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http://hdl.handle.net/10609/91516
Title: A simheuristic approach for the stochastic team orienteering problem
Author: Panadero Martínez, Javier  
Armas Adrián, Jésica de
Currie, Christine S.M.
Juan Pérez, Ángel Alejandro
Others: University of Southampton
Universitat Pompeu Fabra
Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Keywords: Monte Carlo methods
vehicle routing
stochastic processes
Issue Date: Dec-2017
Publisher: Winter Simulation Conference (WSC). Proceedings
Citation: Panadero, J., De Armas, J., Currie, C. & Juan, A. (2017). A Simheuristic to Solve the Stochastic Team Orienteering Problem. Winter Simulation Conference (WSC). Proceedings, 2017(). 3208-3217. doi: 10.1109/WSC.2017.8248039
Series/Report no.: Winter Simulation Conference, Las Vegas, EUA, 03-06, desembre de 2017
Project identifier: info:eu-repo/grantAgreement/TRA2013-48180-C3-P
info:eu-repo/grantAgreement/TRA2015-71883-REDT
info:eu-repo/grantAgreement/2017-1-ES01-KA103-036672
info:eu-repo/grantAgreement/20161ES01KA103023472
Also see: https://www.informs-sim.org/wsc17papers/includes/files/267.pdf
https://ieeexplore.ieee.org/document/8248039
Abstract: The team orienteering problem is a variant of the well-known vehicle routing problem in which a set of vehicle tours are constructed in such in a way that: (i) the total collected reward received from visiting a subset of customers is maximized; and (ii) the length of each vehicle tour is restricted by a pre-specified limit. While most existing works refer to the deterministic version of the problem and focus on maximizing total reward, some degree of uncertainty (e.g., in customers¿ service times or in travel times) should be expected in real-life applications. Accordingly, this paper proposes a simheuristic algorithm for solving the stochastic team orienteering problem, where goals other than maximizing the expected reward need to be considered. A series of numerical experiments contribute to illustrate the potential of our approach, which integrates Monte Carlo simulation inside a metaheuristic framework.
Language: English
URI: http://hdl.handle.net/10609/91516
ISBN: 9781538634288
ISSN: 1558-4305
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