and collision avoidance. The application can uniformly deal with discrete switch decision of a satellite thruster and continuous trajectory optimization. The application can realize fuel optimization, reduce cost, accurately control the thruster and improve orbit adjustment accuracy.

The application discloses a heat pipe constraint component layout comprehensive optimization method based on mixed integer programming, relates to the technical field of component layout optimization, and comprises the following steps: determining component information and heat pipe information in a component layout area; determining the number of heat pipes required by the components; constructing an allocation relationship optimization constraint model of the components and the heat pipes; taking the center positions of the components as optimization variables, taking the minimization of the maximum actual heat conduction power of the heat pipes as an optimization target, taking non-interference constraints between the components and the component layout area, non-interference constraints between the components, component system centroid constraints and heat coupling constraints between the components as constraint conditions, constructing an optimization target model and a constraint model; constructing an intersection constraint model of the components and the heat pipes; simultaneously solving various models to obtain and solve a component layout optimization model, and obtaining the positions of the components in the layout area. The application can realize the fast optimization solution of the component layout under the consideration of the quality characteristic requirements and the heat pipe constraints, has low solution difficulty and high efficiency.

This invention discloses a method for configuring and dynamically scheduling a photovoltaic-storage-charging system in an industrial park that integrates smart power distribution, belonging to the fields of new energy microgrids and smart power distribution technology. The method includes: constructing an integrated photovoltaic-storage-charging system capable of both grid-connected and islanded operation; selecting key equipment for photovoltaics, energy storage, and charging piles and modeling their full lifecycle costs; constructing a collaborative optimization configuration model with economic and operational constraints, aiming at optimizing the total system cost, and solving it using a mixed integer programming algorithm; establishing a comprehensive power quality evaluation system from the dimensions of flexibility, power supply quality, new energy absorption rate, and carbon emissions, and using a combined weighting method to achieve quantitative grading of system performance; and developing an interactive visualization design platform based on MATLAB / GUIDE, supporting multi-source data import, parameter adjustment, and multi-scheme comparison. This invention achieves synergistic optimization of the economy and energy efficiency of the photovoltaic-storage-charging system, lowers the planning threshold, and is applicable to the low-carbon transformation of industrial parks and smart microgrid planning.

The application provides a kind of collaborative caching method of multi-bit rate video based on edge computing, the application studies the MBS caching placement mechanism of multi-bit rate video, and formulates an integer programming problem.Under the constraint of caching capacity, the problem of how to deploy multiple bit rate videos on MES is proposed, with the goal of maximizing user perceived QoE;The application provides a system model, including a network model, a caching model and a QoE function;For a general QoE function, an efficient caching algorithm based on greedy heuristic is designed, and for a linear QoE formula, it is proved that there is an optimal solution, which converts the problem into a monotone submodule maximization problem.Using the video collaborative caching strategy of the application, better performance can be achieved, and the user perceived QoE is improved.

A plurality of qubit collision types and a plurality of constraints are defined. For a set of qubits, a computerized mixed integer programming solver is used to iteratively minimize collisions under the constraints by minimizing a sum of a product of a number of collisions of each collision type given a constraint multiplied by a weight. A frequency tuning plan for the set of qubits is output based on the iterative minimization. The physical qubits are facilitated to be tuned in accordance with the frequency tuning plan.

This invention discloses a hardware and task-aware design method for maximizing on-chip data reuse in an NPU, relating to deep learning algorithm model technology and electronic information technology. Based on the characteristics of the computing task, a model of the total bandwidth requirement of the computing task is constructed using a unified representation of the NPU hardware architecture. Multi-dimensional data block size and on-chip cache architecture are used as optimization variables, considering computing task constraints and NPU on-chip RAM space size constraints, to construct an optimization equation that minimizes bandwidth requirements. An integer programming algorithm is used to solve the bandwidth requirement minimization optimization equation, calculating the optimal multi-dimensional data block size and on-chip cache architecture design. Based on the necessary and sufficient condition for the optimization objective to reach the theoretical minimum, the minimum design of the NPU on-chip RAM space is given. This invention significantly improves on-chip data reuse rate, enhances the inference performance of bandwidth-constrained NPUs, and effectively guides the design of on-chip cache architecture and the configuration of on-chip RAM space.

