Recherche globale ou à points de démarrages multiples
Solveurs à points de démarrages multiples pour l'optimisation basée sur le gradient, avec ou sans contrainte
Ces solveurs s'appliquent aux problèmes avec des fonctions objectif lisses et des contraintes. Ils exécutent les solveurs Optimization Toolbox™ à plusieurs reprises pour essayer de localiser une solution globale ou plusieurs solutions locales.
Fonctions
Objets
Rubriques
Optimisation à démarrages multiples (MultiStart) basé sur des problèmes
- Minimiser la fonction non linéaire à l'aide d'un solveur à démarrage multiple (MultiStart) basé sur des problèmes
Trouvez une meilleure solution à un problème non linéaire à l'aide d'un solveur à démarrages multiples. - Specify Start Points for MultiStart, Problem-Based
Specify start points forMultiStartin the problem-based approach. - Find Multiple Local Solutions Using MultiStart or GlobalSearch, Problem-Based
Use thelocalfield of theoutputstructure to examine the points whereGlobalSearchandMultiStartstart. - MultiStart with lsqnonlin, Problem-Based
Fit a function to data usingMultiStartandlsqnonlin.
Notions de base sur l'optimisation de GlobalSearch et MultiStart
- Trouver des minima globaux ou locaux multiples
Exemple montrant queGlobalSearchrenvoie moins de solutions queMultiStart, souvent avec une qualité supérieure. - Maximizing Monochromatic Polarized Light Interference Patterns Using GlobalSearch and MultiStart
Find a global minimum in a problem having multiple local minima. - Optimize Using Only Feasible Start Points
Example showing how to avoid starting from infeasible points. - MultiStart Using lsqcurvefit or lsqnonlin
Shows how to use MultiStart to help find a global minimum to a least-squares problem.
Workflow d'optimisation
- Workflow pour GlobalSearch et MultiStart
Comment configurer et exécuter les solveurs. - Create Problem Structure
Provides detailed steps for creating a problem structure. - Create Solver Object
Describes what a solver object is, and how to set its properties. - Set Start Points for MultiStart
Provides details on the ways to set the start points. - Run the Solver
Provides basic examples of the complete workflow for both GlobalSearch and MultiStart.
Techniques pour une recherche efficace
- Parallel MultiStart
Shows how to compute in parallel for faster searches. - Isolated Global Minimum
An extended example showing ways to search for a global minimum. - Refine Start Points
Examples of how to search your space effectively and efficiently. - Change Options
Considerations in setting local solver options and global solver properties. - Reproduce Results
How to set random seeds to reproduce results.
Examiner les résultats
- Iterative Display
Describes the two types of iterative display for monitoring solver progress. - Global Output Structures
Describes the types of output structures that GlobalSearch and MultiStart can return. - Visualize the Basins of Attraction
Example showing how to plot multiple initial and final points in a 2-D problem. - Output Functions for GlobalSearch and MultiStart
Provides details and an example of monitoring and halting solvers by using output functions. - Plot Functions for GlobalSearch and MultiStart
How to use both built-in and custom plot functions for monitoring solution progress.
Introduction aux solveurs à démarrage multiple (MultiStart)
- Problems That GlobalSearch and MultiStart Can Solve
GlobalSearch and MultiStart apply to smooth problems where there are multiple local solutions. - How GlobalSearch and MultiStart Work
Describes the solver algorithms. - Single Solution
Describes the first four outputs, usually calledx,fval,exitflag, andoutput, from bothGlobalSearchandMultiStart. - Multiple Solutions
Describes how to obtain multiple solutions from GlobalSearch and MultiStart, and how to change the definition of distinct solutions. - GlobalSearch and MultiStart Properties (Options)
Describes properties of GlobalSearch and MultiStart objects.
