460 results about "Design space" patented technology

The invention discloses an automobile front subframe lightweight design method considering modal constraint. The method comprises the following steps: (1) constructing a front subframe parameterized model and a weight-modal simulation model by adopting CATIA (Computer-graphics Aided Three-dimensional Interactive Application) and Altar Optistruct; (2) establishing a population in a design space based on a space filling Latin hypercube sampling method; (3) constructing a classification cooperation speed updating formula based on a particle swarm algorithm to generate offspring particle individuals; (4) constructing a Gaussian process machine learning model and a fitness evaluation function, and screening an optimal offspring particle individual based on a feasibility rule; and (5) constructing a comprehensive score calculation formula according to a statistical ranking method to determine the updating condition of the population individuals, updating the database and skipping to the step (3) until the optimized structure meets the requirement. According to the method, the coverage capability of the filial generation in the target space is enhanced through the classification collaborative speed updating formula, and the prediction precision of the Gaussian process machine learning model is continuously improved, so that the optimization performance of the lightweight of the front subframe of the automobile is improved.

The invention belongs to the technical field of material structure optimization, and discloses an enhanced structure design method and system for a three-period minimal curved surface, and the method comprises the steps: modeling a geometric model of the three-period minimal curved surface, and exporting the model; expanding a design domain of the geometric model to obtain a corresponding expanded design space of the three-period minimal curved surface; a design space file is converted into an analysis data structure, a general expression mode is constructed for the three-period minimum curved surface, an equal geometric element stiffness matrix is solved by using a Gaussian integral method and the elastic performance of each point in a design domain and assembled into a global stiffness matrix, and the structural response of the model is solved; constructing a local density distribution function in the Bayesian unit, and assembling all LDDFs to obtain a global density distribution function for presenting structural topology; and constructing a stiffness maximization topological optimization mathematical model for the TPMS, calculating an objective function and analyzing sensitivity, and carrying out iterative updating on design variables in the optimization model based on an optimal criterion method to obtain a reinforced structure configuration.

The invention relates to a spinel multi-objective reverse design method based on machine learning and a Bayesian optimization algorithm, electronic equipment and a storage medium, and the design method comprises the steps: firstly extracting related data of a spinel material from a database, and constructing a balanced data set through preprocessing; feature engineering is carried out, a comprehensive feature set is constructed, and key features are reserved; then training a multi-target prediction model through hyper-parameter optimization by using a multi-task gradient elevator model; and finally, integrating to a Bayesian reverse design framework, expanding a design space through a specific encoder, and combining a Gaussian process proxy function and an expected hyper-volume improvement criterion to screen candidate materials meeting conditions and verify performance, thereby completing reverse design optimization. Compared with the prior art, the intelligent and efficient spinel novel multi-target reverse design method can be used for solving the problem of data scarcity, and development of high-performance spinel solar cell materials is accelerated.

The invention discloses a robust optimization method based on D optimum and considering intake and exhaust influences, a medium and a program product, and belongs to the technical field of aerodynamic optimization design of aircrafts. According to the method, a representative small sample set is constructed by introducing a D optimal criterion, optimization coverage of a design space is realized by maximizing an information matrix determinant, and an optimization objective function is formed by a weighted sum of a mean value and a standard deviation of aerodynamic performance so as to balance performance improvement and robustness optimization. An FFD method is adopted to carry out geometric parametric modeling on the aerodynamic configuration and the intake and exhaust system of the aircraft, an uncertainty quantitative agent model is established through a GPCE method, statistical characteristics and gradient information of a target function are analyzed and calculated, iterative updating is carried out through a gradient optimization algorithm, and it is ensured that design constraints and convergence criteria are met. According to the method, the uncertainty influence of geometric parameters and intake and exhaust conditions is fully considered, the aerodynamic performance of the aircraft is improved, and the adaptability and robustness under actual flight conditions are enhanced.