The present application provides a railway operation scheduling method based on four-layer graph integer programming modeling, comprising: S1. obtaining a standardized data set; S2. obtaining time-related data; S3. updating the standardized data set; S4. constructing a constraint system; S5. constructing a four-layer graph structure; S6. constructing a MILP model; S7. hybrid solving; S8. calculation acceleration; S9. calibrating the upper limit of the optimal single-day task number; S10. based on the solving result of S7, outputting a scheduling plan, a resource allocation scheme, path information and a visualization chart. The present application aims to provide a comprehensive scheme of "unified modeling + efficient solving + feasibility guarantee + calculation acceleration", which can quickly generate an executable railway operation scheduling plan that meets the requirements of engineering practice under the conditions of multiple tasks, multiple resources and strict window constraints, and improve the intelligent level and implementation efficiency of operation and maintenance management.

The application discloses an optimization method, system and device of joint antenna selection and precoding and a storage medium, and belongs to the technical field of wireless communication. The method comprises the following steps: acquiring communication data of a base station to a user in a target XL-MIMO communication system; calculating a receiving signal of the user based on the communication data; constructing a joint optimization model with the maximum sum rate as an optimization target and an antenna selection matrix and a hybrid precoding matrix at the base station as optimization variables based on the receiving signal; decomposing a solution problem of the joint optimization model into sub-problems by using an alternating direction method; alternately solving the sub-problems to obtain an optimization result; and obtaining the antenna selection matrix and the hybrid precoding matrix at the base station according to the optimization result. The application converts the antenna selection problem from integer programming into a matrix sparsity optimization problem by using the alternating direction method, effectively solves the constraint optimization problem of the key variable, and improves the spectrum efficiency of the communication system.

This invention discloses a multi-task adaptive scheduling method for embedded systems, belonging to the field of embedded system scheduling technology. It constructs a hierarchical closed-loop scheduling architecture, using mixed integer programming for second-level global optimization to generate a baseline solution and resource shadow prices. Deep reinforcement learning performs millisecond-level real-time decision-making to output six-dimensional structured scheduling actions. Combined with a dual-scale collaborative optimization mechanism, it includes emergency task scheduling, emergency anomaly repair, and dynamic task priority management strategies. This invention achieves proactive perception of resource scarcity, balances global optimization and rapid response, supports fine-grained resource control, improves system robustness and emergency fault tolerance, and balances energy efficiency and service quality.

This application provides a BIM-based intelligent layout method for tower cranes and trestles in large-scale public building projects, relating to the field of building structure construction technology. The method includes: system construction and data preparation; employing optimization algorithms to arrange tower cranes and trestles, modeling the tower crane-trestle layout problem as a mixed integer programming problem coupled with facility site selection and path planning; using a two-stage heuristic algorithm to arrange tower cranes and trestles, obtaining a Pareto optimal solution set; and simulating and verifying the tower crane and trestle layout schemes included in the Pareto optimal solution set and outputting the solution. This application constructs a tower crane-trestle collaborative layout model, aiming to minimize the total material transportation cost, total time, and total risk, simultaneously optimizing the location, model, and quantity of tower cranes and the path of trestles in three-dimensional space, forming an integrated construction logistics solution.

This invention belongs to the field of communication transmission scheduling technology. It provides a data transmission scheduling method based on edge computing communication devices, comprising: deploying collaborative scheduling agents at each edge node to collect available bandwidth, computing load, data dependencies, and task queue priorities in real time and report them to a central collaborative scheduler. The central scheduler reconstructs the directed acyclic graph of computing tasks based on global information, constructs a data dependency-aware queue, and jointly models bandwidth allocation and computing resource orchestration as a mixed-integer programming problem. A deep Q-network algorithm is used to solve for the optimal data transmission rate and computing task scheduling order. During the execution of each node agent, execution deviations are continuously monitored and feedback is provided. The central scheduler corrects resource estimates according to preset rules and then reschedules the tasks. This invention solves the resource mismatch problem caused by the deep coupling of data transmission and computing tasks in edge computing through joint optimization of computing and communication and a closed-loop feedback mechanism.