Configuring the Optimization Techniques

You can configure some of the Optimization technique options.

You can map many of the various technique options to parameters so that they are dynamically driven at run time. For more information, see Mapping Options and Attributes to Parameters.


In this section:

Configuring the Adaptive Simulated Annealing (ASA) Technique
Configuring the Archive-Based Micro Genetic Algorithm (AMGA) Technique
Configuring the Downhill Simplex Technique
Configuring the Evolutionary Optimization (EVOL) Algorithm
Configuring the Hooke-Jeeves Technique
Configuring the Large Scale Generalized Reduced Gradient (LSGRG) Technique
Configuring the Mixed-Integer Sequential Quadratic Programming (MISQP) Technique
Configuring the Modified Method of Feasible Directions (MMFD) Technique
Configuring the Multifunction Optimization System Tool (MOST) Technique
Configuring the Multi-Island Genetic Algorithm Technique
Configuring the Multi-Objective Particle Swarm Technique
Configuring the Neighborhood Cultivation Genetic Algorithm (NCGA) Technique
Configuring the Non-Dominated Sorting Genetic Algorithm (NSGA-II) Technique
Configuring the Pointer Automatic Optimizer Technique
Configuring the Sequential Quadratic Programming (NLPQLP) Technique
Configuring the Stress Ratio Technique