= SASEGASA =
The self-adaptive segregative genetic algorithm with simulated annealing aspects developed by (Affenzeller et al. 2009). 

'''Algorithm Parameters:'''
||= Parameter         =||= Description =||
|| Analyzer            || !MultiAnalyzer: The operator used to analyze the villages. ||
|| !ComparisonFactorLowerBound || The lower bound of the comparison factor (start). ||
|| !ComparisonFactorModifier || The operator used to modify the comparison factor. ||
|| !ComparisonFactorUpperBound || The upper bound of the comparison factor (end). ||
|| Crossover           || The operator used to cross solutions. ||
|| Elites              || The numer of elite solutions which are kept in each generation. ||
|| !FinalMaximumSelectionPressure || The maximum selection pressure used when there is only one village left. ||
|| !MaximumGenerations || The maximum number of generations which should be processed. ||
|| !MaximumSelectionPressure || The maximum selection pressure that terminates the algorithm. ||
|| !MutationProbability || The probability that the mutation operator is applied on a solution. ||
|| Mutator             || The operator used to mutate solutions. ||
|| !NumberOfVillages    || The initial number of villages. ||
|| !OffspringSelectionBeforeMutation || True if the offspring selection step should be applied before mutation, false if it should be applied after mutation. ||
|| Population Size     || The size of the population of solutions. ||
|| Seed                || The random seed used to initialize the new pseudo random number generator. ||
|| !SelectedParents    || How much parents should be selected each time the offspring selection step is performed until the population is filled. ||
|| Selector            || !ProportionalSelector: The operator used to select solutions for reproduction. ||
|| !SetSeedRandomly    || True if the random seed should be set to a random value, otherwise false. ||
|| !SuccessRatio       || The ratio of successful to total children that should be achieved. || 
|| !VillageAnalyzer    || The operator used to analyze each village. ||

'''Is there a sample/tutorial?'''

Not yet, but we might add one in the future if there is demand. Meanwhile, have a look at our other samples shipped with HeuristicLab [[UsersTSPSample| here]]. 

'''References:'''
* Affenzeller, M. et al. 2009. Genetic Algorithms and Genetic Programming - Modern Concepts and Practical Applications. CRC Press.