74 results about "Multivariable optimization" patented technology

A method, system and article of manufacture are disclosed for allocating tasks to a team of persons. The method comprises comprising the step of identifying a set of tasks and a set of persons, each of the tasks having a given set of task attributes, and each of the persons having a given set of employee attributes. The method comprises the further steps of establishing a cost function including a set of cost factors based on one or more of the task or employee attributes, and establishing a utility function including a set of utility factors based on one or more of the task or employee attributes. One or more assignments of the tasks among the employees are found that minimizes the cost function; and the one assignment, of said one or more assignments, is identified that maximizes the utility function.

The invention discloses an optimization design method of a radial-flow-type hydraulic turbine. In the design method, a unitary thermal optimization design, a three-dimensional modeling method of a through-flow part and a complete machine optimization platform are utilized, wherein the optimization platform comprises four modules, namely nozzle blade and impeller blade parameterization, a coevolution genetic algorithm, a self-adaption approximation model, and autocall of CFD (computational fluid dynamics). Through the parameterization, characteristic variables describing impeller blades, nozzle blade patterns and installation angle variation are extracted. The optimization target is to enhance the overall efficiency and expansion ratio of the hydraulic turbine simultaneously under a complete machine environment. The optimization platform can be used for reducing the calculated amount and accelerating the convergence by virtue of the following measures: the approximation model is built and updated by a dynamic sampling strategy, and enough prediction accuracy is obtained by virtue of less CFD calculation; and a complicated multivariable optimization problem is decomposed into a plurality of relatively independent and interactive subproblems by virtue of the coevolution genetic algorithm, so that not only can the characteristics of the original problem be maintained, but also the calculated amount is reduced effectively.

The invention discloses a robust resource allocation algorithm of a cognitive heterogeneous wireless network and belongs to the technical field of communication cognitive heterogeneous wireless networks. The robust resource allocation algorithm is characterized by considering a robust resource allocation algorithm in a cognitive heterogeneous multi-network environment influenced by channel parameter perturbation, considering cross-layer interference constraint and bounded channel uncertainty and interference power uncertainty in an objective function, converting the original infinite dimensional multivariate optimization problem into the convex optimization problem of certainty by using a robust optimization theory, obtaining a robust power control algorithm by using a lagrangian duality method, and achieving sharing of the robust resource of the cognitive heterogeneous wireless network. Simulation results show that the algorithm can effectively protect the performance of users of a macro-cellular network and has stronger robustness.

The invention discloses a computer implemented method and system for real-time optimal management of hospital's Emergency Room resources. The system provides optimal work plan for crewmembers and equipment, taking into consideration relevant variables. It uses multivariable optimization techniques to optimize the defined cost functions, which represent overall patient treatment waiting time and cost. Real-time information is provided to both patients and crewmembers. The work plan is continuously updated according to occurring events.

The invention relates to a crack performance measurement and optimization solution method for a composite material glue joint structure and belongs to the field of technical research in aeronautical material science. The method comprises the following steps: 1, establishing a crack propagation constructive relation model; 2, designing glue joint layer crack propagation tests by combining constructive relation forms; 3, reversely measuring glue joint layer crack propagation performance parameters by utilizing the multi-variable optimization method, and establishing a complete interface crack propagation mathematic model and analysis method. The crack performance measurement and optimization solution method for the composite material glue joint structure is high in calculation precision and speed, the established crack propagation constructive relation is simple and easy to use, the wide practical application value is achieved, and processes of damage start, material degradation, crack generation and crack propagation of bonding layer materials can be completely revealed.

The invention discloses a PSO (Particle Swarm Optimization)-based maximum wind energy capturing method of a VSVF (Variable-speed Variable-frequency) wind power system. Aiming at the VSVF wind power system which is formed by a variable-frequency transformer and multiple parallel-running permanent magnetic synchronous wind power generation units, cooperative optimization can be carried out on the rotating speed of the variable-frequency transformer and the pitch angles of all permanent magnetic synchronous wind power generation units through PSO, so that the capturing of maximum wind energy of the VSVF wind power system is realized. Compared with a univariate optimization method aiming at the rotating speed of the variable-frequency transformer, a PSO-based multivariate optimization method provided by the invention is capable of obtaining more wind energy.