The invention discloses an aircraft aerodynamic performance analysis method, which comprises the following steps: constructing a multi-dimensional parameterized model integrating aerodynamic / structure / thermal control, and outputting a global design space; based on a global design space, fusing sparse fluid dynamics and engineering data to train an agent model, and verifying the cross-speed domain reliability; decoupling the centroid / lift-drag ratio / thermal load conflict by using the proxy model, and generating a speed domain adaptive configuration library; executing fluid-structure-thermal field strong coupling simulation by utilizing a shock wave-boundary layer self-adaptive grid technology aiming at the speed domain self-adaptive configuration library; based on a fluid-structure-thermal field strong coupling mechanism, utilizing a dynamic sensing technology to predict the aerodynamic performance of the aircraft; and integrating dynamic prediction data and digital simulation, calibrating model parameters, and outputting an aerodynamic performance report and an optimization scheme. According to the method, the problems of insufficient multi-physical field integration, low cross-speed domain reliability, poor configuration self-adaption and low coupling simulation precision in aerodynamic performance analysis of a traditional aircraft are solved.

The invention discloses a building facade optimization method and system based on sustainable analysis, and relates to the technical field of data processing. According to the method, parametric modeling is carried out on the external facade of a target building, and a design space is defined; training a machine learning model integrating energy consumption, carbon emission, cost and lighting prediction functions by using historical data; building an optimization problem by taking external facade parameters as decision variables and taking minimization of energy consumption, carbon emission and cost and maximization of lighting as targets, and automatically generating an optimal scheme set by adopting a multi-target optimization algorithm; a decision maker is assisted to select a final scheme through a visual interface, and a corresponding BIM model is output; the method effectively solves the problems that a traditional design method is difficult to coordinate multi-target conflicts, depends on experience and is low in efficiency, and can automatically and intelligently generate an optimal design scheme which is energy-saving, low-carbon, low-cost and good in lighting performance.

The invention discloses a wafer level chip system design space construction and rapid parameter search method. The method comprises the steps of task graph definition, prefabricated member parameter quantification, joint model construction based on task graph features and prefabricated member features, and Bayesian optimization implementation strategy. According to the technical scheme, construction and search of the design space can be guided, so that the number of times of calling a simulator is reduced, and construction of the design space of the wafer-level chip system architecture, efficient parameter search and performance evaluation are achieved. The method can be used for agile design and hardware implementation of a multi-chip integrated wafer-level chip system architecture.

The invention provides a centrifugal pump performance optimization method and device, computer equipment and a storage medium, and belongs to the field of centrifugal pump design. The method comprises the steps that a parameterized model of a centrifugal pump impeller is established to define the geometrical shape of the centrifugal pump impeller, a design space is determined, and a plurality of sample points are generated; for each sample point, performing computational fluid dynamics simulation, adjusting inlet pressure, monitoring a ratio of simulation lift to rated lift, determining critical cavitation pressure corresponding to the sample point, and storing flow field data to construct a data set; training an agent model by using the data set; the lift, the efficiency and the critical cavitation pressure serve as targets, design variables serve as optimization variables, performance is evaluated through an agent model, global optimization is conducted through a multi-target optimization algorithm, and a target design scheme is selected from a Pareto solution set obtained through optimization. Therefore, the centrifugal pump performance under different design variables can be quickly and accurately predicted, multiple targets are effectively balanced, and a comprehensive optimization solution is provided.

The innovation is the Landscape Syntax Algorithm, a new analytical framework to transcend the age-old limitations of space syntax. It integrates the highly versatile idea of landscape. Space syntax is largely objective and deals with the arrangement of space, along with little or no consideration for the more subjective parts of human aspects and experiences. Thus, the Landscape Syntax Algorithm fills that gap by providing a model that marries objective spatial measures with the more subjective cognitive and experiential aspects of landscape. This is carried out by infusing perceptual cognition and history / contextual layers within spatial analysis. Hence, there is a thorough reading of the relation between human experience and the built world. It opens up the opportunity to unify the most objective spatial configuration and subjective perceptual cognition to provide a powerful resource for the architect, urban planner, or researcher interested in analyzing and designing spaces that connect to the human experience in a more profound and mature sense. This invention enables quantification and analysis of landscape as moving and interactive phenomena towards a much more human-oriented contextual design of space.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures include: obtaining a design space, design criteria, and boundary conditions for numerical simulation; defining an application of the boundary conditions to a voxelized mesh, including specifying a distribution of a load to nodes of voxels in the voxelized mesh that correspond to a surface of preserve geometry; and iteratively modifying a generatively designed three dimensional shape in the design space in accordance with the design criteria and a physical response of the modeled object determined by the numerical simulation performed using the application of the boundary conditions to the voxelized mesh, wherein the distribution of the total loading value during determination of the physical response ensures an equivalence between the total loading value and a sum of loading values distributed to the respective nodes of the voxels that correspond to the surface.

