Please use this identifier to cite or link to this item:

http://hdl.handle.net/10609/90878
Title: A multi-start simheuristic for the stochastic two-dimensional vehicle routing problem
Author: Guimarans Serrano, Daniel
Dominguez, Oscar
Juan Pérez, Ángel Alejandro
Martinez Masip, Enoc
Keywords: routing
vehicles
vehicle routing
computational modeling
heuristic algorithms
cost reduction
Monte Carlo methods
Issue Date: Dec-2016
Publisher: Winter Simulation Conference (WSC). Proceedings
Citation: Guimarans, D., Dominguez, O., Juan, A.A. & Martinez, E. (2016). A multi-start simheuristic for the stochastic two-dimensional vehicle routing problem. Winter Simulation Conference (WSC). Proceedings, 2016(), 2326-2334. doi: 10.1109/WSC.2016.7822273
Published in: Winter Simulation Conference, Washington D.C., EUA, 11-14, desembre de 2016
Project identifier: info:eu-repo/grantAgreement/TRA2013-48180-C3-P
info:eu-repo/grantAgreement/TRA2015-71883-REDT
info:eu-repo/grantAgreement/2014-CTP-00001
Also see: https://ieeexplore.ieee.org/document/7822273
https://www.informs-sim.org/wsc16papers/203.pdf
Abstract: The two-dimensional vehicle routing problem (2L-VRP) is a realistic extension of the classical vehicle routing problem where customers' demands are composed by sets of non-stackable items. Examples of such problems can be found in many real-life applications, e.g. furniture or industrial machinery transportation. Often, these real-life instances have to deal with uncertainty in many aspects of the problem, such as variable traveling times due to traffic conditions or customers availability. We present a hybrid simheuristic algorithm that combines biased-randomized routing and packing heuristics within a multi-start framework. Monte Carlo simulation is used to deal with uncertainty at different stages of the search process. With the goal of minimizing total expected cost, we use this methodology to solve a set of stochastic instances of the 2L-VRP with unrestricted oriented loading. Our results show that accounting for systems variability during the algorithm search yields more robust solutions with lower expected costs.
Language: English
URI: http://hdl.handle.net/10609/90878
ISBN: 9781509044863
ISSN: 1558-4305MIAR
Appears in Collections:Articles

Share:
Export:
Files in This Item:
There are no files associated with this item.

Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.