28 results about "Relaxation algorithm" patented technology

The invention relates to the technical field of e-commerce logistics and supply chain management, and discloses a multi-channel e-commerce platform order processing optimization system and method, and the method comprises the steps: correcting physical inventory data through a Lagrange dual variable fed back in a previous period, calculating a virtual inventory, and receiving a discrete order flow; constructing a space-time hypergraph model of the to-be-processed order according to the commodity homogeneous attribute and the spatial neighborhood attribute; performing constraint optimization solution on the hypergraph model based on a Lagrangian relaxation algorithm, and generating an optimal order allocation matrix meeting productivity constraints and a Lagrangian dual variable of a current period; and analyzing the distribution matrix to generate an operation instruction, issuing the operation instruction to the physical warehouse, and feeding back the dual variables to the inventory calculation module. According to the method, collaborative operation benefits are mined through the space-time hypergraph, and a negative feedback closed loop with physical capacity pointing to front-end sales is constructed by using dual variables, so that performance cost optimization and flow adaptive control are realized.

The invention relates to the technical field of satellite network communication, and particularly discloses a multi-task planning method and system for a low-orbit communication-remote integrated satellite network, and the method comprises the steps: constructing a system model which comprises a communication-remote integrated satellite, a data relay satellite, a ground station and a task set, and carrying out the multi-task planning of the low-orbit communication-remote integrated satellite network based on the system model. Establishing an optimization problem aiming at maximizing the weighted task completion amount; solving the task acquisition planning sub-problem by using a positive semidefinite relaxation algorithm, and solving the task transmission planning sub-problem by using a column generation algorithm; and feeding back a solving result of the task transmission planning sub-problem to the task acquisition planning sub-problem to update a task weight, and iteratively executing the step of solving the task acquisition planning sub-problem and the task transmission planning sub-problem until a convergence condition is met, and aiming at a complex scene in which heterogeneous businesses coexist, solving the task transmission planning sub-problem and solving the task transmission planning sub-problem. An efficient global optimization solution is provided, the task income is maximized, a dynamic feedback iteration mechanism is introduced, and the overall collaboration and adaptability of the system are enhanced.

The application discloses a method for designing and optimizing a VLCP system assisted by light reflection RIS under low signal-to-noise ratio, wherein the VLCP system comprises an intelligent wall adopting a smart surface RIS with mirror reflection, a transmitter and a user terminal equipped with a receiver with a liquid crystal smart surface, communication and positioning signals are integrated into the transmitter, the transmitter comprises an LED, and the method comprises the following steps: under low signal-to-noise ratio, taking asymptotic capacity as a communication metric constraint condition, taking a Cramer-Rao lower bound of positioning error as a positioning metric constraint condition, combining a positioning constraint satisfaction process based on a two-stage greedy algorithm and a communication performance maximization process based on a greedy strategy convex relaxation algorithm, optimizing elements of an RIS allocation matrix to maximize the asymptotic capacity, obtaining an optimal RIS allocation matrix, and completing the design and optimization of the VLCP system. In a low signal-to-noise ratio scene, the VLCP system of the application can significantly improve system performance by applying RIS.

The invention discloses a numerical weather forecast cold start error suppression method and device, and relates to the technical field of offshore wind power, and the suppression method comprises the steps: S1, collecting initial data through a marine meteorological sensor array, including sea wave height, period, wave direction and corresponding wind field initial observation data, and constructing a multi-dimensional data set after preprocessing; s2, on the basis of the data set and historical sea wave-wind field time series data, a physical mechanism and data driving combination method is adopted to construct a sea wave-wind field coupling model, and the nonlinear coupling relation between sea waves and the wind speed and the wind direction is quantified. According to the method, a physical mechanism and data driving fusion modeling is adopted, so that the meteorological rule conformity is guaranteed, the nonlinear coupling relationship is accurately captured, the limitation of a pure physical and pure data driving model is avoided, and the prediction core support is tamped; based on neural network mining time sequence and mode characteristics, a lattice point relaxation algorithm parameter strategy is dynamically adjusted, and the problem that traditional fixed parameters are poor in adaptability is solved.

