Version 7 (modified by gkronber, 14 years ago) (diff) |
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Travelling Salesman Problem
The traveling salesman problem (TSP) is certainly one of the classical as well as most frequently analyzed representatives of combinatorial optimization problems with a lot of solution methodologies and solution manipulation operators. The problem is that a person has to visit a number of cities starting from and returning to his home city. The goal is to find a tour where every city is visited exactly once and where the travel distances become minimal.
Problem Parameters:
Parameter | Description |
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BestKnownQuality | The quality of the best known solution of this TSP instance. |
BestKnownSolution | The best known solution of this TSP instance. |
Coordinates | The x- and y-Coordinates of the cities. |
DistanceMatrix | The matrix which contains the distances between the cities. |
Evaluator | TSPRoundedEuclideanPathEvaluator: The operator which should be used to evaluate TSP solutions. |
Maximization | Set to false as the Traveling Salesman Problem is a minimization problem. |
SolutionCreator | RandomPermutationCreator: The operator which should be used to create new TSP solutions. |
UseDistanceMatrix | True if a distance matrix should be calculated and used for evaluation, otherwise false. |
Is there a sample/tutorial?
Yes, HeuristicLab comes with a set of pre-configured algorithms that solve the "ch130" traveling salesman problem from the TSPLIB:
TPS Operators
TSPRoundedEuclideanPathEvaluator
An operator which evaluates TSP solutions given in path representation using the rounded Euclidean distance metric.
Operator Parameters:
Parameter | Description |
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Coordinates | The x- and y-Coordinates of the cities. |
DistanceMatrix | The matrix which contains the distances between the cities. |
TSPTour | The TSP solution given in path representation which should be evaluated. |
TSPTourLength | The evaluated quality of the TSP solution. |
UseDistanceMatrix | True if a distance matrix should be calculated and used for evaluation, otherwise false. |