Changes between Version 1 and Version 2 of UsersSamples

Timestamp:

06/01/10 17:17:23 (16 years ago)

Author:

mkofler

Comment:

Added GA TSP sample documentation

UsersSamples

@@ -7 +7 @@
  * Genetic programming for artificial ant problem - A standard genetic programming algorithm for the artificial ant problem (Santa-Fe ant trail)
  * Genetic programming for symbolic regression - A standard genetic programming algorithm to solve a symbolic regression problem (Boston Housing dataset)
+
 [=#ESGriewank]
 == Evolution Strategy - Griewank == 
+A pre-defined evolution strategy which solves the 10-dimensional [TestFunctions#GriewankFunction Griewank test function]. HeuristicLab 3 provides a set of real valued test functions for benchmarking purposes. For a full overview please go the [TestFunctions Test Functions] wiki page. 
+
+'''Algorithm:''' Evolution Strategy
+
+'''Algorithm Parameters:'''
+ * Population Size: 20
+ * Children: 500
+ * !MaximumGenerations: 200
+ * !ParentsPerChild: 5
+ * !PlusSelection: False (Comma Selection)
+ * Recombinator: !AverageCrossover
+ * Mutator: !NormalAllPositionsManipulator
+
+'''Problem:''' Single Objective Test Function
+
+'''Problem Parameters:'''
+ * !BestKnownQuality: 0
+ * !BestKnownSolution: [0;0;0;0;0;0;0;0;0;0]
+ * Bounds: [-600, 600]
+ * Evaluator: !GriewankEvaluator
+ * Maximization: False
+ * !ProblemSize: 10
+ * !SolutionCreator: !UniformRandomRealVectorCreator
+
 [=#GATSP]
 == Genetic Algorithm - TSP == 
+This sample demonstrates how to employ a genetic algorithm to optimize a travelling salesman problem instance, namely "ch130" from the [http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/ TSP Lib]. 
+
+'''Algorithm:''' Genetic Algorithm
+
+'''Algorithm Parameters:'''
+ * !PopulationSize: 100
+ * Elites: 1
+ * !MutationProbability: 5%
+ * !MaximumGenerations: 1000
+ * Selector: !ProportionalSelector
+ * Crossover: Crossover2 (cf. Affenzeller, M. et al. 2009. Genetic Algorithms and Genetic Programming - Modern Concepts and Practical Applications. CRC Press. p. 135)
+ * Mutator: !InversionManipulator
+
+'''Problem:''' Single Objective Test Function
+
+'''Problem Parameters:'''
+ * !BestKnownQuality: 6110
+ * !BestKnownSolution: The best known solution of this TSP instance (cf. TSP Lib)
+ * Coordinates: The x and y coordinates of the cities
+ * Evaluator: !TSPRoundedEuclideanPathEvaluator
+ * Maximization: False
+ * !SolutionCreator: !RandomPermutationCreator
+ * !UseDistanceMatrix: True