The invention discloses a single-line bidirectional railway train working diagram compiling method based on a Lagrange relaxation algorithm, and relates to the technical field of railway transportation. In order to solve the problems of huge scale, complex constraint and high solving difficulty of single-line bidirectional railway train working diagram compiling and optimization tasks, the method comprises the following steps of: modeling based on passenger waiting time and energy consumption during train operation, constructing an optimization target, constructing constraint conditions according to train operation requirements, and establishing an optimization result; the method comprises the following steps: carrying out Lagrange relaxation processing on an avoidance constraint related to an opposite train at a platform, adding the Lagrange relaxation processing as a Lagrange penalty term into a target function, decomposing an original problem into sub-problems for respectively solving arrival and departure time sets of an uplink train and a downlink train, limiting the penalty term by utilizing an activation function, and processing the simplified sub-problems by utilizing a subgradient algorithm. According to the method, the train working diagram close to the mathematical accurate solution optimization effect can be iteratively solved in a short time, and the method is suitable for solving the single-track railway scene of the large-scale train working diagram.

The application relates to the technical field of satellite network communication, and particularly discloses a low-orbit integrated satellite network multi-task planning method and system, which comprises the following steps: a system model containing an integrated satellite, a data relay satellite, a ground station and a task set is constructed; based on the system model, an optimization problem with the target of maximizing the weighted task completion amount is established; a semi-positive definite relaxation algorithm is used to solve the task collection planning sub-problem, and a column generation algorithm is used to solve the task transmission planning sub-problem; the solving result of the task transmission planning sub-problem is fed back to the task collection planning sub-problem to update the task weight, and the steps of solving the task collection planning sub-problem and the task transmission planning sub-problem are iteratively executed until the convergence condition is met; for a complex scene where heterogeneous services coexist, an efficient global optimization solution is provided, the task benefit is maximized, a dynamic feedback iteration mechanism is introduced, and the overall coordination and adaptability of the system are enhanced.

A method and apparatus for simulating the operation of a cascade reversible hydropower station based on piecewise McCormick relaxation is disclosed. The method includes: constructing a simulation model of the reversible hydropower station operation based on the operating conditions of the station and aiming to maximize the total output of the station; linearizing the nonlinear part of the simulation model using piecewise McCormick relaxation and piecewise linearization to simplify it into a mixed-integer linear programming model; and iteratively relaxing the simulation model based on upstream runoff data and operating parameters to obtain the simulation results. This invention uses piecewise McCormick relaxation to transform the nonlinear problem into a linear problem, while employing an iterative relaxation algorithm to improve the solution accuracy. It does not require narrowing the feasible boundary of McCormick relaxation, has fewer iterations, and a faster convergence speed, thus improving the speed and stability of the solution while ensuring simulation accuracy.

The invention discloses a sum rate optimization method of an MA and RIS combined auxiliary NOMA uplink transmission system, which is suitable for an uplink transmission system consisting of a multi-antenna base station, an RIS and two communication users, and each communication user is provided with a single movable antenna. In order to effectively improve the transmission capability of the proposed system, the invention provides a sum rate optimization method of an MA and RIS combined auxiliary NOMA uplink transmission system. Specifically, the sum rate of the NOMA uplink transmission system is maximized by jointly optimizing a base station to receive a beam forming vector, an RIS phase shift matrix and an MA position. For the provided complex non-convex problem, a positive semidefinite relaxation algorithm is utilized to optimize receiving beam forming and an RIS phase shift matrix of a base station, a continuous convex approximation algorithm is utilized to optimize an MA position, and alternate iteration is carried out until a convergence condition is met. A simulation result shows that compared with a traditional fixed position antenna and RIS combined auxiliary NOMA uplink transmission scheme, the scheme provided by the invention remarkably improves the sum rate of an NOMA uplink transmission system.

The invention discloses a concealed wireless communication beam forming optimization method under limited character input, and belongs to the technical field of wireless communication. According to the method, a transmitting power and beam forming vector optimization strategy for jointly optimizing a transmitting end under different modulation modes is constructed, and a positive semidefinite relaxation algorithm is designed on the basis of utilizing lower bound approximation of an objective function: an initial non-convex objective function and a hidden constraint are equivalently converted into a convex form which is easier to process; and solving by using a CVX toolkit in MATLAB to obtain a design which enables the problem to be optimal in beam forming vector. Furthermore, in order to reduce the calculation complexity, the invention provides a low-complexity optimization strategy, and a simulation result shows that the method can remarkably reduce the calculation complexity while meeting the covert communication performance.

