.. _simulated_annealing-py:


######################
simulated_annealing.py
######################

SIMO metaheuristic simulated annealing algorithm

    >>> epsilon = 0.00001


****************************
class SimulatedAnnealing(Optimizer):
****************************

Simulated annealing heuristic optimization algorithm implementation. Example keyword arguments :: 

    repeats=10
    initial_solutions=100
    maximum_iterations=1000
    starting_temperature=0.999
    freezing_temperature=0.001
    cooling_factor=0.95
    iterations_per_temperature=100
    iteration_multiplier=0.95



def __init__(self, logger, logname, optlogger, taskdef, simdbin, opdbin,
             simdbout, opdbout, \*\*keywords):
========================================================================

Initialize optimizer::

    >>> from simo.optimization.simulated_annealing import SimulatedAnnealing
    >>> execfile('optimization/test/mocks4optimizer.py')
    >>> chart_path = 'optimization/test'

    >>> sa = SimulatedAnnealing(
    ...     logger, logname, taskdef, simdbin, simdbout, False, False, 
    ...     False, chart_path, True, 'test', True, keyword1='test-kw')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "repeats" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "initial_solutions" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "maximum_iterations" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "starting_temperature" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "freezing_temperature" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "cooling_factor" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "iterations_per_temperature" missing!')
    Called Logger.log_message(
        'optimization-test',
        'ERROR',
        'Parameter "iteration_multiplier" missing!')

    >>> sa = SimulatedAnnealing(
    ...     logger, logname, taskdef, simdbin, simdbout, False, False, 
    ...     False, chart_path, True, 'test', True, 
    ...     repeats=2,
    ...     initial_solutions=5,
    ...     maximum_iterations=20,
    ...     starting_temperature=0.999,
    ...     freezing_temperature=0.001,
    ...     cooling_factor=0.95,
    ...     iterations_per_temperature=100,
    ...     iteration_multiplier=0.95)


def optimize(self):
===================

Run simulated annealinf optimization algorithm


def _run_SA(self, iteration):
=============================

Run SA algorithm for a single iteration/repeat

Parameters::

    iteration -- current simulated iteration as int

::

    >>> sa._stat_logger = ologger  # replace stat logger with a mock
    >>> sa._data = omatrix2  # replace data handler with a mock
    >>> sa._analyze_data()  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
    Called OMatrix.analyze_data(
        <Mock ... SimInputDB>,
        <bound method SimulatedAnnealing._add_info of 
        <simo.optimization.simulated_annealing.SimulatedAnnealing object at ...>>)
    True
    >>> sa.set_data(0)  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
    Called OMatrix.construct_data(0)
    True
    >>> sa._curr_U = 0.5  # set current utility
    >>> sa._best_U = 0.5  # set best utility
    >>> sa._run_SA()  # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
    Called OMatrix.solution_utility(array([...]))
    Called OMatrix.solution_feasibility(array([...]))
    Called OMatrix.compare_utilities(0.5, 1.0)
    Called OMatrix.compare_utilities(0.5, 1.0)
    Called OLogger.add_round(array([...]), 1.0, 1.0)
    ...