Optimisation par modèle de substitution
Solveur d'optimisation par modèle de substitution pour fonctions objectif coûteuses, avec limites et contraintes d'entiers facultatives
Utilisez l’optimisation par modèle de substitution pour les fonctions objectif coûteuses (qui prennent du temps). Le solveur requiert des limites finies sur toutes les variables, autorise les contraintes d'inégalité non linéaire et accepte les contraintes entières sur les variables sélectionnées. Le solveur peut éventuellement sauvegarder son état après chaque évaluation de fonction, permettant ainsi une récupération après des arrêts prématurés.
Fonctions
Tâches du Live Editor
| Optimize | Optimize or solve equations in the Live Editor |
Rubriques
Optimisation par modèle de substitution basée sur les problèmes
- Optimize Multidimensional Function Using surrogateopt, Problem-Based
Basic example minimizing a multidimensional function in the problem-based approach. - Mixed-Integer Surrogate Optimization, Problem-Based
Solve integer and mixed-integer problems using the problem-based approach andsurrogateopt. - Specify Starting Points and Values for surrogateopt, Problem-Based
Specify start points and their function values usingoptimvaluesin the problem-based approach. - Solve Feasibility Problem Using surrogateopt, Problem-Based
Solve a feasibility problem using the problem-based approach andsurrogateoptsolver. - Feasibility Using Problem-Based Optimize Live Editor Task
Solve a nonlinear feasibility problem using the problem-based Optimize Live Editor task and several solvers. - Optimize a Satellite Constellation While Satisfying Constraints on Ground Station Access
Find the best constellation of satellites subject to visibility constraints.
Optimiser avec l'optimisation par modèle de substitution
- Surrogate Optimization of Multidimensional Function
Solve a multidimensional problem usingsurrogateopt,patternsearch, andfmincon, and then compare the results. - Modify surrogateopt Options
Search for the global minimum usingsurrogateopt, and then modify options of the function to revise the search. - Interpret surrogateoptplot
How to interpret asurrogateoptplotplot. - Compare Surrogate Optimization with Other Solvers
Comparesurrogateopttopatternsearchandfminconon a nonsmooth problem. - Surrogate Optimization of Six-Element Yagi-Uda Antenna
Solve an antenna design problem using surrogate optimization. - Work with Checkpoint Files
Shows how to use checkpoint files to restart, recover, analyze, or extend an optimization. - Surrogate Optimization with Nonlinear Constraint
Solve a problem containing a nonlinear ODE with a nonlinear constraint usingsurrogateopt. - Convert Nonlinear Constraints Between surrogateopt Form and Other Solver Forms
Presents techniques for converting objective and nonlinear constraint functions for other solvers to and fromsurrogateoptform. - Mixed-Integer Surrogate Optimization
Integer-constrained surrogate optimization. - Optimal Component Choice Using surrogateopt
Choose components from lists to best fit a response curve. - Solve Nonlinear Problem with Integer and Nonlinear Constraints
Compare the solution of a nonlinear problem both with and without integer constraints. - Solve Feasibility Problem
Usesurrogateoptto solve a feasibility problem. - Fix Variables in surrogateopt
Fix some variables by setting their upper and lower bounds equal. - Optimize Simulink Model in Parallel
This example shows how to optimize a Simulink® model in parallel using several Global Optimization Toolbox solvers. - Improve surrogateopt Solution or Process
Hints for obtaining a better solution or obtaining a solution more quickly.
Introduction à l'optimisation par modèle de substitution
- Qu'est-ce que l'optimisation par modèle de substitution ?
L'optimisation par modèle de substitution tente de trouver un minimum global d'une fonction objectif en utilisant quelques évaluations de fonctions objectif. - Surrogate Optimization Algorithm
Learn details of the surrogate optimization algorithm, when run in serial or parallel. - Surrogate Optimization Options
Explore the options for surrogate optimization, including algorithm control, stopping criteria, command-line display, and output and plot functions.