The invention relates to the technical field of tunnel engineering, in particular to a near-field dynamics simulation method and system for tunnel yielding support, and the method comprises the steps: dispersing a lining, a steel bar and a high polymer buffer layer model into space material points, distributing different material attributes for different materials, and generating a space coordinate matrix of the material points; a virtual boundary layer serving as a displacement boundary condition applying object is arranged on the outer wall of the lining; determining neighborhoods of the material points, and forming a neighborhood matrix of all the material points; setting a displacement boundary condition according to the large deformation grade; obtaining a compression constitutive model of the high polymer buffer layer, and calculating a micro-elastic modulus; adopting a self-adaptive dynamic relaxation algorithm to construct a near-field kinetic equation to iteratively solve the bond elongation of the material point; and calculating a global damage coefficient according to a comparison result of the key elongation and the critical elongation. According to the invention, crack initiation and development can be simulated on an engineering scale model, and a protection mechanism of an interlayer high polymer buffer layer for large deformation of soft rock is disclosed.

The invention provides an STAR-RIS assisted cellular-removal large-scale MIMO beam forming method and system based on sequence rank-one constraint relaxation, and a storage medium. The method comprises the following steps: step 1, utilizing a fractional programming method to carry out beam forming; an original non-convex problem is decoupled into an active beam forming design of an access point and a passive beam forming design of a simultaneous transmission and reflection reconfigurable intelligent surface, and the active beam forming design and the passive beam forming design are alternately optimized; and 2, for a matrix rank-one constraint existing in the passive beam forming design, gradually relaxing the constraint through a relaxation algorithm based on a sequence rank-one constraint, finding a local optimal solution meeting a constraint relaxation problem, and gradually tightening a feasible solution until the matrix rank is a one solution. The method disclosed by the invention has the beneficial effects that the method disclosed by the invention has the same performance as a traditional penalty operator algorithm under the condition of not updating a penalty term, the operation complexity is lower, and the reliability is higher.

The application belongs to the technical field of power system operation control, and relates to a parallel acceleration solving method for power system post-disaster recovery based on quantum calculation, which comprises the following steps: step 1, establishing a basic model of power system post-disaster recovery; step 2, according to a quantum agent Lagrange relaxation algorithm, decomposing the original optimization problem into various node sub-problems; and step 3, solving the post-disaster recovery model, continuously updating the Lagrange multiplier and the penalty factor in the iteration process, and realizing optimal solving under the interactive calculation of quantum calculation and classical calculation to obtain the post-disaster recovery scheme to guide the actual safe operation of the power system. According to the application, the problem is decomposed into multiple node-centered sub-problems, and the sub-problems are divided into discrete and continuous parts for solving, so that the solving difficulty is reduced. The application realizes the effects of parallel calculation and quantum embedding acceleration calculation, does not need to relax the problem for complete optimization, and guarantees better convergence.

A method and device for optimizing train departure path and timetable cooperatively, the method comprising: constructing a space-time state network for describing the operation of a train bottom; based on the space-time state network, constructing a train departure path and timetable cooperative optimization model; wherein the train departure path and timetable cooperative optimization model comprises a model for minimizing the space-time state path cost of the train bottom leaving a section and corresponding constraint conditions; using a Lagrange relaxation algorithm to transform the train departure path and timetable cooperative optimization model, and using a dynamic programming algorithm to solve the model to obtain an optimal train departure path and timetable. Through the method and device provided in the embodiment of the application, the train operation cost can be effectively reduced while the travel time of passengers is shortened, and the method can be used for assisting actual transportation production and improving the overall quality of train operation plans in departure time periods.

The invention discloses an underground pipeline scattered wave separation imaging method and system and a medium, and relates to the cross technical field of geophysical exploration and digital signal processing, and the method comprises the steps: obtaining and preprocessing original seismic data, taking an obtained two-dimensional time-space domain seismic record as an input, and constructing a scattered wave sparse dictionary based on discrete shear wave transformation; establishing an objective function based on morphological component analysis, performing iterative solution by using a block coordinate relaxation algorithm, and alternately updating a scattering wave sparse coefficient and an interference wave sparse coefficient until a convergence condition is met; reconstructing a pure scattered wave field through shear wave inverse transformation according to the finally obtained scattered wave sparse coefficient; performing migration imaging on the pure scattered wave field to obtain a spatial position image of the underground pipeline; according to the separation imaging method, a complete pipeline scattering form can be identified and captured under a strong noise background.

