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anneal__define.pro
The anneal class performs simulated annealing to maximize a fitness function. This is a little different than normal, where annealing minimizes a penalty (or energy) function.
Simulated annealing maximizes a function by taking random steps in parameter space from the current input. At each step, the function to maximize is evaluated given the current input. If the input yields a higher fitness than the previous input, it is automatically accepted and the old input discarded. If it is lower, than it is accepted with a probability that decreases as the simulation continues. The process continues, drawing new random inputs and occasionally swapping out the old inputs, until the simulation ends. Thus, the process transitions from a random walk to a hill-climbing algorithm; this helps prevent getting stuck at local maxima.
Class description for anneal
Routines
result = anneal::selectTrial(state)This function selects the next trial input, given the current input.
result = anneal::fitness(state)This function evaluates the target function on a given input.
result = anneal::temperature(step)This function calculates the "temperature" at a given iteration of the simulation.
result = anneal::getBestState( [fitness=fitness])This function returns the best set of inputs encountered during the run
result = anneal::getBestFitness( [state=state])Returns the best maximum function output encountered during the simulation
result = anneal::getAllStates(fitnesses=fitnesses)Returns the sequence of inputs attempted during the simulation.
result = anneal::getAllFitnesses(states=states)Returns all of the function evaluations computed during the simulation.
anneal::runresult = anneal::init(start_state, nstep, save=save, verbose=verbose)This function initializes the object
anneal::cleanupanneal__define
Routine details
topanneal::selectTrial
result = anneal::selectTrial(state)
This function selects the next trial input, given the current input. This is not implemented; each individual problem must subclass this class, overriding the selectTrial method.
Parameters
- state in required
The current input
topanneal::fitness
result = anneal::fitness(state)
This function evaluates the target function on a given input. Again, this function must be overridden in a subclass in order for the procedure to work.
Parameters
- state in required
The input to evaluate
topanneal::temperature
result = anneal::temperature(step)
This function calculates the "temperature" at a given iteration of the simulation. This should probably be overridden for specific implementations, though a default cooling function is provided.
Parameters
- step in required
The iteration number of the simulation
topanneal::getBestState
result = anneal::getBestState( [fitness=fitness])
This function returns the best set of inputs encountered during the run
Keywords
- fitness in optional
Set to a named variable to hold the function's output at the returned set of inputs
topanneal::getBestFitness
result = anneal::getBestFitness( [state=state])
Returns the best maximum function output encountered during the simulation
Keywords
- state in optional
Set to a named variable to hold the input corresponding to the maximum function output
topanneal::getAllStates
result = anneal::getAllStates(fitnesses=fitnesses)
Returns the sequence of inputs attempted during the simulation. Only works if /SAVE was set during object creation
KEYWORD_PARAMETERS: fitnesses: Set to a named variable to hold all of the function evaluations.
Return value
An array of all the states _
Keywords
- fitnesses
topanneal::getAllFitnesses
result = anneal::getAllFitnesses(states=states)
Returns all of the function evaluations computed during the simulation. Only works if /SAVE was set during object creation.
KEYWORD_PARAMETERS: states: Set to a named variable to hold all of the inputs tried.
Keywords
- states
topanneal::run
anneal::run
topanneal::init
result = anneal::init(start_state, nstep, save=save, verbose=verbose)
This function initializes the object
Parameters
- start_state in required
The seed input value to start the simulation on.
- nstep in required
The number of iterations to run the simulation for
Keywords
- save
- verbose
topanneal::cleanup
anneal::cleanup
topanneal__define
anneal__define
File attributes
| Modifcation date: | Fri Jul 8 13:46:48 2011 |
| Lines: | 275 |