The invention provides a shell optimization method and device of an electric drive controller, computer equipment and a storage medium, and belongs to the technical field of computers. According to the method, by accurately simulating the loading state, optimization can fit the actual operation situation. And the modal optimization boundary is reasonably set, the equivalent sound power is determined and the electromagnetic excitation is loaded, so that the vibration noise characteristics of the shell can be deeply analyzed, and a scientific basis is provided for optimization. The optimization design space model is determined according to the design scheme and the whole vehicle space, and the feasibility and adaptability of optimization are guaranteed. The material density distribution is obtained through topological optimization analysis, the surface topography topological feature distribution is determined, the performance requirement is met, meanwhile, the shell lightweight design is achieved, the overall performance, reliability and economical efficiency of the electric drive controller are improved, and the product competitiveness is enhanced.

The invention discloses a wireless power transmission coil optimization method and a related system, which can realize automation of coil structure parameters and multi-target global optimization by acquiring a coil geometric parameter space, constructing a comprehensive optimization function and performing iterative search in the coil geometric parameter space. The problems that in traditional design, the number of simulation iterations is large, design efficiency is low, local optimum is prone to occurring, and multiple performance indexes are difficult to balance are effectively solved, coil design efficiency and precision are remarkably improved, and dependence on artificial experience is reduced. Therefore, the number of manual intervention and simulation is remarkably reduced, the coil design efficiency is improved, and the prototype development period of the WPT system is shortened. Besides, iterative search is carried out in the parameter space, so that the whole design space can be effectively explored, a locally optimal solution trap can be jumped out, and a globally optimal or approximately globally optimal coil structure parameter combination can be obtained more possibly.

In various embodiments, a computer-implemented method for displaying object information associated with a computer-aided design, the method comprising displaying a design space that includes a plurality of design objects, generating a prompt that includes a set of object identifiers corresponding to a first set of design objects included in the plurality of design objects and a first query for a set of object labels corresponding to the first set of design objects, transmitting the prompt to at least one trained machine learning (ML) model for processing, receiving, from the at least one trained ML model, a first ML response that includes the set of object labels corresponding to the first set of design objects, and displaying the set of object labels within the design space.

The invention discloses a power turbine optimization method and system based on data driving, and the method comprises the steps: selecting a plurality of optimization working condition points, and determining turbine operation working condition parameters under each optimization working condition point; obtaining a blade profile optimization geometric parameter, and determining the dimension and the variation range of the blade profile optimization geometric parameter; forming a plurality of groups of geometric parameter schemes based on the blade profile optimization geometric parameters, and establishing a turbine three-dimensional model and dividing computational grids; cFD simulation is carried out on the turbine under each group of geometric parameter schemes, aerodynamic performance parameters of each geometric parameter scheme under each working condition are obtained, and a sample library is formed based on the blade profile optimization geometric parameters, turbine operation working condition parameters and the aerodynamic performance parameters so as to establish a neural network prediction model; and performing multi-objective optimization on the blade profile optimization geometric parameters by adopting a neural network prediction model to determine optimal blade profile geometric parameters. By means of the scheme, the optimal blade profile geometric parameter combination meeting the multiple performance targets at the same time can be efficiently searched in the design space.

An acoustic vibration coupling plane structure topological optimization method based on an energy finite element is characterized in that discretization processing and unit assembly of the energy finite element are carried out on an acoustic system by utilizing a unit independent grid method, an energy finite element model is constructed, and then the optimization of the acoustic performance of an acoustic vibration system is realized by combining the energy finite element model with the topological optimization method; according to the method, a unified analysis framework is provided for an acoustic vibration system, the dynamic change of a discontinuous interface of an energy density field in iterative optimization can be adapted, and a high-degree-of-freedom design space is provided; the calculation cost is reduced, the calculation efficiency is improved, and the accuracy of an analysis result is ensured.