This invention provides a multi-target association and fusion positioning method and device. The method includes: acquiring the received measurement parameters of each receiving station radar, the coordinates of the transmitting station, and the coordinates of the receiving station; combining the received measurement parameters to obtain a combined measurement vector, and combining the transmitting station coordinates and the receiving station coordinates to obtain a station location vector; based on the combined measurement vector and the station location vector, using an improved least squares method to solve for the target position, obtaining the target least squares solution corresponding to the target position; based on the target least squares solution and the station location vector, calculating the homogeneity hypothesis measurement for each receiving station radar, and generating a likelihood function penalty term using the homogeneity hypothesis measurement; constructing a multidimensional allocation optimization model using the likelihood function penalty term, and solving the multidimensional allocation optimization model using a Lagrange relaxation algorithm to obtain the association result; and determining the true position of the target based on the association result.

The application provides a method and equipment for relaxing the limit value of RE101 project in GJB151B. Firstly, 25Hz-100kHz is divided into two frequency band ranges, 25Hz-30kHz and 30kHz-100kHz. Then, different relaxation methods are selected according to the current frequency band to obtain the relaxation limit value of the power line interface part in the RE101 project. Finally, corresponding relaxation conversion is carried out according to the corresponding CE type relaxation rule, which is consistent with the conduction relaxation algorithm, easy to understand and has strong engineering applicability.

This invention relates to a multi-dimensional confidence-based point-line fusion SLAM method and system for visually degraded environments, belonging to the fields of computer vision and robot navigation technology. The invention constructs a nonlinear mapping function based on two-dimensional image entropy, dynamically adjusts the gradient threshold and Gaussian smoothing parameters of the line feature extraction algorithm, and introduces a sudden illumination safety mode to enhance adaptability to extreme environments. It performs photometric consistency verification on point features after optical flow tracking, performs region growing on line features using the aforementioned adaptive parameters, and proposes a hierarchical non-convex relaxation algorithm guided by dual weights of geometric residuals and pixel gradients for noise-resistant fitting. It establishes a linear inverse mapping mechanism between front-end feature confidence and back-end optimization information matrix, dynamically adjusting residual weights according to feature quality. In motion-blurred and illumination-changing environments, it can effectively extract high-quality features and perform tight-coupling optimization, improving the positioning accuracy and speed of the SLAM system in weak-texture and drastically changing illumination environments.

The application relates to the technical field of wireless communication, and provides a kind of passive hybrid concealment communication method and system based on RIS, which includes the following steps: step one: constructing a multi-user concealment communication system;Step two: constructing the signal model of the main user and the secondary user, obtaining the signal-to-interference-and-noise ratio of the main user and the secondary user according to the signal model, and obtaining the user rate under the limited block length according to the signal-to-interference-and-noise ratio;Step three: constructing the signal model and binary hypothesis model of the eavesdropper Willie;Step four: establishing an optimization model with the optimization goal of maximizing the worst secondary user's concealment rate;Step five: introducing auxiliary variables, alternating optimization algorithm, semi-positive relaxation algorithm and Gaussian randomization method to convert the non-convex optimization problem into a convex optimization problem for solving, and using MM algorithm and alternating direction multiplier method (ADMM) to solve the problem with low complexity.The application can better guarantee the communication quality of the main user and the concealment transmission of the secondary user.

The application provides a kind of steel enterprise oxygen system optimization scheduling model construction and solution method, it is related to industrial information technology field, establishes steel enterprise oxygen system optimization scheduling model, considers oxygen demand constraint, unit production process constraint, minimum switch-on and switch-off time constraint and climbing constraint.The model decides the production running state of each unit and oxygen production in each period, to reduce the total operation cost of oxygen system.According to the characteristics of the model, a Lagrangian relaxation algorithm is designed to solve it.The method relaxes the material balance constraint to the objective function by Lagrange multiplier, and decomposes the original problem into air separation unit subproblem, gasifier unit subproblem and storage system subproblem.In order to speed up the solution speed of subproblem, an optimal property acceleration strategy is proposed, a subgradient algorithm is designed, and a multiplier updating strategy is proposed.The application can significantly reduce the oxygen dispersion, reduce the production operation cost of oxygen system, and ensure the safe and stable operation of oxygen system.

