@misc{10818/48474,
year = {2019},
month = {10},
url = {http://hdl.handle.net/10818/48474},
abstract = {The capacitated location routing problem (CLRP) integrates a facility location problem with a
multi-depot vehicle routing problem. We consider the CLRP with stochastic demands, whose
specific values are only revealed upon reaching each customer. The main goal is to minimise
the expected costs of: (i) opening facilities, (ii) using a fleet of vehicles, (iii) executing a routing
plan, and (iv) applying corrective actions. The latter are required whenever a route failure
occurs due to unexpected high demands. We propose a simheuristic algorithm hybridizing
simulation with an iterated local search metaheuristic, aimed at: (i) proposing a safety-stock
policy to diminish the likelihood of route failure; and, (ii) estimating the expected cost and the
reliability of each “elite” solution. We assess our approach on classical CLRP benchmarks, which
are later extended to consider demand uncertainty. Finally, we also discuss the effects of the
safety-stock policy on costs and reliability.},
publisher = {Journal of Simulation},
keywords = {Location routing problem},
keywords = {Stochastic demands},
keywords = {Simheuristics},
keywords = {Iterated local search},
keywords = {Biased randomisation},
title = {A simheuristic algorithm for the capacitated
location routing problem with stochastic demands},
doi = {10.1080/17477778.2019.1680262},
author = {Quintero Araujo, Carlos L. and Guimarans, Daniel and Juan, Angel A.},
}