The invention discloses an optimization design method and a manufacturing method of a heating structure. The optimization design method comprises the following steps: constructing a spiral line heating wire parameter model with adjustable spacing and arc supplement; a design space is constructed, the standard deviation, the variable coefficient and the uniformity of the temperature of the temperature measuring point are used as evaluation indexes, and an optimal Latin hypercube sampling method is adopted for experimental design and simulation analysis to obtain a real response value; based on the training sample and the real response values of the three evaluation indexes, respectively constructing Gaussian process regression models, and performing model optimization by using a Bayesian optimization method; constructing a multi-objective optimization mathematical model based on design variables and objective function response values obtained by the optimized Gaussian process regression model, and solving an optimization parameter combination based on an NSGA-II algorithm; and verifying a multi-objective optimization result. According to the method, the relationship between the design parameters and the performance indexes can be more accurately captured, the optimization efficiency and accuracy are improved, and the surface temperature uniformity of the heating disc is more effectively improved.

The invention discloses a physical perception-based generative three-dimensional reverse design method and system, which realize efficient exploration and optimization in a three-dimensional design space by constructing a unified physical-geometric potential representation and combining a two-stage optimization strategy. According to the method, shape and physical field data combined training is utilized to obtain potential representation, so that a geometric structure and physical constraints are compactly represented; on the basis, two stages of physical perception optimization are adopted: in the first stage, global exploration is performed in a potential manifold through a gradient-guided diffusion model, and an initial grid is generated; and in the second stage, the initial grid is locally optimized by utilizing target-driven topology maintenance optimization, so that the initial grid gradually approaches the target performance requirement. According to the method, the high-fidelity three-dimensional geometric design can be directly generated, the target performance and the result diversity of the design are remarkably improved, the method can be widely applied to aerospace, energy equipment and complex engineering structure design, and a new technical approach is provided for efficient implementation of the three-dimensional intelligent design.

The invention discloses a small modular prismatic high-temperature gas cooled reactor core optimization design method and system based on data driving. The method comprises the following steps: constructing a training data set; a data-driven agent model is trained to replace and execute high-cost simulation calculation; and exploring a design space and generating a group of Pareto optimal candidate solutions by using a multi-objective evolution algorithm and taking the proxy model as a fitness function evaluator. The key feature of the method is a closed loop of iterative verification and model updating: verifying the candidate solution through high-fidelity simulation, if the prediction precision does not meet the convergence criterion, expanding the verified new data point to a training data set, and retraining the agent model. According to the method, the calculation cost can be remarkably reduced, a complex design space can be efficiently explored, and a physically reliable reactor design scheme with better performance can be obtained.

The invention discloses a wind power blade design method and device, equipment, a medium and a product, and belongs to the field of wind power blade design. The wind power blade design method comprises the steps that input configuration data and value ranges corresponding to multiple design variables are obtained; variable values are selected from the value ranges corresponding to the design variables; blade appearance analysis is carried out based on the configuration data and the variable values, and candidate appearance data and performance data of the blade are obtained; evaluating whether the performance data meets a preset condition or not according to the target function and the constraint condition; if not, the variable value of the design variable is selected again, blade appearance analysis is conducted again, candidate appearance data and performance data are obtained, and the candidate appearance data obtained through last analysis are determined as final appearance data of the blade until the performance data meet the preset condition or the number of iterations reaches the preset number of times. The problem of multiple working conditions can be solved, and an optimal solution in a global design space can be obtained.

In various embodiments, a computer-implemented method for displaying a prompt space comprises displaying a design space comprising one or more design objects, receiving a selection of a current location within the design space, and displaying the prompt space at a placement location within the design space based on the current location.

The invention discloses an outer rotor permanent magnet synchronous motor torque optimization method, which comprises the following steps: 1) design parameter selection: selecting key characteristics of a motor stator slot as design parameters, including slot shoulder height Hs1, tooth length Hs2, chord length Bs0 and slot shoulder width Bs1; 2) finite element model construction: establishing a multi-target finite element model with cogging torque, torque pulsation and average torque as targets; 3) establishing an analytic model: establishing the analytic model of the motor torque by using an energy method and a repetitive unit method, and comparing the analytic model with the finite element model to verify the accuracy of the analytic model; 4) response surface model construction: based on the simulation data of the finite element model, performing finite element analysis by adopting a central composite design CCD, constructing a response surface model, performing sensitivity analysis on design variables, and determining the influence of each variable on an optimization target; and 5) optimization efficiency improvement: determining optimal configuration in a design space by using an adaptive genetic aggregation algorithm AGA, and achieving a multi-objective optimization effect.