The invention relates to the technical field of wireless communication, and provides an active and passive hybrid covert communication method and system based on RIS, and the method comprises the following steps: 1, constructing a multi-user covert communication system; 2, constructing a signal model of the main user and the auxiliary user, obtaining a signal to interference plus noise ratio of the main user and the auxiliary user according to the signal model, and obtaining a user rate under a limited block length according to the signal to interference plus noise ratio; 3, constructing a signal model and a binary hypothesis model of the eavesdropper Willie; 4, establishing an optimization model by taking maximization of the hiding rate of the worst secondary user as an optimization target; and 5, introducing an auxiliary variable, an alternating optimization algorithm, a positive semidefinite relaxation algorithm and a Gaussian randomization method to convert a non-convex optimization problem into a convex optimization problem for solving, and performing low-complexity solving on the problem by using an MM algorithm and an alternating direction multiplier method ADMM. According to the invention, the communication quality of the primary user and the hidden transmission of the secondary user can be well ensured.

The invention provides a near-field dynamics simulation method and system for a nonlinear creep process of a deep rock mass. Comprising the following steps: constructing a rock mass creep whole-process database through multi-type mechanical tests, and introducing a nonlinear sticky kettle element to construct a deep rock mass nonlinear creep constitutive model; digital representation is carried out on the geometrical morphology of the deep rock mass, and a rock mass near-field dynamic model is constructed; embedding the deep rock mass nonlinear creep constitutive model into a rock mass near-field dynamic model to obtain a near-field dynamic rock mass nonlinear creep constitutive model; and establishing a discrete form of the model by adopting a self-adaptive dynamic relaxation algorithm according to multiple accumulation conditions of nonlinear creep of the deep rock mass, and solving the discrete form to obtain a nonlinear creep curve viewer. According to the method, the advantages of near-field dynamics simulation can be played, meanwhile, the mechanical characteristics of the deep rock mass can be better reflected, an effective means is provided for simulation analysis of the deformation and fracture process of the deep rock mass, and then the application range of near-field dynamics in the field of geotechnical engineering is widened.

This invention belongs to the field of radar image processing technology and provides an efficient super-resolution imaging method and apparatus for tomographic synthetic aperture radar. The method includes: acquiring a multi-baseline tomographic SAR dataset based on multiple SAR images; performing nonlocal filtering estimation on the interferometric parameters of the multiple SAR images to obtain nonlocal filtering parameters; constructing a tomographic SAR imaging model based on the nonlocal filtering parameters and a relaxation algorithm; and using the tomographic SAR imaging model to perform super-resolution imaging processing on the multi-baseline tomographic SAR dataset to obtain super-resolution imaging results. The method described in this embodiment improves the super-resolution imaging capability and data processing efficiency of nonlocal tomographic SAR.

The invention discloses a trace point matching method based on a relaxation algorithm, and the method can achieve the restoration and improvement of a multi-target overall trace point with a large number of false alarm and leak detection phenomena. The method comprises two parts of false alarm elimination and missing detection completion. In the false alarm rejection part, a sliding window method is firstly used, a plurality of continuous screen point sets to be subjected to trace point matching are included in a sliding window, then redundant trace points are removed by using an outlier rejection algorithm, then mutual trace point matching is performed by using an improved relaxation algorithm, and finally a result is updated on an original point set. In the case of missing detection for complementing all scores, the method comprises the following steps: firstly, performing vector construction on point sets of adjacent screens by using a group velocity, indicating the direction and distance of vectors, and complementing trace points if no measurement point is found at a corresponding position; the effectiveness of the method is verified through simulation, and the method can be used for solving the problems of false alarm missing detection and robust tracking of multi-target overall trace points.

