Globale oder Suche mit mehreren Startpunkten
Solver für Gradientenoptimierung mit mehreren Startpunkten, mit oder ohne Nebenbedingungen
Diese Solver eignen sich für Probleme mit glatten Zielfunktionen und Randbedingungen. Sie führen Optimization Toolbox™-Solver wiederholt aus, um zu versuchen, eine globale Lösung oder mehrere lokale Lösungen zu finden.
Funktionen
Objekte
Themen
Problembasierter Mehrfachstart
- Minimize Nonlinear Function Using Multiple-Start Solver, Problem-Based
Find a better solution to a nonlinear problem using a multiple-start solver. - 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.
Grundlagen der GlobalSearch- und MultiStart-Optimierung
- Suchen Sie nach globalen oder mehreren lokalen Minima
Beispiel, das zeigt, dassGlobalSearchweniger Lösungen zurückgibt alsMultiStart, oft mit höherer Qualität. - 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.
Optimierungs-Workflow
- Workflow für GlobalSearch und MultiStart
Wie man die Solver einrichtet und ausführt. - 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.
Techniken für eine effektive Suche
- 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.
Ergebnisse prüfen
- 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.
Hintergrundinformationen zum Solver mit mehreren Startpunkten
- 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.