The invention provides a design space position visualization quantifiable method suitable for bridge construction lofting, which specifically comprises the following steps: (1) Dynamo software reads a bridge floor road center line given by a design drawing, and generates a corresponding bridge based on the bridge floor road center line, comprising the following steps: sequentially generating a bridge pier corresponding to a bridge deck road center line, a support padstone at the top of the bridge pier and a bridge deck box girder falling on the support padstone; and (2) reading the bridge corresponding to the midline of the bridge floor road from the Dynamo software by the Revit software, and displaying the bridge. A Dynamo software and Revit software combined three-dimensional modeling calculation method is adopted, the Dynamo software quickly establishes piers, support cushion stones and box girders in batches under an absolute coordinate system, position coordinate calculation of important feature points on a bridge is further completed by means of the Dynamo software, and three-dimensional display is performed on the bridge constructed by the Dynamo software through the Revit software. And synchronously displaying the position coordinates of the important feature points.

The invention discloses a rotor blade optimization design method which comprises the following steps: firstly, establishing a multi-target blade layout optimization problem, performing parametric modeling on an initial blade, extracting blade layout parameters as design variables, then determining sampling points through experimental design, and calculating target values and constraint values; carrying out variance analysis to obtain sensitivity information of an optimization target to a design variable, carrying out multi-target optimization by adopting an evolutionary algorithm, setting an iteration stop condition to obtain a Pareto leading-edge solution set, carrying out design variable analysis on the selected individual to obtain a design variable analysis result, and based on the design variable analysis result and the sensitivity information, carrying out multi-target optimization on the Pareto leading-edge solution set; and dynamically adjusting the design space until an iteration stop condition is met, and outputting a final optimization scheme. A sand blind suppression target is embedded into a multi-target optimization framework, and a design space dynamic adjustment strategy is introduced, so that the conventional pneumatic / structural performance is ensured, the sand and dust concentration is remarkably reduced, and the environmental adaptability and the flight safety of a rotor wing are improved.

The invention discloses an integrated design method for a woven composite variable-curvature reinforced thin-wall structure, and the method comprises the steps: achieving the parametric modeling of a design model of the woven composite variable-curvature reinforced thin-wall structure through a Python language; the method comprises the following steps of: modeling a woven composite material variable curvature reinforced thin-wall structure design model for each sample point sampled in a design space of design variables, performing instability mechanical response solution by utilizing finite element software explicit dynamics, and then selecting a design variable optimal solution based on a deep neural network model in combination with a multi-objective optimization algorithm; and according to the optimal solution of the design variable, the variable-curvature reinforced thin-wall structure of the woven composite material is constructed. According to the method, integrated structural design is conducted on the woven composite material and the variable-curvature reinforced thin-wall structure, the design space of the woven composite material variable-curvature reinforced thin-wall structure is rich, the bearing efficiency of the woven composite material variable-curvature reinforced thin-wall structure is improved, and the further lightweight design requirement of the related engineering field is met.

The invention provides a laminar flow wing robust optimization method based on manifold learning, and belongs to the field of aircraft design, and the method comprises the steps: giving an initial geometrical shape and a design variable as a starting point of laminar flow wing robust optimization; filtering the design space based on a geometric fairing and Grassmann manifold coupling method, and deforming a design object; dynamically updating the volume grid by using an inverse distance interpolation method to ensure that the volume grid is consistent with the deformed geometrical shape; calculating flow field information according to the updated volume grid; obtaining derivative information about a design variable through a laminar flow discrete adjoint solver; and obtaining a design variable change direction according to the derivative information, generating a new design variable, and obtaining a steady optimization result of the laminar flow wing if an iteration result meets feasibility tolerance and optimality tolerance. According to the method, the robustness of laminar flow wing optimization can be improved, and the influence of a geometric parameterization form on the drag reduction effect of the optimization method is reduced, so that a more stable optimization result is obtained.

The invention provides a wing body fusion layout wide-speed-domain wide-frequency-band thin airfoil profile design method and an airfoil profile family, and the method is based on the analysis of the three-dimensional flow characteristics of the wing body fusion layout, selects typical subsonic, transonic and supersonic Mach number design points, balances the contradiction between induced resistance and wave resistance under different Mach numbers, and improves the design precision of the wing body fusion layout. The method comprises the following steps: selecting a multi-band set frequency point as a low-detectivity design point for a wide-band low-detectivity design of a wing body fusion layout; a low-dimensional large-scale and high-dimensional small-scale combined optimization design method is adopted to search a design space, and pneumatic and low-detectivity multi-disciplinary efficient design of a wing body fusion layout airfoil is achieved; the method comprises the following steps: selecting an optimized section from a wing according to regions, performing parameterization by adopting a multi-frame orthogonal overlapping FFD method based on the optimized section, introducing orthogonal control frames with different densities to realize refined hierarchical control of the optimized section airfoil, avoiding the problem of inconsistent physical scale deformation of the front and rear edges of the wing, and giving consideration to local refined design.