The invention discloses a communication, inductance and energy integrated joint beam forming and resource allocation method, which comprises the following steps of: S1, constructing an optimization problem of maximizing the gain of a sensing beam directional diagram based on a bifunctional signal transmitted by a base station, and taking a beam forming vector transmitted by the base station, an IRS phase shift matrix and a resource allocation coefficient as optimization variables, the service quality requirement of the communication user and the minimum energy threshold constraint of the energy collection equipment are met; s2, solving the optimization problem by adopting a semi-definite relaxation algorithm, converting a non-convex problem into a convex semi-definite programming problem through relaxation rank-one constraint, and recovering a feasible solution by utilizing a randomization technology; or alternatively optimizing the beam forming vector and the IRS phase shift vector by adopting a low-complexity algorithm based on Lagrange duality and coordinate descent, and updating the Lagrange multiplier through a sub-gradient method until a complementary relaxation condition is met. The algorithm is high in intersection and low in complexity.

The application discloses a covert wireless communication beamforming optimization method under limited character input and belongs to the technical field of wireless communication.The application constructs a joint optimization strategy of the transmission power and the beamforming vector optimization strategy of the transmission end under different modulation modes, designs a semi-positive definite relaxation algorithm on the basis of using the lower bound approximation of the objective function, equivalently converts the initial non-convex objective function and the covert constraint into a more easily handled convex form, solves by using the CVX tool package in MATLAB, and obtains the design of the optimal beamforming vector of the problem.Further, in order to reduce the calculation complexity, the application proposes a low-complexity optimization strategy, and simulation results show that the method can significantly reduce the calculation complexity while meeting the performance of covert communication.

The present application relates to the technical field of power system operation control, and specifically to a parallel accelerated solution method for post-disaster restoration of a power system based on quantum computing, including: step 1: establishing a model for post-disaster restoration; step 2: according to the quantum proxy Lagrangian relaxation algorithm, decomposing an original optimization problem into node subproblems; and step 3: solving the model for post-disaster restoration, updating Lagrange multipliers and penalty factors in iteration, achieving an optimal solution under the interaction of quantum computing and classical computing, and accelerating the acquisition of a restoration plan to guide a safe operation of the power system. The present application decomposes a problem into subproblems and divides the subproblems into discrete and continuous parts for solution, reducing the difficulty. The effects of parallel computing and quantum-embedding accelerated computing are realized without complete optimization for a relaxed problem, ensuring better convergence.

The embodiment of the invention provides a power distribution network energy storage optimization method and device, equipment, a medium and a program product. The method comprises the following steps: acquiring historical data of distributed photovoltaic, constructing an output uncertainty model of the distributed photovoltaic according to the historical data and a connection function, establishing an objective function, and performing linear reconstruction on nonlinear characteristics of the objective function through a relaxation algorithm, and solving a target function based on a linear reconstruction result to optimize energy storage configuration of the power distribution network. By introducing the connection function, the potential dependency relationship of the distributed photovoltaic output characteristics can be captured, the objective function is established by using the connection function, and the non-linear characteristics are processed through the relaxation algorithm, so that the energy storage configuration of the power distribution network can be more accurate and reasonable, and the cost and the resource waste are reduced on the basis of ensuring the power supply reliability of the power distribution network.

The invention provides an unmanned aerial vehicle communication and sensing integrated beamforming and trajectory design method and system, and relates to the technical field of unmanned aerial vehicle communication and sensing integration, and the method comprises the steps: building an unmanned aerial vehicle communication and sensing integrated scene model with the minimization of the total power consumption of an unmanned aerial vehicle task period as a target; decomposing the unmanned aerial vehicle communication perception integrated scene model to obtain an unmanned aerial vehicle beam forming design sub-model and an unmanned aerial vehicle trajectory design sub-model; constructing an alternating optimization framework, wherein the alternating optimization framework specifically comprises a semi-definite relaxation algorithm and a continuous convex approximation algorithm; according to the unmanned aerial vehicle trajectory parameters, solving the unmanned aerial vehicle beam forming design sub-model through a semi-definite relaxation algorithm to obtain communication beam forming parameters and a sensing signal covariance matrix; solving the unmanned aerial vehicle trajectory design sub-model through a continuous convex approximation algorithm to obtain updated unmanned aerial vehicle trajectory parameters; repeating calculation until a convergence condition is reached, and outputting an optimal strategy; and executing the optimal strategy.