Citation
Tabu search techniques for the heterogeneous vehicle routing problem with time windows and carrier-dependent costs. Journal of Scheduling, 14 (6): 601-615, 2011.
Selected
Abstract
In this work we formalize a new complex variant of the classical vehicle routing problem arising from a real-world application. Our formulation includes a heterogeneous fleet, a multi-day planning horizon, a complex carrierdependent cost for vehicles, and the possibility of leaving orders unscheduled. For tackling this problem we propose a metaheuristic approach based on Tabu Search and on a combination of neighborhood relations. We perform an experimental analysis to tune and compare different combinations, highlighting the most important features of the algorithm. The outcome is that a significant improvement is obtained by a complex combination of neighborhood relations. In addition, we compare our solver with previous work on public benchmarks of a similar version of the problem, namely the Vehicle Routing Problem with Private fleet and Common carrier. The conclusion is that our results are competitive with the best ones in literature.
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Bibtex
@ARTICLE{2011-601-615-SI, author = {S. Ceschia and L. Di Gaspero and A. Schaerf},
title = {Tabu search techniques for the heterogeneous vehicle routing problem with time windows and carrier-dependent costs},
journal = {Journal of Scheduling},
year = {2011},
volume = {14},
pages = {601--615},
number = {6},
note = {Selected},
abstract = {In this work we formalize a new complex variant of the classical vehicle routing problem arising from a real-world application. Our formulation includes a heterogeneous fleet, a multi-day planning horizon, a complex carrierdependent cost for vehicles, and the possibility of leaving orders unscheduled. For tackling this problem we propose a metaheuristic approach based on Tabu Search and on a combination of neighborhood relations. We perform an experimental analysis to tune and compare different combinations, highlighting the most important features of the algorithm. The outcome is that a significant improvement is obtained by a complex combination of neighborhood relations. In addition, we compare our solver with previous work on public benchmarks of a similar version of the problem, namely the Vehicle Routing Problem with Private fleet and Common carrier. The conclusion is that our results are competitive with the best ones in literature.},
doi = {10.1007/s10951-010-0213-x},
owner = {user},
timestamp = {2012.05.25} }