The invention discloses a bridge splicing part route optimization design method based on a constraint condition genetic algorithm, and relates to the technical field of bridge engineering design, and the method comprises the steps: building a hard constraint and soft constraint double-layer constraint system based on a standardized data set and a parameterized model in a step 2, and associating the system to fitness calculation of chromosomes; and based on a constraint processing result, integrating multi-objective optimization requirements, and constructing a fitness function. According to the method, a route is abstracted into a third-order cubic B-spline curve and parameterized coding is carried out, iteration is carried out in combination with a genetic algorithm, a design space can be globally explored in an optimizable control point range, and compared with traditional experience design, a better global solution can be found, and the problem of local optimum caused by experience limitation of engineers is avoided. The fitness function realizes multi-target quantitative integration through normalized indexes and adjustable weights, the weights of cost, smoothness and environmental influence can be flexibly adjusted according to project scenes, the problems of multi-target qualitative and difficult comparison in traditional design are solved, and the scheme adaptability is remarkably improved.

The invention discloses a front subframe lightweight design method and device based on RMNN, a medium and a program product, and the method comprises the steps: (1) constructing three simulation models of weight, stress and modal of a front subframe, and deducing a lightweight design model containing stress and modal constraints; (2) generating a population based on a uniform experimental design and a correlation criterion, performing simulation evaluation on the population, and constructing a database; (3) constructing a network architecture and training an RMNN; (4) generating a candidate frame set according to a random preferential strategy and the RMNN; and (5) establishing a radial basis function model, screening an optimal frame, performing simulation evaluation, updating the database and the population, returning to the step (3) until the optimization target reaches the standard, and outputting an optimal solution of the optimization parameter. According to the method, the feasible region is quickly searched through the RMNN, the problems that the high-dimensional design space search efficiency is low and the feasible region is difficult to recognize under multiple constraints are further solved in combination with the radial basis function model, and quick optimization can be carried out for the lightweight design of the front subframe.

The invention discloses a variant reconstruction AUV (Autonomous Underwater Vehicle) shape optimization method based on proxy-assisted multi-starting-point space reduction. The variant reconstruction AUV shape optimization method comprises the following steps: establishing a parameterized model of a variant reconstruction AUV; constructing a variant reconstruction AUV shape modeling-grid division-performance simulation automation framework, realizing input of design variables, and automatically performing variant reconstruction AUV shape modeling and watershed grid division; a variant reconstruction AUV shape hydrodynamic force simulation calculation framework is built, and assessment of variant reconstruction AUV hydrodynamic force performance is achieved; generating a plurality of groups of initial samples for a design space of design variables, calculating target function values corresponding to the samples by utilizing the simulation automation framework and the simulation calculation framework, and importing the samples and corresponding sailing resistance into a sample library; and performing optimization in the design space of the design variables by utilizing an agent-assisted multi-starting-point space reduction method to obtain an optimal solution of the variant reconstruction AUV shape design problem. According to the method, the reliability of an optimization result and the design efficiency can be improved, and the optimization time is shortened.

The invention relates to the technical field of lithologic reservoir scheme optimization, and discloses a multi-source multi-precision data fusion lithologic reservoir variable credibility proxy optimization method, which comprises the following steps of: constructing a low-precision carbonate reservoir numerical model only considering pores and a high-precision carbonate reservoir numerical model simultaneously considering pores and cracks; an optimization variable, a design space and a production scheme multi-objective optimization model with economic parameters and accumulated oil production as objective functions are set; sampling the optimization variables by adopting a Latin hypercube sampling method based on the design space so as to generate nl first production schemes and nh second production schemes; establishing a variable credibility agent model for fusing target functions calculated by the first production scheme and the second production scheme based on a scale function; and optimizing each parameter in the production scheme multi-objective optimization model based on a hybrid particle swarm algorithm. According to the method, the optimization efficiency and the quality of an optimization scheme are greatly improved.