Using statistical tests for improving state-of-the-art heuristics for the probabilistic traveling salesman problem with deadlines

Authors:
Dennis Weyland;Roberto Montemanni;Luca Maria Gambardella
Affiliations:
IDSIA, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Switzerland;IDSIA, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Switzerland;IDSIA, Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Switzerland
Venue:
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Year:
2011

Citing 4
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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.