The invention provides a renewable energy optimization method of an energy collection type wireless relay network with maximum throughput. The method comprises the following steps: 1) realizing the maximum throughput in the energy collection type wireless relay network via renewable energy optimization management, wherein the optimization problem is described as a multi-variable optimization; 2) decomposing P1 problem into two sub optimization problems due to the convex optimization properties: power sub optimization and time slot sub optimization; in view of the power sub optimization, optimizing the variable pi by using a regular convex optimization algorithm (interior point method); and in view of the time slot sub optimization, optimizing the variable (the formula is as shown in the specification) by using a prediction subgradient method. The invention provides a renewable energy optimization method for realizing the maximum throughput and maximum system efficiency in the energy collection type wireless relay network by combining time scheduling with power allocation.

A method for operating a vapor compression system modifies each control signal of a set of control signals with a corresponding modification signal of a set of modification signals, wherein each modification signal includes a perturbation signal, and the pertubation signals haver different frequencies and determines a metric signal representing perturbations in the system caused by the set of modification signals. Next, the method adjusts a value of each modification signal based on a function of a phase between the modification signal and a corresponding frequency component of the metric signal.

A HVAC system for a building includes a plant and a plurality of single-variable extremum-seeking controllers (ESCs). The plant includes HVAC equipment operable to affect an environmental condition inthe building. Each of the single-variable ESCs is configured to perturb a different manipulated variable with a different excitation signal and provide the manipulated variables as perturbed inputs to the plant. The plant uses multiple perturbed inputs to concurrently affect a performance variable. The single-variable ESCs are configured to estimate a gradient of the performance variable with respect to the each manipulated variable and independently drive the gradients toward zero by independently modulating the manipulated variables.

A method for separating and estimating multiple motion parameters in an X-ray angiogram image. The method includes: determining a cardiac motion signal cycle and a variation frame sequence of translational motion according to an angiogram image sequence, tracing structure feature points of vessels in the angiogram image sequence whereby obtaining a motion sequence, processing the motion sequence via multivariable optimization and Fourier frequency-domain filtering, separating an optimum translational motion curve, a cardiac motion curve, a respiratory motion curve and a high-frequency motion curve according to the variation frame sequence of translational motion, a cycle of the cardiac motion signal, a range of a respiratory motion signal cycle, and a range of a high-frequency motion signal cycle.

A method for maximizing throughput of a centralized radio relay network based on depth deterministic policy gradient comprises the following steps: 1) maximizing throughput in the centralized radio relay network through regenerative energy optimization management, wherein, the optimization problem is described as a multivariable optimization problem; 2) decomposing the problem P1 into two parts ofoptimization: Power sub-optimization and slot sub-optimization, i.e., deep deterministic strategy gradient method optimizes variables pi and (img file = 'DDA000173585526000011. TIF' wi= '48' he= '66'/) to obtain the optimal ri. A method for maximizing system efficiency with maximum throughput in a centralized radio relay network by combining time scheduling and power allocation is provided.

Disclosed is a cold-rolling mill multivariate strip shape control method based on a constrained optimization algorithm. The method includes the steps that a multivariate optimization model used for solving an optimal regulating quantity of each strip shape regulating mechanism is designed; the multivariate optimization model is converted into a standard form of an optimization problem; an initial searching point for solving the multivariate optimization problem of the standard form is designed; a searching mechanism in the direction of each coordinate axis is designed; searching is performed in the direction of each coordinate axis, and a candidate value of an optimal point is calculated; a searching termination criterion is designed; and a cold-rolling mill multivariate strip shape control system model is established. By means of the cold-rolling mill multivariate strip shape control method based on the constrained optimization algorithm, the multivariate strip shape optimization model can be converted into a series of univariate optimization problems, and the method has the advantages of being high in calculation efficiency, saving the storage space of a controller and being capable of achieving concurrent computation and the like, and is quite suitable for development of a cold-rolling strip shape control system with the multiple strip shape regulating mechanisms.

The invention discloses a windproof grid pneumatic optimization method based on Kriging improved model, which takes the height and the void ratio of a windproof grid as optimization variables, and obtains the height and the void ratio values of the windproof grid with the optimal windproof effect through optimization. According to the method, the influence of the height and porosity of the windproof fence is considered, and multivariable optimization design is carried out; the updating of the Kriging agent model is improved by adopting a multi-point point adding criterion, so that the convergence speed of the wind barrier optimization design is increased. The method is simple and effective, and compared with a traditional optimization algorithm (such as a genetic algorithm), optimization time can be saved to a great extent, and an optimal solution can be obtained accurately and quickly.

