目标函数

Theobjective functionis the function you want to optimize.Global Optimization Toolboxalgorithms attempt to find the minimum of the objective function. Write the objective function as a file or anonymous function, and pass it to the solver as a function handle. For more information, seeCompute Objective FunctionsandCreate Function Handle.

Temperature

Thetemperatureis a parameter in simulated annealing that affects two aspects of the algorithm:

Temperature can be a vector with different values for each component of the current point. Typically, the initial temperature is a scalar.

Temperature decreases gradually as the algorithm proceeds. You can specify the initial temperature as a positive scalar or vector in theInitialTemperatureoption. You can specify the temperature as a function of iteration number as a function handle in theTemperatureFcnoption. The temperature is a function of theAnnealing Parameter, which is a proxy for the iteration number. The slower the rate of temperature decrease, the better the chances are of finding an optimal solution, but the longer the run time. For a list of built-in temperature functions and the syntax of a custom temperature function, seeTemperature Options.

Annealing Parameter

Theannealing parameteris a proxy for the iteration number. The algorithm can raise temperature by setting the annealing parameter to a lower value than the current iteration. (SeeReannealing.) You can specify the temperature schedule as a function handle with theTemperatureFcnoption.

Reannealing

Annealingis the technique of closely controlling the temperature when cooling a material to ensure that it reaches an optimal state.Reannealingraises the temperature after the algorithm accepts a certain number of new points, and starts the search again at the higher temperature. Reannealing avoids the algorithm getting caught at local minima. Specify the reannealing schedule with theReannealIntervaloption.