Optimización sustitutiva
Solucionador de optimización sustituto para funciones objetivo costosas, con límites y restricciones de números enteros opcionales
Utilice la optimización sustituta para funciones objetivas costosas (que consumen mucho tiempo). El solucionador requiere límites finitos en todas las variables, permite restricciones de desigualdad no lineal y acepta restricciones de números enteros en variables seleccionadas. El solucionador puede guardar opcionalmente su estado después de cada evaluación de función, lo que permite la recuperación de detencións prematuras.
Funciones
Tareas de Live Editor
Optimize | Optimizar o resolver ecuaciones en Live Editor |
Temas
Optimización sustitutiva basada en problemas
- 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
. - Especificar puntos de inicio y valores para surrogateopt, basado en problemas
Especifique los puntos de inicio y sus valores de función utilizandooptimvalues
en el enfoque basado en problemas. - Solve Feasibility Problem Using surrogateopt, Problem-Based
Solve a feasibility problem using the problem-based approach andsurrogateopt
solver. - Factibilidad utilizando la tarea Optimize basada en problemas de Live Editor
Resuelva un problema de factibilidad no lineal utilizando la tarea Optimize basada en problemas de Live Editor y varios solvers. - Optimize a Satellite Constellation While Satisfying Constraints on Ground Station Access
Find the best constellation of satellites subject to visibility constraints.
Optimizar mediante optimización sustitutiva
- 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 asurrogateoptplot
plot. - Compare Surrogate Optimization with Other Solvers
Comparesurrogateopt
topatternsearch
andfmincon
on 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 fromsurrogateopt
form. - 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
Usesurrogateopt
to 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.
Antecedentes de la optimización sustitutiva
- ¿Qué es la optimización sustitutiva?
La optimización sustituta intenta encontrar un mínimo global de una función objetivo utilizando pocas evaluaciones de la función objetivo. - 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.