The invention relates to a cold-rolled steel strip shape control system for actively preventing saturation phenomenon of an executer. The cold-rolled steel strip shape control system comprises a strip shape deviation computing module, a strip shape deviation signal filtering processing module, a steel strip form multi-variable optimization controller, a compensation regulation module and a rolling mill transmission device, wherein one output end of the rolling mill transmission device is connected with the strip shape deviation signal filtering processing module through a real-time position state acquiring module of the rolling mill transmission device and a current strip shape regulation and control capability online evaluation computing module; the other output end of the rolling mill transmission device is connected with the compensation regulation module; the third output end of the rolling mill transmission device is connected with an online strip shape measuring module through a rolling mill outlet strip shape; and the output end of the online strip shape measuring module is connected with the strip shape deviation computing module. By adopting the cold-rolled steel strip shape control system, the problem of poor strip shape control effect is solved, the saturation phenomenon occurring probability of rolling mill transmission equipment is lowered to the maximum extent, the service life of a strip shape control device is prolonged, and the prolonging of the service life of the rolling mill equipment and control over the production cost are facilitated.

An energy collection wireless relay network throughput maximum method based on deep reinforcement learning comprises the following steps of: 1) achieving the maximum throughput through reuseable energy optimization management in an energy collection wireless relay network, wherein the optimization problem describes a multi-variable optimization problem; 2) decomposing a problem P1 into two portions for optimization: power sub optimization and slot time sub optimization, namely, the reinforcement learning algorithm is employed to optimize a variable pi and a variable as shown in the descriptionto obtain an optimal ri. The present invention provides a method for achieving the maximum throughput and the maximum system benefit in the energy collection wireless relay network through combination of time dispatching and power distribution.

A control system is configured to operate a multiple-input system to achieve an optimal value for a performance variable of the multiple-input system. The control system includes a mapper configured to generate a mapping from a first number of manipulated variables to a second number of latent variables. The second number is smaller than the first number and each of the latent variables includes a linear combination of the manipulated variables. The control system also includes an extremum-seeking controller configured to receive the performance variable from the multiple-input system as a feedback and modulate values of the second number of latent variables to drive the performance variable to the optimal value. The mapper is further configured to use the mapping to translate modulated values of the second number of latent variables to modulated values of the first number of manipulated variables and provide the modulated values of the first number of manipulated variables to the multiple-input system.

A method for maximizing the throughput of an energy collecting type relay network based on deep multi-network learning comprises the following steps: 1) maximizing the throughput in the centralized wireless relay network through regenerative energy optimization management, wherein, the optimization problem is described as a multivariable optimization problem; 2) decomposing the problem P1 into twoparts of optimization: power sub-optimization and time slot sub-optimization, i. e., optimizing variables pi and taui by deep multi-network learning to obtain the optimal ri. A method for maximizingsystem efficiency with maximum throughput in a centralized radio relay network by combining time scheduling and power allocation is provided.

The invention discloses a closed-loop control method of cold-rolled sheet shape based on lag compensation. The closed-loop control method comprises the specific steps of manufacturing a structure of a sheet shape closed-loop control system based on a multivariate optimization model; designing the multivariate optimization model of the sheet shape closed-loop control system; manufacturing PID control models of all sheet shape regulating mechanisms; manufacturing PID+Smith predictor control models of all the sheet shape regulating mechanisms; determining process models of control circuits of all the sheet shape regulating mechanisms, and setting corresponding PID parameters; and establishing control modes of the sheet shape closed-loop control system. The closed-loop control method has the advantages that the influence of measurement lag to the stability of the sheet shape closed-loop control system during sheet shape control process can be removed through switching the sheet shape closed-loop control modes according to the rolling speed change, the structure is simple, the calculation efficiency is high, the control real time performance is relatively high, the stability of the sheet shape closed-loop control system is not influenced by measurement lag, and relatively high homeostatic control accuracy is achieved.

The invention discloses a pseudo-satellite layout method based on a genetic algorithm, and belongs to the technical field of navigation and positioning. By utilizing multivariable optimization advantages of a genetic algorithm, the pseudo-satellite layout method based on the genetic algorithm considering the whole pseudo-satellite coverage area is proposed, and the positioning precision and availability in the pseudo-satellite coverage area can be greatly improved. The pseudo-satellite layout method comprises the following steps of: (1) establishing a layout model according to a layout environment, and taking an average position precision factor in a layout area as a target function; (2) optimizing a target function value by using the genetic algorithm; (3) and outputting final pseudo-satellite layout coordinates and a target function value optimized by using the genetic algorithm.