The Probabilistic Traveling Salesman Problem with Deadlines (PTSPD) is a Stochastic Vehicle Routing Problem with a computationally demanding objective function. Currently heuristics using an approximation of the objective function based on Monte Carlo Sampling are the state-of-the-art methods for the PTSPD. We show that those heuristics can be significantly improved by using statistical tests in combination with the sampling-based evaluation of solutions for the pairwise comparison of solutions.
Using statistical tests for improving state-of-the-art heuristics for the probabilistic traveling salesman problem with deadlines / Weyland, Dennis; Montemanni, Roberto; Gambardella Luca, Maria. - 6927:1(2012), pp. 448-455. (Intervento presentato al convegno 13th International Conference on Computer Aided Systems Theory, EUROCAST 2011 tenutosi a Las Palmas de Gran Canaria, esp nel 2011) [10.1007/978-3-642-27549-4_57].
Using statistical tests for improving state-of-the-art heuristics for the probabilistic traveling salesman problem with deadlines
Montemanni Roberto;
2012
Abstract
The Probabilistic Traveling Salesman Problem with Deadlines (PTSPD) is a Stochastic Vehicle Routing Problem with a computationally demanding objective function. Currently heuristics using an approximation of the objective function based on Monte Carlo Sampling are the state-of-the-art methods for the PTSPD. We show that those heuristics can be significantly improved by using statistical tests in combination with the sampling-based evaluation of solutions for the pairwise comparison of solutions.
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